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common module

This module contains some common functions for both folium and ipyleaflet.

PlanetaryComputerEndpoint (TitilerEndpoint)

This class contains the methods for the Microsoft Planetary Computer endpoint.

Source code in leafmap/common.py
class PlanetaryComputerEndpoint(TitilerEndpoint):
    """This class contains the methods for the Microsoft Planetary Computer endpoint."""

    def __init__(
        self,
        endpoint="https://planetarycomputer.microsoft.com/api/data/v1",
        name="item",
        TileMatrixSetId="WebMercatorQuad",
    ):
        """Initialize the PlanetaryComputerEndpoint object.

        Args:
            endpoint (str, optional): The endpoint of the titiler server. Defaults to "https://planetarycomputer.microsoft.com/api/data/v1".
            name (str, optional): The name to be used in the file path. Defaults to "item".
            TileMatrixSetId (str, optional): The TileMatrixSetId to be used in the file path. Defaults to "WebMercatorQuad".
        """
        super().__init__(endpoint, name, TileMatrixSetId)

    def url_for_stac_collection(self):
        return f"{self.endpoint}/collection/{self.TileMatrixSetId}/tilejson.json"

    def url_for_collection_assets(self):
        return f"{self.endpoint}/collection/assets"

    def url_for_collection_bounds(self):
        return f"{self.endpoint}/collection/bounds"

    def url_for_collection_info(self):
        return f"{self.endpoint}/collection/info"

    def url_for_collection_info_geojson(self):
        return f"{self.endpoint}/collection/info.geojson"

    def url_for_collection_pixel_value(self, lon, lat):
        return f"{self.endpoint}/collection/point/{lon},{lat}"

    def url_for_collection_wmts(self):
        return f"{self.endpoint}/collection/{self.TileMatrixSetId}/WMTSCapabilities.xml"

    def url_for_collection_lat_lon_assets(self, lng, lat):
        return f"{self.endpoint}/collection/{lng},{lat}/assets"

    def url_for_collection_bbox_assets(self, minx, miny, maxx, maxy):
        return f"{self.endpoint}/collection/{minx},{miny},{maxx},{maxy}/assets"

    def url_for_stac_mosaic(self, searchid):
        return f"{self.endpoint}/mosaic/{searchid}/{self.TileMatrixSetId}/tilejson.json"

    def url_for_mosaic_info(self, searchid):
        return f"{self.endpoint}/mosaic/{searchid}/info"

    def url_for_mosaic_lat_lon_assets(self, searchid, lon, lat):
        return f"{self.endpoint}/mosaic/{searchid}/{lon},{lat}/assets"

__init__(self, endpoint='https://planetarycomputer.microsoft.com/api/data/v1', name='item', TileMatrixSetId='WebMercatorQuad') special

Initialize the PlanetaryComputerEndpoint object.

Parameters:

Name Type Description Default
endpoint str

The endpoint of the titiler server. Defaults to "https://planetarycomputer.microsoft.com/api/data/v1".

'https://planetarycomputer.microsoft.com/api/data/v1'
name str

The name to be used in the file path. Defaults to "item".

'item'
TileMatrixSetId str

The TileMatrixSetId to be used in the file path. Defaults to "WebMercatorQuad".

'WebMercatorQuad'
Source code in leafmap/common.py
def __init__(
    self,
    endpoint="https://planetarycomputer.microsoft.com/api/data/v1",
    name="item",
    TileMatrixSetId="WebMercatorQuad",
):
    """Initialize the PlanetaryComputerEndpoint object.

    Args:
        endpoint (str, optional): The endpoint of the titiler server. Defaults to "https://planetarycomputer.microsoft.com/api/data/v1".
        name (str, optional): The name to be used in the file path. Defaults to "item".
        TileMatrixSetId (str, optional): The TileMatrixSetId to be used in the file path. Defaults to "WebMercatorQuad".
    """
    super().__init__(endpoint, name, TileMatrixSetId)

TitilerEndpoint

This class contains the methods for the titiler endpoint.

Source code in leafmap/common.py
class TitilerEndpoint:
    """This class contains the methods for the titiler endpoint."""

    def __init__(
        self,
        endpoint="https://titiler.xyz",
        name="stac",
        TileMatrixSetId="WebMercatorQuad",
    ):
        """Initialize the TitilerEndpoint object.

        Args:
            endpoint (str, optional): The endpoint of the titiler server. Defaults to "https://titiler.xyz".
            name (str, optional): The name to be used in the file path. Defaults to "stac".
            TileMatrixSetId (str, optional): The TileMatrixSetId to be used in the file path. Defaults to "WebMercatorQuad".
        """
        self.endpoint = endpoint
        self.name = name
        self.TileMatrixSetId = TileMatrixSetId

    def url_for_stac_item(self):
        return f"{self.endpoint}/{self.name}/{self.TileMatrixSetId}/tilejson.json"

    def url_for_stac_assets(self):
        return f"{self.endpoint}/{self.name}/assets"

    def url_for_stac_bounds(self):
        return f"{self.endpoint}/{self.name}/bounds"

    def url_for_stac_info(self):
        return f"{self.endpoint}/{self.name}/info"

    def url_for_stac_info_geojson(self):
        return f"{self.endpoint}/{self.name}/info.geojson"

    def url_for_stac_statistics(self):
        return f"{self.endpoint}/{self.name}/statistics"

    def url_for_stac_pixel_value(self, lon, lat):
        return f"{self.endpoint}/{self.name}/point/{lon},{lat}"

    def url_for_stac_wmts(self):
        return (
            f"{self.endpoint}/{self.name}/{self.TileMatrixSetId}/WMTSCapabilities.xml"
        )

__init__(self, endpoint='https://titiler.xyz', name='stac', TileMatrixSetId='WebMercatorQuad') special

Initialize the TitilerEndpoint object.

Parameters:

Name Type Description Default
endpoint str

The endpoint of the titiler server. Defaults to "https://titiler.xyz".

'https://titiler.xyz'
name str

The name to be used in the file path. Defaults to "stac".

'stac'
TileMatrixSetId str

The TileMatrixSetId to be used in the file path. Defaults to "WebMercatorQuad".

'WebMercatorQuad'
Source code in leafmap/common.py
def __init__(
    self,
    endpoint="https://titiler.xyz",
    name="stac",
    TileMatrixSetId="WebMercatorQuad",
):
    """Initialize the TitilerEndpoint object.

    Args:
        endpoint (str, optional): The endpoint of the titiler server. Defaults to "https://titiler.xyz".
        name (str, optional): The name to be used in the file path. Defaults to "stac".
        TileMatrixSetId (str, optional): The TileMatrixSetId to be used in the file path. Defaults to "WebMercatorQuad".
    """
    self.endpoint = endpoint
    self.name = name
    self.TileMatrixSetId = TileMatrixSetId

WhiteboxTools (WhiteboxTools)

This class inherits the whitebox WhiteboxTools class.

Source code in leafmap/common.py
class WhiteboxTools(whitebox.WhiteboxTools):
    """This class inherits the whitebox WhiteboxTools class."""

    def __init__(self, **kwargs):

        super().__init__(**kwargs)

__install_from_github(url)

Install a package from a GitHub repository.

Parameters:

Name Type Description Default
url str

The URL of the GitHub repository.

required
Source code in leafmap/common.py
def __install_from_github(url):
    """Install a package from a GitHub repository.

    Args:
        url (str): The URL of the GitHub repository.
    """

    try:
        download_dir = os.path.join(os.path.expanduser("~"), "Downloads")
        if not os.path.exists(download_dir):
            os.makedirs(download_dir)

        repo_name = os.path.basename(url)
        zip_url = os.path.join(url, "archive/master.zip")
        filename = repo_name + "-master.zip"
        download_from_url(
            url=zip_url, out_file_name=filename, out_dir=download_dir, unzip=True
        )

        pkg_dir = os.path.join(download_dir, repo_name + "-master")
        pkg_name = os.path.basename(url)
        work_dir = os.getcwd()
        os.chdir(pkg_dir)
        print("Installing {}...".format(pkg_name))
        cmd = "pip install ."
        os.system(cmd)
        os.chdir(work_dir)
        print("{} has been installed successfully.".format(pkg_name))
        # print("\nPlease comment out 'install_from_github()' and restart the kernel to take effect:\nJupyter menu -> Kernel -> Restart & Clear Output")

    except Exception as e:
        raise Exception(e)

adjust_longitude(in_fc)

Adjusts longitude if it is less than -180 or greater than 180.

Parameters:

Name Type Description Default
in_fc dict

The input dictionary containing coordinates.

required

Returns:

Type Description
dict

A dictionary containing the converted longitudes

Source code in leafmap/common.py
def adjust_longitude(in_fc):
    """Adjusts longitude if it is less than -180 or greater than 180.

    Args:
        in_fc (dict): The input dictionary containing coordinates.

    Returns:
        dict: A dictionary containing the converted longitudes
    """
    try:

        keys = in_fc.keys()

        if "geometry" in keys:

            coordinates = in_fc["geometry"]["coordinates"]

            if in_fc["geometry"]["type"] == "Point":
                longitude = coordinates[0]
                if longitude < -180:
                    longitude = 360 + longitude
                elif longitude > 180:
                    longitude = longitude - 360
                in_fc["geometry"]["coordinates"][0] = longitude

            elif in_fc["geometry"]["type"] == "Polygon":
                for index1, item in enumerate(coordinates):
                    for index2, element in enumerate(item):
                        longitude = element[0]
                        if longitude < -180:
                            longitude = 360 + longitude
                        elif longitude > 180:
                            longitude = longitude - 360
                        in_fc["geometry"]["coordinates"][index1][index2][0] = longitude

            elif in_fc["geometry"]["type"] == "LineString":
                for index, element in enumerate(coordinates):
                    longitude = element[0]
                    if longitude < -180:
                        longitude = 360 + longitude
                    elif longitude > 180:
                        longitude = longitude - 360
                    in_fc["geometry"]["coordinates"][index][0] = longitude

        elif "type" in keys:

            coordinates = in_fc["coordinates"]

            if in_fc["type"] == "Point":
                longitude = coordinates[0]
                if longitude < -180:
                    longitude = 360 + longitude
                elif longitude > 180:
                    longitude = longitude - 360
                in_fc["coordinates"][0] = longitude

            elif in_fc["type"] == "Polygon":
                for index1, item in enumerate(coordinates):
                    for index2, element in enumerate(item):
                        longitude = element[0]
                        if longitude < -180:
                            longitude = 360 + longitude
                        elif longitude > 180:
                            longitude = longitude - 360
                        in_fc["coordinates"][index1][index2][0] = longitude

            elif in_fc["type"] == "LineString":
                for index, element in enumerate(coordinates):
                    longitude = element[0]
                    if longitude < -180:
                        longitude = 360 + longitude
                    elif longitude > 180:
                        longitude = longitude - 360
                    in_fc["coordinates"][index][0] = longitude

        return in_fc

    except Exception as e:
        print(e)
        return None

basemap_xyz_tiles()

Returns a dictionary containing a set of basemaps that are XYZ tile layers.

Returns:

Type Description
dict

A dictionary of XYZ tile layers.

Source code in leafmap/common.py
def basemap_xyz_tiles():
    """Returns a dictionary containing a set of basemaps that are XYZ tile layers.

    Returns:
        dict: A dictionary of XYZ tile layers.
    """
    from .leafmap import basemaps

    layers_dict = {}
    keys = dict(basemaps).keys()
    for key in keys:
        if isinstance(basemaps[key], ipyleaflet.WMSLayer):
            pass
        else:
            layers_dict[key] = basemaps[key]
    return layers_dict

bbox_to_gdf(bbox, crs='EPSG:4326')

Converts a bounding box to a GeoDataFrame.

Parameters:

Name Type Description Default
bbox tuple

A bounding box in the form of a tuple (minx, miny, maxx, maxy).

required
crs str

The coordinate reference system of the bounding box to convert to. Defaults to "EPSG:4326".

'EPSG:4326'

Returns:

Type Description
geopandas.GeoDataFrame

A GeoDataFrame containing the bounding box.

Source code in leafmap/common.py
def bbox_to_gdf(bbox, crs="EPSG:4326"):
    """Converts a bounding box to a GeoDataFrame.

    Args:
        bbox (tuple): A bounding box in the form of a tuple (minx, miny, maxx, maxy).
        crs (str, optional): The coordinate reference system of the bounding box to convert to. Defaults to "EPSG:4326".

    Returns:
        geopandas.GeoDataFrame: A GeoDataFrame containing the bounding box.
    """
    check_package(name="geopandas", URL="https://geopandas.org")
    from shapely.geometry import box
    import geopandas as gpd

    minx, miny, maxx, maxy = bbox
    geometry = box(minx, miny, maxx, maxy)
    d = {"geometry": [geometry]}
    gdf = gpd.GeoDataFrame(d, crs="EPSG:4326")
    gdf.to_crs(crs=crs, inplace=True)
    return gdf

bbox_to_geojson(bounds)

Convert coordinates of a bounding box to a geojson.

Parameters:

Name Type Description Default
bounds list

A list of coordinates representing [left, bottom, right, top].

required

Returns:

Type Description
dict

A geojson feature.

Source code in leafmap/common.py
def bbox_to_geojson(bounds):
    """Convert coordinates of a bounding box to a geojson.

    Args:
        bounds (list): A list of coordinates representing [left, bottom, right, top].

    Returns:
        dict: A geojson feature.
    """
    return {
        "geometry": {
            "type": "Polygon",
            "coordinates": [
                [
                    [bounds[0], bounds[3]],
                    [bounds[0], bounds[1]],
                    [bounds[2], bounds[1]],
                    [bounds[2], bounds[3]],
                    [bounds[0], bounds[3]],
                ]
            ],
        },
        "type": "Feature",
    }

cesium_to_streamlit(html, width=800, height=600, responsive=True, scrolling=False, token_name=None, token_value=None, **kwargs)

Renders an cesium HTML file in a Streamlit app. This method is a static Streamlit Component, meaning, no information is passed back from Leaflet on browser interaction.

Parameters:

Name Type Description Default
html str

The HTML file to render. It can a local file path or a URL.

required
width int

Width of the map. Defaults to 800.

800
height int

Height of the map. Defaults to 600.

600
responsive bool

Whether to make the map responsive. Defaults to True.

True
scrolling bool

Whether to allow the map to scroll. Defaults to False.

False
token_name str

The name of the token in the HTML file to be replaced. Defaults to None.

None
token_value str

The value of the token to pass to the HTML file. Defaults to None.

None

Returns:

Type Description
streamlit.components

components.html object.

Source code in leafmap/common.py
def cesium_to_streamlit(
    html,
    width=800,
    height=600,
    responsive=True,
    scrolling=False,
    token_name=None,
    token_value=None,
    **kwargs,
):
    """Renders an cesium HTML file in a Streamlit app. This method is a static Streamlit Component, meaning, no information is passed back from Leaflet on browser interaction.

    Args:
        html (str): The HTML file to render. It can a local file path or a URL.
        width (int, optional): Width of the map. Defaults to 800.
        height (int, optional): Height of the map. Defaults to 600.
        responsive (bool, optional): Whether to make the map responsive. Defaults to True.
        scrolling (bool, optional): Whether to allow the map to scroll. Defaults to False.
        token_name (str, optional): The name of the token in the HTML file to be replaced. Defaults to None.
        token_value (str, optional): The value of the token to pass to the HTML file. Defaults to None.

    Returns:
        streamlit.components: components.html object.
    """
    if token_name is None:
        token_name = "your_access_token"

    if token_value is None:
        token_value = os.environ.get("CESIUM_TOKEN")

    html_to_streamlit(
        html, width, height, responsive, scrolling, token_name, token_value
    )

check_cmap(cmap)

Check the colormap and return a list of colors.

Parameters:

Name Type Description Default
cmap str | list | Box

The colormap to check.

required

Returns:

Type Description
list

A list of colors.

Source code in leafmap/common.py
def check_cmap(cmap):
    """Check the colormap and return a list of colors.

    Args:
        cmap (str | list | Box): The colormap to check.

    Returns:
        list: A list of colors.
    """

    from box import Box
    from .colormaps import get_palette

    if isinstance(cmap, str):
        try:
            return get_palette(cmap)
        except Exception as e:
            raise Exception(f"{cmap} is not a valid colormap.")
    elif isinstance(cmap, Box):
        return list(cmap["default"])
    elif isinstance(cmap, list) or isinstance(cmap, tuple):
        return cmap
    else:
        raise Exception(f"{cmap} is not a valid colormap.")

check_color(in_color)

Checks the input color and returns the corresponding hex color code.

Parameters:

Name Type Description Default
in_color str or tuple

It can be a string (e.g., 'red', '#ffff00') or tuple (e.g., (255, 127, 0)).

required

Returns:

Type Description
str

A hex color code.

Source code in leafmap/common.py
def check_color(in_color):
    """Checks the input color and returns the corresponding hex color code.

    Args:
        in_color (str or tuple): It can be a string (e.g., 'red', '#ffff00') or tuple (e.g., (255, 127, 0)).

    Returns:
        str: A hex color code.
    """
    import colour

    out_color = "#000000"  # default black color
    if isinstance(in_color, tuple) and len(in_color) == 3:
        if all(isinstance(item, int) for item in in_color):
            rescaled_color = [x / 255.0 for x in in_color]
            out_color = colour.Color(rgb=tuple(rescaled_color))
            return out_color.hex_l
        else:
            print(
                "RGB color must be a tuple with three integer values ranging from 0 to 255."
            )
            return
    else:
        try:
            out_color = colour.Color(in_color)
            return out_color.hex_l
        except Exception as e:
            print("The provided color is invalid. Using the default black color.")
            print(e)
            return out_color

check_dir(dir_path, make_dirs=True)

Checks if a directory exists and creates it if it does not.

Parameters:

Name Type Description Default
dir_path [str

The path to the directory.

required
make_dirs bool

Whether to create the directory if it does not exist. Defaults to True.

True

Exceptions:

Type Description
FileNotFoundError

If the directory could not be found.

TypeError

If the input directory path is not a string.

Returns:

Type Description
str

The path to the directory.

Source code in leafmap/common.py
def check_dir(dir_path, make_dirs=True):
    """Checks if a directory exists and creates it if it does not.

    Args:
        dir_path ([str): The path to the directory.
        make_dirs (bool, optional): Whether to create the directory if it does not exist. Defaults to True.

    Raises:
        FileNotFoundError: If the directory could not be found.
        TypeError: If the input directory path is not a string.

    Returns:
        str: The path to the directory.
    """

    if isinstance(dir_path, str):
        if dir_path.startswith("~"):
            dir_path = os.path.expanduser(dir_path)
        else:
            dir_path = os.path.abspath(dir_path)

        if not os.path.exists(dir_path) and make_dirs:
            os.makedirs(dir_path)

        if os.path.exists(dir_path):
            return dir_path
        else:
            raise FileNotFoundError("The provided directory could not be found.")
    else:
        raise TypeError("The provided directory path must be a string.")

check_file_path(file_path, make_dirs=True)

Gets the absolute file path.

Parameters:

Name Type Description Default
file_path str

The path to the file.

required
make_dirs bool

Whether to create the directory if it does not exist. Defaults to True.

True

Exceptions:

Type Description
FileNotFoundError

If the directory could not be found.

TypeError

If the input directory path is not a string.

Returns:

Type Description
str

The absolute path to the file.

Source code in leafmap/common.py
def check_file_path(file_path, make_dirs=True):
    """Gets the absolute file path.

    Args:
        file_path (str): The path to the file.
        make_dirs (bool, optional): Whether to create the directory if it does not exist. Defaults to True.

    Raises:
        FileNotFoundError: If the directory could not be found.
        TypeError: If the input directory path is not a string.

    Returns:
        str: The absolute path to the file.
    """
    if isinstance(file_path, str):
        if file_path.startswith("~"):
            file_path = os.path.expanduser(file_path)
        else:
            file_path = os.path.abspath(file_path)

        file_dir = os.path.dirname(file_path)
        if not os.path.exists(file_dir) and make_dirs:
            os.makedirs(file_dir)

        return file_path

    else:
        raise TypeError("The provided file path must be a string.")

check_titiler_endpoint(titiler_endpoint=None)

Returns the default titiler endpoint.

Returns:

Type Description
object

A titiler endpoint.

Source code in leafmap/common.py
def check_titiler_endpoint(titiler_endpoint=None):
    """Returns the default titiler endpoint.

    Returns:
        object: A titiler endpoint.
    """
    if titiler_endpoint is None:
        if os.environ.get("TITILER_ENDPOINT") == "planetary-computer":
            titiler_endpoint = PlanetaryComputerEndpoint()
        else:
            titiler_endpoint = TitilerEndpoint()
    elif titiler_endpoint in ["planetary-computer", "pc"]:
        titiler_endpoint = PlanetaryComputerEndpoint()

    return titiler_endpoint

classify(data, column, cmap=None, colors=None, labels=None, scheme='Quantiles', k=5, legend_kwds=None, classification_kwds=None)

Classify a dataframe column using a variety of classification schemes.

Parameters:

Name Type Description Default
data str | pd.DataFrame | gpd.GeoDataFrame

The data to classify. It can be a filepath to a vector dataset, a pandas dataframe, or a geopandas geodataframe.

required
column str

The column to classify.

required
cmap str

The name of a colormap recognized by matplotlib. Defaults to None.

None
colors list

A list of colors to use for the classification. Defaults to None.

None
labels list

A list of labels to use for the legend. Defaults to None.

None
scheme str

Name of a choropleth classification scheme (requires mapclassify). Name of a choropleth classification scheme (requires mapclassify). A mapclassify.MapClassifier object will be used under the hood. Supported are all schemes provided by mapclassify (e.g. 'BoxPlot', 'EqualInterval', 'FisherJenks', 'FisherJenksSampled', 'HeadTailBreaks', 'JenksCaspall', 'JenksCaspallForced', 'JenksCaspallSampled', 'MaxP', 'MaximumBreaks', 'NaturalBreaks', 'Quantiles', 'Percentiles', 'StdMean', 'UserDefined'). Arguments can be passed in classification_kwds.

'Quantiles'
k int

Number of classes (ignored if scheme is None or if column is categorical). Default to 5.

5
legend_kwds dict

Keyword arguments to pass to :func:matplotlib.pyplot.legend or matplotlib.pyplot.colorbar. Defaults to None. Keyword arguments to pass to :func:matplotlib.pyplot.legend or Additional accepted keywords when scheme is specified: fmt : string A formatting specification for the bin edges of the classes in the legend. For example, to have no decimals: {"fmt": "{:.0f}"}. labels : list-like A list of legend labels to override the auto-generated labblels. Needs to have the same number of elements as the number of classes (k). interval : boolean (default False) An option to control brackets from mapclassify legend. If True, open/closed interval brackets are shown in the legend.

None
classification_kwds dict

Keyword arguments to pass to mapclassify. Defaults to None.

None

Returns:

Type Description
pd.DataFrame, dict

A pandas dataframe with the classification applied and a legend dictionary.

Source code in leafmap/common.py
def classify(
    data,
    column,
    cmap=None,
    colors=None,
    labels=None,
    scheme="Quantiles",
    k=5,
    legend_kwds=None,
    classification_kwds=None,
):
    """Classify a dataframe column using a variety of classification schemes.

    Args:
        data (str | pd.DataFrame | gpd.GeoDataFrame): The data to classify. It can be a filepath to a vector dataset, a pandas dataframe, or a geopandas geodataframe.
        column (str): The column to classify.
        cmap (str, optional): The name of a colormap recognized by matplotlib. Defaults to None.
        colors (list, optional): A list of colors to use for the classification. Defaults to None.
        labels (list, optional): A list of labels to use for the legend. Defaults to None.
        scheme (str, optional): Name of a choropleth classification scheme (requires mapclassify).
            Name of a choropleth classification scheme (requires mapclassify).
            A mapclassify.MapClassifier object will be used
            under the hood. Supported are all schemes provided by mapclassify (e.g.
            'BoxPlot', 'EqualInterval', 'FisherJenks', 'FisherJenksSampled',
            'HeadTailBreaks', 'JenksCaspall', 'JenksCaspallForced',
            'JenksCaspallSampled', 'MaxP', 'MaximumBreaks',
            'NaturalBreaks', 'Quantiles', 'Percentiles', 'StdMean',
            'UserDefined'). Arguments can be passed in classification_kwds.
        k (int, optional): Number of classes (ignored if scheme is None or if column is categorical). Default to 5.
        legend_kwds (dict, optional): Keyword arguments to pass to :func:`matplotlib.pyplot.legend` or `matplotlib.pyplot.colorbar`. Defaults to None.
            Keyword arguments to pass to :func:`matplotlib.pyplot.legend` or
            Additional accepted keywords when `scheme` is specified:
            fmt : string
                A formatting specification for the bin edges of the classes in the
                legend. For example, to have no decimals: ``{"fmt": "{:.0f}"}``.
            labels : list-like
                A list of legend labels to override the auto-generated labblels.
                Needs to have the same number of elements as the number of
                classes (`k`).
            interval : boolean (default False)
                An option to control brackets from mapclassify legend.
                If True, open/closed interval brackets are shown in the legend.
        classification_kwds (dict, optional): Keyword arguments to pass to mapclassify. Defaults to None.

    Returns:
        pd.DataFrame, dict: A pandas dataframe with the classification applied and a legend dictionary.
    """

    import warnings
    import numpy as np
    import pandas as pd
    import geopandas as gpd
    import matplotlib as mpl
    import matplotlib.pyplot as plt

    try:
        import mapclassify
    except ImportError:
        raise ImportError(
            "mapclassify is required for this function. Install with `pip install mapclassify`."
        )

    if isinstance(data, gpd.GeoDataFrame) or isinstance(data, pd.DataFrame):
        df = data
    else:
        try:
            df = gpd.read_file(data)
        except Exception:
            raise TypeError(
                "Data must be a GeoDataFrame or a path to a file that can be read by geopandas.read_file()."
            )

    if df.empty:
        warnings.warn(
            "The GeoDataFrame you are attempting to plot is "
            "empty. Nothing has been displayed.",
            UserWarning,
        )
        return

    columns = df.columns.values.tolist()
    if column not in columns:
        raise ValueError(
            f"{column} is not a column in the GeoDataFrame. It must be one of {columns}."
        )

    # Convert categorical data to numeric
    init_column = None
    value_list = None
    if np.issubdtype(df[column].dtype, np.object0):
        value_list = df[column].unique().tolist()
        value_list.sort()
        df["category"] = df[column].replace(value_list, range(0, len(value_list)))
        init_column = column
        column = "category"
        k = len(value_list)

    if legend_kwds is not None:
        legend_kwds = legend_kwds.copy()

    # To accept pd.Series and np.arrays as column
    if isinstance(column, (np.ndarray, pd.Series)):
        if column.shape[0] != df.shape[0]:
            raise ValueError(
                "The dataframe and given column have different number of rows."
            )
        else:
            values = column

            # Make sure index of a Series matches index of df
            if isinstance(values, pd.Series):
                values = values.reindex(df.index)
    else:
        values = df[column]

    values = df[column]
    nan_idx = np.asarray(pd.isna(values), dtype="bool")

    if cmap is None:
        cmap = "Blues"
    cmap = plt.cm.get_cmap(cmap, k)
    if colors is None:
        colors = [mpl.colors.rgb2hex(cmap(i))[1:] for i in range(cmap.N)]
        colors = ["#" + i for i in colors]
    elif isinstance(colors, list):
        colors = [check_color(i) for i in colors]
    elif isinstance(colors, str):
        colors = [check_color(colors)] * k

    allowed_schemes = [
        "BoxPlot",
        "EqualInterval",
        "FisherJenks",
        "FisherJenksSampled",
        "HeadTailBreaks",
        "JenksCaspall",
        "JenksCaspallForced",
        "JenksCaspallSampled",
        "MaxP",
        "MaximumBreaks",
        "NaturalBreaks",
        "Quantiles",
        "Percentiles",
        "StdMean",
        "UserDefined",
    ]

    if scheme.lower() not in [s.lower() for s in allowed_schemes]:
        raise ValueError(
            f"{scheme} is not a valid scheme. It must be one of {allowed_schemes}."
        )

    if classification_kwds is None:
        classification_kwds = {}
    if "k" not in classification_kwds:
        classification_kwds["k"] = k

    binning = mapclassify.classify(
        np.asarray(values[~nan_idx]), scheme, **classification_kwds
    )
    df["category"] = binning.yb
    df["color"] = [colors[i] for i in df["category"]]

    if legend_kwds is None:
        legend_kwds = {}

    if "interval" not in legend_kwds:
        legend_kwds["interval"] = True

    if "fmt" not in legend_kwds:
        if np.issubdtype(df[column].dtype, np.floating):
            legend_kwds["fmt"] = "{:.2f}"
        else:
            legend_kwds["fmt"] = "{:.0f}"

    if labels is None:
        # set categorical to True for creating the legend
        if legend_kwds is not None and "labels" in legend_kwds:
            if len(legend_kwds["labels"]) != binning.k:
                raise ValueError(
                    "Number of labels must match number of bins, "
                    "received {} labels for {} bins".format(
                        len(legend_kwds["labels"]), binning.k
                    )
                )
            else:
                labels = list(legend_kwds.pop("labels"))
        else:
            # fmt = "{:.2f}"
            if legend_kwds is not None and "fmt" in legend_kwds:
                fmt = legend_kwds.pop("fmt")

            labels = binning.get_legend_classes(fmt)
            if legend_kwds is not None:
                show_interval = legend_kwds.pop("interval", False)
            else:
                show_interval = False
            if not show_interval:
                labels = [c[1:-1] for c in labels]

        if init_column is not None:
            labels = value_list
    elif isinstance(labels, list):
        if len(labels) != len(colors):
            raise ValueError("The number of labels must match the number of colors.")
    else:
        raise ValueError("labels must be a list or None.")

    legend_dict = dict(zip(labels, colors))
    df["category"] = df["category"] + 1
    return df, legend_dict

clip_image(image, mask, output)

Clip an image by mask.

Parameters:

Name Type Description Default
image str

Path to the image file in GeoTIFF format.

required
mask str | list | dict

The mask used to extract the image. It can be a path to vector datasets (e.g., GeoJSON, Shapefile), a list of coordinates, or m.user_roi.

required
output str

Path to the output file.

required

Exceptions:

Type Description
ImportError

If the fiona or rasterio package is not installed.

FileNotFoundError

If the image is not found.

ValueError

If the mask is not a valid GeoJSON or raster file.

FileNotFoundError

If the mask file is not found.

Source code in leafmap/common.py
def clip_image(image, mask, output):
    """Clip an image by mask.

    Args:
        image (str): Path to the image file in GeoTIFF format.
        mask (str | list | dict): The mask used to extract the image. It can be a path to vector datasets (e.g., GeoJSON, Shapefile), a list of coordinates, or m.user_roi.
        output (str): Path to the output file.

    Raises:
        ImportError: If the fiona or rasterio package is not installed.
        FileNotFoundError: If the image is not found.
        ValueError: If the mask is not a valid GeoJSON or raster file.
        FileNotFoundError: If the mask file is not found.
    """
    try:
        import json
        import fiona
        import rasterio
        import rasterio.mask
    except ImportError as e:
        raise ImportError(e)

    if not os.path.exists(image):
        raise FileNotFoundError(f"{image} does not exist.")

    if not output.endswith(".tif"):
        raise ValueError("Output must be a tif file.")

    output = check_file_path(output)

    if isinstance(mask, str):
        if not os.path.exists(mask):
            raise FileNotFoundError(f"{mask} does not exist.")
    elif isinstance(mask, list) or isinstance(mask, dict):

        if isinstance(mask, list):
            geojson = {
                "type": "FeatureCollection",
                "features": [
                    {
                        "type": "Feature",
                        "properties": {},
                        "geometry": {"type": "Polygon", "coordinates": [mask]},
                    }
                ],
            }
        else:
            geojson = {
                "type": "FeatureCollection",
                "features": [mask],
            }
        mask = temp_file_path(".geojson")
        with open(mask, "w") as f:
            json.dump(geojson, f)

    with fiona.open(mask, "r") as shapefile:
        shapes = [feature["geometry"] for feature in shapefile]

    with rasterio.open(image) as src:
        out_image, out_transform = rasterio.mask.mask(src, shapes, crop=True)
        out_meta = src.meta

    out_meta.update(
        {
            "driver": "GTiff",
            "height": out_image.shape[1],
            "width": out_image.shape[2],
            "transform": out_transform,
        }
    )

    with rasterio.open(output, "w", **out_meta) as dest:
        dest.write(out_image)

cog_bands(url, titiler_endpoint='https://titiler.xyz')

Get band names of a Cloud Optimized GeoTIFF (COG).

Parameters:

Name Type Description Default
url str

HTTP URL to a COG, e.g., https://opendata.digitalglobe.com/events/mauritius-oil-spill/post-event/2020-08-12/105001001F1B5B00/105001001F1B5B00.tif

required
titiler_endpoint str

Titiler endpoint. Defaults to "https://titiler.xyz".

'https://titiler.xyz'

Returns:

Type Description
list

A list of band names

Source code in leafmap/common.py
def cog_bands(url, titiler_endpoint="https://titiler.xyz"):
    """Get band names of a Cloud Optimized GeoTIFF (COG).

    Args:
        url (str): HTTP URL to a COG, e.g., https://opendata.digitalglobe.com/events/mauritius-oil-spill/post-event/2020-08-12/105001001F1B5B00/105001001F1B5B00.tif
        titiler_endpoint (str, optional): Titiler endpoint. Defaults to "https://titiler.xyz".

    Returns:
        list: A list of band names
    """

    r = requests.get(
        f"{titiler_endpoint}/cog/info",
        params={
            "url": url,
        },
    ).json()

    bands = [b[0] for b in r["band_descriptions"]]
    return bands

cog_bounds(url, titiler_endpoint='https://titiler.xyz')

Get the bounding box of a Cloud Optimized GeoTIFF (COG).

Parameters:

Name Type Description Default
url str

HTTP URL to a COG, e.g., https://opendata.digitalglobe.com/events/mauritius-oil-spill/post-event/2020-08-12/105001001F1B5B00/105001001F1B5B00.tif

required
titiler_endpoint str

Titiler endpoint. Defaults to "https://titiler.xyz".

'https://titiler.xyz'

Returns:

Type Description
list

A list of values representing [left, bottom, right, top]

Source code in leafmap/common.py
def cog_bounds(url, titiler_endpoint="https://titiler.xyz"):
    """Get the bounding box of a Cloud Optimized GeoTIFF (COG).

    Args:
        url (str): HTTP URL to a COG, e.g., https://opendata.digitalglobe.com/events/mauritius-oil-spill/post-event/2020-08-12/105001001F1B5B00/105001001F1B5B00.tif
        titiler_endpoint (str, optional): Titiler endpoint. Defaults to "https://titiler.xyz".

    Returns:
        list: A list of values representing [left, bottom, right, top]
    """

    r = requests.get(f"{titiler_endpoint}/cog/bounds", params={"url": url}).json()

    if "bounds" in r.keys():
        bounds = r["bounds"]
    else:
        bounds = None
    return bounds

cog_center(url, titiler_endpoint='https://titiler.xyz')

Get the centroid of a Cloud Optimized GeoTIFF (COG).

Parameters:

Name Type Description Default
url str

HTTP URL to a COG, e.g., https://opendata.digitalglobe.com/events/mauritius-oil-spill/post-event/2020-08-12/105001001F1B5B00/105001001F1B5B00.tif

required
titiler_endpoint str

Titiler endpoint. Defaults to "https://titiler.xyz".

'https://titiler.xyz'

Returns:

Type Description
tuple

A tuple representing (longitude, latitude)

Source code in leafmap/common.py
def cog_center(url, titiler_endpoint="https://titiler.xyz"):
    """Get the centroid of a Cloud Optimized GeoTIFF (COG).

    Args:
        url (str): HTTP URL to a COG, e.g., https://opendata.digitalglobe.com/events/mauritius-oil-spill/post-event/2020-08-12/105001001F1B5B00/105001001F1B5B00.tif
        titiler_endpoint (str, optional): Titiler endpoint. Defaults to "https://titiler.xyz".

    Returns:
        tuple: A tuple representing (longitude, latitude)
    """
    bounds = cog_bounds(url, titiler_endpoint)
    center = ((bounds[0] + bounds[2]) / 2, (bounds[1] + bounds[3]) / 2)  # (lat, lon)
    return center

cog_info(url, titiler_endpoint='https://titiler.xyz', return_geojson=False)

Get band statistics of a Cloud Optimized GeoTIFF (COG).

Parameters:

Name Type Description Default
url str

HTTP URL to a COG, e.g., https://opendata.digitalglobe.com/events/mauritius-oil-spill/post-event/2020-08-12/105001001F1B5B00/105001001F1B5B00.tif

required
titiler_endpoint str

Titiler endpoint. Defaults to "https://titiler.xyz".

'https://titiler.xyz'

Returns:

Type Description
list

A dictionary of band info.

Source code in leafmap/common.py
def cog_info(url, titiler_endpoint="https://titiler.xyz", return_geojson=False):
    """Get band statistics of a Cloud Optimized GeoTIFF (COG).

    Args:
        url (str): HTTP URL to a COG, e.g., https://opendata.digitalglobe.com/events/mauritius-oil-spill/post-event/2020-08-12/105001001F1B5B00/105001001F1B5B00.tif
        titiler_endpoint (str, optional): Titiler endpoint. Defaults to "https://titiler.xyz".

    Returns:
        list: A dictionary of band info.
    """

    info = "info"
    if return_geojson:
        info = "info.geojson"

    r = requests.get(
        f"{titiler_endpoint}/cog/{info}",
        params={
            "url": url,
        },
    ).json()

    return r

cog_mosaic(links, titiler_endpoint='https://titiler.xyz', username='anonymous', layername=None, overwrite=False, verbose=True, **kwargs)

Creates a COG mosaic from a list of COG URLs.

Parameters:

Name Type Description Default
links list

A list containing COG HTTP URLs.

required
titiler_endpoint str

Titiler endpoint. Defaults to "https://titiler.xyz".

'https://titiler.xyz'
username str

User name for the titiler endpoint. Defaults to "anonymous".

'anonymous'
layername [type]

Layer name to use. Defaults to None.

None
overwrite bool

Whether to overwrite the layer name if existing. Defaults to False.

False
verbose bool

Whether to print out descriptive information. Defaults to True.

True

Exceptions:

Type Description
Exception

If the COG mosaic fails to create.

Returns:

Type Description
str

The tile URL for the COG mosaic.

Source code in leafmap/common.py
def cog_mosaic(
    links,
    titiler_endpoint="https://titiler.xyz",
    username="anonymous",
    layername=None,
    overwrite=False,
    verbose=True,
    **kwargs,
):
    """Creates a COG mosaic from a list of COG URLs.

    Args:
        links (list): A list containing COG HTTP URLs.
        titiler_endpoint (str, optional): Titiler endpoint. Defaults to "https://titiler.xyz".
        username (str, optional): User name for the titiler endpoint. Defaults to "anonymous".
        layername ([type], optional): Layer name to use. Defaults to None.
        overwrite (bool, optional): Whether to overwrite the layer name if existing. Defaults to False.
        verbose (bool, optional): Whether to print out descriptive information. Defaults to True.

    Raises:
        Exception: If the COG mosaic fails to create.

    Returns:
        str: The tile URL for the COG mosaic.
    """

    if layername is None:
        layername = "layer_" + random_string(5)

    try:
        if verbose:
            print("Creating COG masaic ...")

        # Create token
        r = requests.post(
            f"{titiler_endpoint}/tokens/create",
            json={"username": username, "scope": ["mosaic:read", "mosaic:create"]},
        ).json()
        token = r["token"]

        # Create mosaic
        requests.post(
            f"{titiler_endpoint}/mosaicjson/create",
            json={
                "username": username,
                "layername": layername,
                "files": links,
                # "overwrite": overwrite
            },
            params={
                "access_token": token,
            },
        ).json()

        r2 = requests.get(
            f"{titiler_endpoint}/mosaicjson/{username}.{layername}/tilejson.json",
        ).json()

        return r2["tiles"][0]

    except Exception as e:
        raise Exception(e)

cog_mosaic_from_file(filepath, skip_rows=0, titiler_endpoint='https://titiler.xyz', username='anonymous', layername=None, overwrite=False, verbose=True, **kwargs)

Creates a COG mosaic from a csv/txt file stored locally for through HTTP URL.

Parameters:

Name Type Description Default
filepath str

Local path or HTTP URL to the csv/txt file containing COG URLs.

required
skip_rows int

The number of rows to skip in the file. Defaults to 0.

0
titiler_endpoint str

Titiler endpoint. Defaults to "https://titiler.xyz".

'https://titiler.xyz'
username str

User name for the titiler endpoint. Defaults to "anonymous".

'anonymous'
layername [type]

Layer name to use. Defaults to None.

None
overwrite bool

Whether to overwrite the layer name if existing. Defaults to False.

False
verbose bool

Whether to print out descriptive information. Defaults to True.

True

Returns:

Type Description
str

The tile URL for the COG mosaic.

Source code in leafmap/common.py
def cog_mosaic_from_file(
    filepath,
    skip_rows=0,
    titiler_endpoint="https://titiler.xyz",
    username="anonymous",
    layername=None,
    overwrite=False,
    verbose=True,
    **kwargs,
):
    """Creates a COG mosaic from a csv/txt file stored locally for through HTTP URL.

    Args:
        filepath (str): Local path or HTTP URL to the csv/txt file containing COG URLs.
        skip_rows (int, optional): The number of rows to skip in the file. Defaults to 0.
        titiler_endpoint (str, optional): Titiler endpoint. Defaults to "https://titiler.xyz".
        username (str, optional): User name for the titiler endpoint. Defaults to "anonymous".
        layername ([type], optional): Layer name to use. Defaults to None.
        overwrite (bool, optional): Whether to overwrite the layer name if existing. Defaults to False.
        verbose (bool, optional): Whether to print out descriptive information. Defaults to True.

    Returns:
        str: The tile URL for the COG mosaic.
    """
    import urllib

    links = []
    if filepath.startswith("http"):
        data = urllib.request.urlopen(filepath)
        for line in data:
            links.append(line.decode("utf-8").strip())

    else:
        with open(filepath) as f:
            links = [line.strip() for line in f.readlines()]

    links = links[skip_rows:]
    # print(links)
    mosaic = cog_mosaic(
        links, titiler_endpoint, username, layername, overwrite, verbose, **kwargs
    )
    return mosaic

cog_pixel_value(lon, lat, url, bidx=None, titiler_endpoint='https://titiler.xyz', verbose=True, **kwargs)

Get pixel value from COG.

Parameters:

Name Type Description Default
lon float

Longitude of the pixel.

required
lat float

Latitude of the pixel.

required
url str

HTTP URL to a COG, e.g., 'https://opendata.digitalglobe.com/events/california-fire-2020/pre-event/2018-02-16/pine-gulch-fire20/1030010076004E00.tif'

required
bidx str

Dataset band indexes (e.g bidx=1, bidx=1&bidx=2&bidx=3). Defaults to None.

None
titiler_endpoint str

Titiler endpoint, e.g., "https://titiler.xyz", "planetary-computer", "pc". Defaults to None.

'https://titiler.xyz'
verbose bool

Print status messages. Defaults to True.

True

Returns:

Type Description
list

A dictionary of band info.

Source code in leafmap/common.py
def cog_pixel_value(
    lon,
    lat,
    url,
    bidx=None,
    titiler_endpoint="https://titiler.xyz",
    verbose=True,
    **kwargs,
):
    """Get pixel value from COG.

    Args:
        lon (float): Longitude of the pixel.
        lat (float): Latitude of the pixel.
        url (str): HTTP URL to a COG, e.g., 'https://opendata.digitalglobe.com/events/california-fire-2020/pre-event/2018-02-16/pine-gulch-fire20/1030010076004E00.tif'
        bidx (str, optional): Dataset band indexes (e.g bidx=1, bidx=1&bidx=2&bidx=3). Defaults to None.
        titiler_endpoint (str, optional): Titiler endpoint, e.g., "https://titiler.xyz", "planetary-computer", "pc". Defaults to None.
        verbose (bool, optional): Print status messages. Defaults to True.

    Returns:
        list: A dictionary of band info.
    """

    titiler_endpoint = check_titiler_endpoint(titiler_endpoint)
    kwargs["url"] = url
    if bidx is not None:
        kwargs["bidx"] = bidx

    r = requests.get(f"{titiler_endpoint}/cog/point/{lon},{lat}", params=kwargs).json()
    bands = cog_bands(url, titiler_endpoint)
    # if isinstance(titiler_endpoint, str):
    #     r = requests.get(f"{titiler_endpoint}/cog/point/{lon},{lat}", params=kwargs).json()
    # else:
    #     r = requests.get(
    #         titiler_endpoint.url_for_stac_pixel_value(lon, lat), params=kwargs
    #     ).json()

    if "detail" in r:
        if verbose:
            print(r["detail"])
        return None
    else:
        values = r["values"]
        result = dict(zip(bands, values))
        return result

cog_stats(url, titiler_endpoint='https://titiler.xyz')

Get band statistics of a Cloud Optimized GeoTIFF (COG).

Parameters:

Name Type Description Default
url str

HTTP URL to a COG, e.g., https://opendata.digitalglobe.com/events/mauritius-oil-spill/post-event/2020-08-12/105001001F1B5B00/105001001F1B5B00.tif

required
titiler_endpoint str

Titiler endpoint. Defaults to "https://titiler.xyz".

'https://titiler.xyz'

Returns:

Type Description
list

A dictionary of band statistics.

Source code in leafmap/common.py
def cog_stats(url, titiler_endpoint="https://titiler.xyz"):
    """Get band statistics of a Cloud Optimized GeoTIFF (COG).

    Args:
        url (str): HTTP URL to a COG, e.g., https://opendata.digitalglobe.com/events/mauritius-oil-spill/post-event/2020-08-12/105001001F1B5B00/105001001F1B5B00.tif
        titiler_endpoint (str, optional): Titiler endpoint. Defaults to "https://titiler.xyz".

    Returns:
        list: A dictionary of band statistics.
    """

    r = requests.get(
        f"{titiler_endpoint}/cog/statistics",
        params={
            "url": url,
        },
    ).json()

    return r

cog_tile(url, bands=None, titiler_endpoint='https://titiler.xyz', **kwargs)

Get a tile layer from a Cloud Optimized GeoTIFF (COG). Source code adapted from https://developmentseed.org/titiler/examples/notebooks/Working_with_CloudOptimizedGeoTIFF_simple/

Parameters:

Name Type Description Default
url str

HTTP URL to a COG, e.g., https://opendata.digitalglobe.com/events/mauritius-oil-spill/post-event/2020-08-12/105001001F1B5B00/105001001F1B5B00.tif

required
bands list

List of bands to use. Defaults to None.

None
titiler_endpoint str

Titiler endpoint. Defaults to "https://titiler.xyz".

'https://titiler.xyz'

Returns:

Type Description
tuple

Returns the COG Tile layer URL and bounds.

Source code in leafmap/common.py
def cog_tile(url, bands=None, titiler_endpoint="https://titiler.xyz", **kwargs):
    """Get a tile layer from a Cloud Optimized GeoTIFF (COG).
        Source code adapted from https://developmentseed.org/titiler/examples/notebooks/Working_with_CloudOptimizedGeoTIFF_simple/

    Args:
        url (str): HTTP URL to a COG, e.g., https://opendata.digitalglobe.com/events/mauritius-oil-spill/post-event/2020-08-12/105001001F1B5B00/105001001F1B5B00.tif
        bands (list, optional): List of bands to use. Defaults to None.
        titiler_endpoint (str, optional): Titiler endpoint. Defaults to "https://titiler.xyz".

    Returns:
        tuple: Returns the COG Tile layer URL and bounds.
    """

    kwargs["url"] = url

    band_names = cog_bands(url, titiler_endpoint)

    if isinstance(bands, str):
        bands = [bands]

    if bands is None and "bidx" not in kwargs:
        if len(band_names) >= 3:
            kwargs["bidx"] = [1, 2, 3]
    elif isinstance(bands, list) and "bidx" not in kwargs:
        if all(isinstance(x, int) for x in bands):
            if len(set(bands)) == 1:
                bands = bands[0]
            kwargs["bidx"] = bands
        elif all(isinstance(x, str) for x in bands):
            if len(set(bands)) == 1:
                bands = bands[0]
            kwargs["bidx"] = [band_names.index(x) + 1 for x in bands]
        else:
            raise ValueError("Bands must be a list of integers or strings.")

    if "palette" in kwargs:
        kwargs["colormap_name"] = kwargs["palette"].lower()
        del kwargs["palette"]

    if "rescale" not in kwargs:
        stats = cog_stats(url, titiler_endpoint)
        if "message" not in stats:
            percentile_2 = min([stats[s]["percentile_2"] for s in stats])
            percentile_98 = max([stats[s]["percentile_98"] for s in stats])
            kwargs["rescale"] = f"{percentile_2},{percentile_98}"

    TileMatrixSetId = "WebMercatorQuad"
    if "TileMatrixSetId" in kwargs.keys():
        TileMatrixSetId = kwargs["TileMatrixSetId"]
        kwargs.pop("TileMatrixSetId")

    r = requests.get(
        f"{titiler_endpoint}/cog/{TileMatrixSetId}/tilejson.json", params=kwargs
    ).json()
    return r["tiles"][0]

cog_tile_vmin_vmax(url, bands=None, titiler_endpoint='https://titiler.xyz', percentile=True, **kwargs)

Get a tile layer from a Cloud Optimized GeoTIFF (COG) and return the minimum and maximum values.

Parameters:

Name Type Description Default
url str

HTTP URL to a COG, e.g., https://opendata.digitalglobe.com/events/mauritius-oil-spill/post-event/2020-08-12/105001001F1B5B00/105001001F1B5B00.tif

required
bands list

List of bands to use. Defaults to None.

None
titiler_endpoint str

Titiler endpoint. Defaults to "https://titiler.xyz".

'https://titiler.xyz'
percentile bool

Whether to use percentiles or not. Defaults to True.

True

Returns:

Type Description
tuple

Returns the minimum and maximum values.

Source code in leafmap/common.py
def cog_tile_vmin_vmax(
    url, bands=None, titiler_endpoint="https://titiler.xyz", percentile=True, **kwargs
):
    """Get a tile layer from a Cloud Optimized GeoTIFF (COG) and return the minimum and maximum values.

    Args:
        url (str): HTTP URL to a COG, e.g., https://opendata.digitalglobe.com/events/mauritius-oil-spill/post-event/2020-08-12/105001001F1B5B00/105001001F1B5B00.tif
        bands (list, optional): List of bands to use. Defaults to None.
        titiler_endpoint (str, optional): Titiler endpoint. Defaults to "https://titiler.xyz".
        percentile (bool, optional): Whether to use percentiles or not. Defaults to True.
    Returns:
        tuple: Returns the minimum and maximum values.
    """
    stats = cog_stats(url, titiler_endpoint)

    if isinstance(bands, str):
        bands = [bands]

    if bands is not None:
        stats = {s: stats[s] for s in stats if s in bands}

    if percentile:
        vmin = min([stats[s]["percentile_2"] for s in stats])
        vmax = max([stats[s]["percentile_98"] for s in stats])
    else:
        vmin = min([stats[s]["min"] for s in stats])
        vmax = max([stats[s]["max"] for s in stats])

    return vmin, vmax

cog_validate(source, verbose=False)

Validate Cloud Optimized Geotiff.

Parameters:

Name Type Description Default
source str

A dataset path or URL. Will be opened in "r" mode.

required
verbose bool

Whether to print the output of the validation. Defaults to False.

False

Exceptions:

Type Description
ImportError

If the rio-cogeo package is not installed.

FileNotFoundError

If the provided file could not be found.

Returns:

Type Description
tuple

A tuple containing the validation results (True is src_path is a valid COG, List of validation errors, and a list of validation warnings).

Source code in leafmap/common.py
def cog_validate(source, verbose=False):
    """Validate Cloud Optimized Geotiff.

    Args:
        source (str): A dataset path or URL. Will be opened in "r" mode.
        verbose (bool, optional): Whether to print the output of the validation. Defaults to False.

    Raises:
        ImportError: If the rio-cogeo package is not installed.
        FileNotFoundError: If the provided file could not be found.

    Returns:
        tuple: A tuple containing the validation results (True is src_path is a valid COG, List of validation errors, and a list of validation warnings).
    """
    try:
        from rio_cogeo.cogeo import cog_validate, cog_info
    except ImportError:
        raise ImportError(
            "The rio-cogeo package is not installed. Please install it with `pip install rio-cogeo` or `conda install rio-cogeo -c conda-forge`."
        )

    if not source.startswith("http"):
        source = check_file_path(source)

        if not os.path.exists(source):
            raise FileNotFoundError("The provided input file could not be found.")

    if verbose:
        return cog_info(source)
    else:
        return cog_validate(source)

connect_postgis(database, host='localhost', user=None, password=None, port=5432, use_env_var=False)

Connects to a PostGIS database.

Parameters:

Name Type Description Default
database str

Name of the database

required
host str

Hosting server for the database. Defaults to "localhost".

'localhost'
user str

User name to access the database. Defaults to None.

None
password str

Password to access the database. Defaults to None.

None
port int

Port number to connect to at the server host. Defaults to 5432.

5432
use_env_var bool

Whether to use environment variables. It set to True, user and password are treated as an environment variables with default values user="SQL_USER" and password="SQL_PASSWORD". Defaults to False.

False

Exceptions:

Type Description
ValueError

If user is not specified.

ValueError

If password is not specified.

Returns:

Type Description
[type]

[description]

Source code in leafmap/common.py
def connect_postgis(
    database, host="localhost", user=None, password=None, port=5432, use_env_var=False
):
    """Connects to a PostGIS database.

    Args:
        database (str): Name of the database
        host (str, optional): Hosting server for the database. Defaults to "localhost".
        user (str, optional): User name to access the database. Defaults to None.
        password (str, optional): Password to access the database. Defaults to None.
        port (int, optional): Port number to connect to at the server host. Defaults to 5432.
        use_env_var (bool, optional): Whether to use environment variables. It set to True, user and password are treated as an environment variables with default values user="SQL_USER" and password="SQL_PASSWORD". Defaults to False.

    Raises:
        ValueError: If user is not specified.
        ValueError: If password is not specified.

    Returns:
        [type]: [description]
    """
    check_package(name="geopandas", URL="https://geopandas.org")
    check_package(
        name="sqlalchemy",
        URL="https://docs.sqlalchemy.org/en/14/intro.html#installation",
    )

    from sqlalchemy import create_engine

    if use_env_var:
        if user is not None:
            user = os.getenv(user)
        else:
            user = os.getenv("SQL_USER")

        if password is not None:
            password = os.getenv(password)
        else:
            password = os.getenv("SQL_PASSWORD")

        if user is None:
            raise ValueError("user is not specified.")
        if password is None:
            raise ValueError("password is not specified.")

    connection_string = f"postgresql://{user}:{password}@{host}:{port}/{database}"
    engine = create_engine(connection_string)

    return engine

coords_to_geojson(coords)

Convert a list of bbox coordinates representing [left, bottom, right, top] to geojson FeatureCollection.

Parameters:

Name Type Description Default
coords list

A list of bbox coordinates representing [left, bottom, right, top].

required

Returns:

Type Description
dict

A geojson FeatureCollection.

Source code in leafmap/common.py
def coords_to_geojson(coords):
    """Convert a list of bbox coordinates representing [left, bottom, right, top] to geojson FeatureCollection.

    Args:
        coords (list): A list of bbox coordinates representing [left, bottom, right, top].

    Returns:
        dict: A geojson FeatureCollection.
    """

    features = []
    for bbox in coords:
        features.append(bbox_to_geojson(bbox))
    return {"type": "FeatureCollection", "features": features}

create_code_cell(code='', where='below')

Creates a code cell in the IPython Notebook.

Parameters:

Name Type Description Default
code str

Code to fill the new code cell with. Defaults to ''.

''
where str

Where to add the new code cell. It can be one of the following: above, below, at_bottom. Defaults to 'below'.

'below'
Source code in leafmap/common.py
def create_code_cell(code="", where="below"):
    """Creates a code cell in the IPython Notebook.

    Args:
        code (str, optional): Code to fill the new code cell with. Defaults to ''.
        where (str, optional): Where to add the new code cell. It can be one of the following: above, below, at_bottom. Defaults to 'below'.
    """

    import base64
    from IPython.display import Javascript, display

    encoded_code = (base64.b64encode(str.encode(code))).decode()
    display(
        Javascript(
            """
        var code = IPython.notebook.insert_cell_{0}('code');
        code.set_text(atob("{1}"));
    """.format(
                where, encoded_code
            )
        )
    )

Downloads a file from voila. Adopted from https://github.com/voila-dashboards/voila/issues/578

Parameters:

Name Type Description Default
filename str

The file path to the file to download

required
title str

str. Defaults to "Click here to download: ".

'Click here to download: '

Returns:

Type Description
str

HTML download URL.

Source code in leafmap/common.py
def create_download_link(filename, title="Click here to download: "):
    """Downloads a file from voila. Adopted from https://github.com/voila-dashboards/voila/issues/578

    Args:
        filename (str): The file path to the file to download
        title (str, optional): str. Defaults to "Click here to download: ".

    Returns:
        str: HTML download URL.
    """
    import base64
    from IPython.display import HTML

    data = open(filename, "rb").read()
    b64 = base64.b64encode(data)
    payload = b64.decode()
    basename = os.path.basename(filename)
    html = '<a download="{filename}" href="data:text/csv;base64,{payload}" style="color:#0000FF;" target="_blank">{title}</a>'
    html = html.format(payload=payload, title=title + f" {basename}", filename=basename)
    return HTML(html)

create_legend(legend_title='Legend', legend_dict=None, legend_keys=None, legend_colors=None, builtin_legend=None, **kwargs)

Create a custom legend.

Parameters:

Name Type Description Default
legend_title str

Title of the legend. Defaults to 'Legend'.

'Legend'
legend_dict dict

A dictionary containing legend items as keys and color as values. If provided, legend_keys and legend_colors will be ignored. Defaults to None.

None
legend_keys list

A list of legend keys. Defaults to None.

None
legend_colors list

A list of legend colors. Defaults to None.

None
builtin_legend str

Name of the builtin legend to add to the map. Defaults to None.

None
Source code in leafmap/common.py
def create_legend(
    legend_title="Legend",
    legend_dict=None,
    legend_keys=None,
    legend_colors=None,
    builtin_legend=None,
    **kwargs,
):
    """Create a custom legend.

    Args:
        legend_title (str, optional): Title of the legend. Defaults to 'Legend'.
        legend_dict (dict, optional): A dictionary containing legend items as keys and color as values. If provided, legend_keys and legend_colors will be ignored. Defaults to None.
        legend_keys (list, optional): A list of legend keys. Defaults to None.
        legend_colors (list, optional): A list of legend colors. Defaults to None.
        builtin_legend (str, optional): Name of the builtin legend to add to the map. Defaults to None.

    """
    import pkg_resources
    from .legends import builtin_legends

    pkg_dir = os.path.dirname(pkg_resources.resource_filename("leafmap", "leafmap.py"))
    legend_template = os.path.join(pkg_dir, "data/template/legend.html")

    # if "min_width" not in kwargs.keys():
    #     min_width = None
    # if "max_width" not in kwargs.keys():
    #     max_width = None
    # else:
    #     max_width = kwargs["max_width"]
    # if "min_height" not in kwargs.keys():
    #     min_height = None
    # else:
    #     min_height = kwargs["min_height"]
    # if "max_height" not in kwargs.keys():
    #     max_height = None
    # else:
    #     max_height = kwargs["max_height"]
    # if "height" not in kwargs.keys():
    #     height = None
    # else:
    #     height = kwargs["height"]
    # if "width" not in kwargs.keys():
    #     width = None
    # else:
    #     width = kwargs["width"]

    # if width is None:
    #     max_width = "300px"
    # if height is None:
    #     max_height = "400px"

    if not os.path.exists(legend_template):
        print("The legend template does not exist.")
        return

    if legend_keys is not None:
        if not isinstance(legend_keys, list):
            print("The legend keys must be a list.")
            return
    else:
        legend_keys = ["One", "Two", "Three", "Four", "etc"]

    if legend_colors is not None:
        if not isinstance(legend_colors, list):
            print("The legend colors must be a list.")
            return
        elif all(isinstance(item, tuple) for item in legend_colors):
            try:
                legend_colors = [rgb_to_hex(x) for x in legend_colors]
            except Exception as e:
                print(e)
        elif all((item.startswith("#") and len(item) == 7) for item in legend_colors):
            pass
        elif all((len(item) == 6) for item in legend_colors):
            pass
        else:
            print("The legend colors must be a list of tuples.")
            return
    else:
        legend_colors = [
            "#8DD3C7",
            "#FFFFB3",
            "#BEBADA",
            "#FB8072",
            "#80B1D3",
        ]

    if len(legend_keys) != len(legend_colors):
        print("The legend keys and values must be the same length.")
        return

    allowed_builtin_legends = builtin_legends.keys()
    if builtin_legend is not None:
        if builtin_legend not in allowed_builtin_legends:
            print(
                "The builtin legend must be one of the following: {}".format(
                    ", ".join(allowed_builtin_legends)
                )
            )
            return
        else:
            legend_dict = builtin_legends[builtin_legend]
            legend_keys = list(legend_dict.keys())
            legend_colors = list(legend_dict.values())

    if legend_dict is not None:
        if not isinstance(legend_dict, dict):
            print("The legend dict must be a dictionary.")
            return
        else:
            legend_keys = list(legend_dict.keys())
            legend_colors = list(legend_dict.values())
            if all(isinstance(item, tuple) for item in legend_colors):
                try:
                    legend_colors = [rgb_to_hex(x) for x in legend_colors]
                except Exception as e:
                    print(e)

    header = []
    content = []
    footer = []

    with open(legend_template) as f:
        lines = f.readlines()
        lines[3] = lines[3].replace("Legend", legend_title)
        header = lines[:6]
        footer = lines[11:]

    for index, key in enumerate(legend_keys):
        color = legend_colors[index]
        if not color.startswith("#"):
            color = "#" + color
        item = "      <li><span style='background:{};'></span>{}</li>\n".format(
            color, key
        )
        content.append(item)

    legend_html = header + content + footer
    legend_text = "".join(legend_html)
    return legend_text

csv_points_to_shp(in_csv, out_shp, latitude='latitude', longitude='longitude')

Converts a csv file containing points (latitude, longitude) into a shapefile.

Parameters:

Name Type Description Default
in_csv str

File path or HTTP URL to the input csv file. For example, https://raw.githubusercontent.com/giswqs/data/main/world/world_cities.csv

required
out_shp str

File path to the output shapefile.

required
latitude str

Column name for the latitude column. Defaults to 'latitude'.

'latitude'
longitude str

Column name for the longitude column. Defaults to 'longitude'.

'longitude'
Source code in leafmap/common.py
def csv_points_to_shp(in_csv, out_shp, latitude="latitude", longitude="longitude"):
    """Converts a csv file containing points (latitude, longitude) into a shapefile.

    Args:
        in_csv (str): File path or HTTP URL to the input csv file. For example, https://raw.githubusercontent.com/giswqs/data/main/world/world_cities.csv
        out_shp (str): File path to the output shapefile.
        latitude (str, optional): Column name for the latitude column. Defaults to 'latitude'.
        longitude (str, optional): Column name for the longitude column. Defaults to 'longitude'.

    """

    if in_csv.startswith("http") and in_csv.endswith(".csv"):
        out_dir = os.path.join(os.path.expanduser("~"), "Downloads")
        out_name = os.path.basename(in_csv)

        if not os.path.exists(out_dir):
            os.makedirs(out_dir)
        download_from_url(in_csv, out_dir=out_dir)
        in_csv = os.path.join(out_dir, out_name)

    wbt = whitebox.WhiteboxTools()
    in_csv = os.path.abspath(in_csv)
    out_shp = os.path.abspath(out_shp)

    if not os.path.exists(in_csv):
        raise Exception("The provided csv file does not exist.")

    with open(in_csv, encoding="utf-8") as csv_file:
        reader = csv.DictReader(csv_file)
        fields = reader.fieldnames
        xfield = fields.index(longitude)
        yfield = fields.index(latitude)

    wbt.csv_points_to_vector(in_csv, out_shp, xfield=xfield, yfield=yfield, epsg=4326)

csv_to_gdf(in_csv, latitude='latitude', longitude='longitude', encoding='utf-8')

Creates points for a CSV file and converts them to a GeoDataFrame.

Parameters:

Name Type Description Default
in_csv str

The file path to the input CSV file.

required
latitude str

The name of the column containing latitude coordinates. Defaults to "latitude".

'latitude'
longitude str

The name of the column containing longitude coordinates. Defaults to "longitude".

'longitude'
encoding str

The encoding of characters. Defaults to "utf-8".

'utf-8'

Returns:

Type Description
object

GeoDataFrame.

Source code in leafmap/common.py
def csv_to_gdf(in_csv, latitude="latitude", longitude="longitude", encoding="utf-8"):
    """Creates points for a CSV file and converts them to a GeoDataFrame.

    Args:
        in_csv (str): The file path to the input CSV file.
        latitude (str, optional): The name of the column containing latitude coordinates. Defaults to "latitude".
        longitude (str, optional): The name of the column containing longitude coordinates. Defaults to "longitude".
        encoding (str, optional): The encoding of characters. Defaults to "utf-8".

    Returns:
        object: GeoDataFrame.
    """

    check_package(name="geopandas", URL="https://geopandas.org")

    import geopandas as gpd

    out_dir = os.getcwd()

    out_geojson = os.path.join(out_dir, random_string() + ".geojson")
    csv_to_geojson(in_csv, out_geojson, latitude, longitude, encoding)

    gdf = gpd.read_file(out_geojson)
    os.remove(out_geojson)
    return gdf

csv_to_geojson(in_csv, out_geojson=None, latitude='latitude', longitude='longitude', encoding='utf-8')

Creates points for a CSV file and exports data as a GeoJSON.

Parameters:

Name Type Description Default
in_csv str

The file path to the input CSV file.

required
out_geojson str

The file path to the exported GeoJSON. Default to None.

None
latitude str

The name of the column containing latitude coordinates. Defaults to "latitude".

'latitude'
longitude str

The name of the column containing longitude coordinates. Defaults to "longitude".

'longitude'
encoding str

The encoding of characters. Defaults to "utf-8".

'utf-8'
Source code in leafmap/common.py
def csv_to_geojson(
    in_csv,
    out_geojson=None,
    latitude="latitude",
    longitude="longitude",
    encoding="utf-8",
):
    """Creates points for a CSV file and exports data as a GeoJSON.

    Args:
        in_csv (str): The file path to the input CSV file.
        out_geojson (str): The file path to the exported GeoJSON. Default to None.
        latitude (str, optional): The name of the column containing latitude coordinates. Defaults to "latitude".
        longitude (str, optional): The name of the column containing longitude coordinates. Defaults to "longitude".
        encoding (str, optional): The encoding of characters. Defaults to "utf-8".

    """

    import json
    import pandas as pd

    if out_geojson is not None:
        out_dir = os.path.dirname(os.path.abspath(out_geojson))
        if not os.path.exists(out_dir):
            os.makedirs(out_dir)

    df = pd.read_csv(in_csv)
    geojson = pandas_to_geojson(
        df, latitude=latitude, longitude=longitude, encoding=encoding
    )

    if out_geojson is None:
        return geojson
    else:
        with open(out_geojson, "w", encoding=encoding) as f:
            f.write(json.dumps(geojson))

csv_to_pandas(in_csv, **kwargs)

Converts a CSV file to pandas dataframe.

Parameters:

Name Type Description Default
in_csv str

File path to the input CSV.

required

Returns:

Type Description
pd.DataFrame

pandas DataFrame

Source code in leafmap/common.py
def csv_to_pandas(in_csv, **kwargs):
    """Converts a CSV file to pandas dataframe.

    Args:
        in_csv (str): File path to the input CSV.

    Returns:
        pd.DataFrame: pandas DataFrame
    """
    import pandas as pd

    try:
        return pd.read_csv(in_csv, **kwargs)
    except Exception as e:
        raise Exception(e)

csv_to_shp(in_csv, out_shp, latitude='latitude', longitude='longitude')

Converts a csv file with latlon info to a point shapefile.

Parameters:

Name Type Description Default
in_csv str

The input csv file containing longitude and latitude columns.

required
out_shp str

The file path to the output shapefile.

required
latitude str

The column name of the latitude column. Defaults to 'latitude'.

'latitude'
longitude str

The column name of the longitude column. Defaults to 'longitude'.

'longitude'
Source code in leafmap/common.py
def csv_to_shp(in_csv, out_shp, latitude="latitude", longitude="longitude"):
    """Converts a csv file with latlon info to a point shapefile.

    Args:
        in_csv (str): The input csv file containing longitude and latitude columns.
        out_shp (str): The file path to the output shapefile.
        latitude (str, optional): The column name of the latitude column. Defaults to 'latitude'.
        longitude (str, optional): The column name of the longitude column. Defaults to 'longitude'.
    """
    import shapefile as shp

    if in_csv.startswith("http") and in_csv.endswith(".csv"):
        out_dir = os.path.join(os.path.expanduser("~"), "Downloads")
        out_name = os.path.basename(in_csv)

        if not os.path.exists(out_dir):
            os.makedirs(out_dir)
        download_from_url(in_csv, out_dir=out_dir)
        in_csv = os.path.join(out_dir, out_name)

    out_dir = os.path.dirname(out_shp)
    if not os.path.exists(out_dir):
        os.makedirs(out_dir)

    try:
        points = shp.Writer(out_shp, shapeType=shp.POINT)
        with open(in_csv, encoding="utf-8") as csvfile:
            csvreader = csv.DictReader(csvfile)
            header = csvreader.fieldnames
            [points.field(field) for field in header]
            for row in csvreader:
                points.point((float(row[longitude])), (float(row[latitude])))
                points.record(*tuple([row[f] for f in header]))

        out_prj = out_shp.replace(".shp", ".prj")
        with open(out_prj, "w") as f:
            prj_str = 'GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137,298.257223563]],PRIMEM["Greenwich",0],UNIT["Degree",0.0174532925199433]] '
            f.write(prj_str)

    except Exception as e:
        raise Exception(e)

delete_shp(in_shp, verbose=False)

Deletes a shapefile.

Parameters:

Name Type Description Default
in_shp str

The input shapefile to delete.

required
verbose bool

Whether to print out descriptive text. Defaults to True.

False
Source code in leafmap/common.py
def delete_shp(in_shp, verbose=False):
    """Deletes a shapefile.

    Args:
        in_shp (str): The input shapefile to delete.
        verbose (bool, optional): Whether to print out descriptive text. Defaults to True.
    """
    from pathlib import Path

    in_shp = os.path.abspath(in_shp)
    in_dir = os.path.dirname(in_shp)
    basename = os.path.basename(in_shp).replace(".shp", "")

    files = Path(in_dir).rglob(basename + ".*")

    for file in files:
        filepath = os.path.join(in_dir, str(file))
        os.remove(filepath)
        if verbose:
            print(f"Deleted {filepath}")

dict_to_json(data, file_path, indent=4)

Writes a dictionary to a JSON file.

Parameters:

Name Type Description Default
data dict

A dictionary.

required
file_path str

The path to the JSON file.

required
indent int

The indentation of the JSON file. Defaults to 4.

4

Exceptions:

Type Description
TypeError

If the input data is not a dictionary.

Source code in leafmap/common.py
def dict_to_json(data, file_path, indent=4):
    """Writes a dictionary to a JSON file.

    Args:
        data (dict): A dictionary.
        file_path (str): The path to the JSON file.
        indent (int, optional): The indentation of the JSON file. Defaults to 4.

    Raises:
        TypeError: If the input data is not a dictionary.
    """
    import json

    file_path = check_file_path(file_path)

    if isinstance(data, dict):
        with open(file_path, "w") as f:
            json.dump(data, f, indent=indent)
    else:
        raise TypeError("The provided data must be a dictionary.")

display_html(src, width=950, height=600)

Display an HTML file in a Jupyter Notebook.

Args src (str): File path to HTML file. width (int, optional): Width of the map. Defaults to 950. height (int, optional): Height of the map. Defaults to 600.

Source code in leafmap/common.py
def display_html(src, width=950, height=600):
    """Display an HTML file in a Jupyter Notebook.

    Args
        src (str): File path to HTML file.
        width (int, optional): Width of the map. Defaults to 950.
        height (int, optional): Height of the map. Defaults to 600.
    """
    if not os.path.isfile(src):
        raise ValueError(f"{src} is not a valid file path.")
    display(IFrame(src=src, width=width, height=height))

download_file(url=None, output=None, quiet=False, proxy=None, speed=None, use_cookies=True, verify=True, id=None, fuzzy=False, resume=False, unzip=True)

Download a file from URL, including Google Drive shared URL.

Parameters:

Name Type Description Default
url str

Google Drive URL is also supported. Defaults to None.

None
output str

Output filename. Default is basename of URL.

None
quiet bool

Suppress terminal output. Default is False.

False
proxy str

Proxy. Defaults to None.

None
speed float

Download byte size per second (e.g., 256KB/s = 256 * 1024). Defaults to None.

None
use_cookies bool

Flag to use cookies. Defaults to True.

True
verify bool | str

Either a bool, in which case it controls whether the server's TLS certificate is verified, or a string, in which case it must be a path to a CA bundle to use. Default is True.. Defaults to True.

True
id str

Google Drive's file ID. Defaults to None.

None
fuzzy bool

Fuzzy extraction of Google Drive's file Id. Defaults to False.

False
resume bool

Resume the download from existing tmp file if possible. Defaults to False.

False
unzip bool

Unzip the file. Defaults to True.

True

Returns:

Type Description
str

The output file path.

Source code in leafmap/common.py
def download_file(
    url=None,
    output=None,
    quiet=False,
    proxy=None,
    speed=None,
    use_cookies=True,
    verify=True,
    id=None,
    fuzzy=False,
    resume=False,
    unzip=True,
):
    """Download a file from URL, including Google Drive shared URL.

    Args:
        url (str, optional): Google Drive URL is also supported. Defaults to None.
        output (str, optional): Output filename. Default is basename of URL.
        quiet (bool, optional): Suppress terminal output. Default is False.
        proxy (str, optional): Proxy. Defaults to None.
        speed (float, optional): Download byte size per second (e.g., 256KB/s = 256 * 1024). Defaults to None.
        use_cookies (bool, optional): Flag to use cookies. Defaults to True.
        verify (bool | str, optional): Either a bool, in which case it controls whether the server's TLS certificate is verified, or a string, in which case it must be a path to a CA bundle to use. Default is True.. Defaults to True.
        id (str, optional): Google Drive's file ID. Defaults to None.
        fuzzy (bool, optional): Fuzzy extraction of Google Drive's file Id. Defaults to False.
        resume (bool, optional): Resume the download from existing tmp file if possible. Defaults to False.
        unzip (bool, optional): Unzip the file. Defaults to True.

    Returns:
        str: The output file path.
    """

    import gdown

    if "https://drive.google.com/file/d/" in url:
        fuzzy = True

    output = gdown.download(
        url, output, quiet, proxy, speed, use_cookies, verify, id, fuzzy, resume
    )

    if unzip and output.endswith(".zip"):

        with zipfile.ZipFile(output, "r") as zip_ref:
            if not quiet:
                print("Extracting files...")
            zip_ref.extractall(os.path.dirname(output))

    return os.path.abspath(output)

download_folder(url=None, id=None, output=None, quiet=False, proxy=None, speed=None, use_cookies=True, remaining_ok=False)

Downloads the entire folder from URL.

Parameters:

Name Type Description Default
url str

URL of the Google Drive folder. Must be of the format 'https://drive.google.com/drive/folders/{url}'. Defaults to None.

None
id str

Google Drive's folder ID. Defaults to None.

None
output str

String containing the path of the output folder. Defaults to current working directory.

None
quiet bool

Suppress terminal output. Defaults to False.

False
proxy str

Proxy. Defaults to None.

None
speed float

Download byte size per second (e.g., 256KB/s = 256 * 1024). Defaults to None.

None
use_cookies bool

Flag to use cookies. Defaults to True.

True
resume bool

Resume the download from existing tmp file if possible. Defaults to False.

required

Returns:

Type Description
list

List of files downloaded, or None if failed.

Source code in leafmap/common.py
def download_folder(
    url=None,
    id=None,
    output=None,
    quiet=False,
    proxy=None,
    speed=None,
    use_cookies=True,
    remaining_ok=False,
):
    """Downloads the entire folder from URL.

    Args:
        url (str, optional): URL of the Google Drive folder. Must be of the format 'https://drive.google.com/drive/folders/{url}'. Defaults to None.
        id (str, optional): Google Drive's folder ID. Defaults to None.
        output (str, optional):  String containing the path of the output folder. Defaults to current working directory.
        quiet (bool, optional): Suppress terminal output. Defaults to False.
        proxy (str, optional): Proxy. Defaults to None.
        speed (float, optional): Download byte size per second (e.g., 256KB/s = 256 * 1024). Defaults to None.
        use_cookies (bool, optional): Flag to use cookies. Defaults to True.
        resume (bool, optional): Resume the download from existing tmp file if possible. Defaults to False.

    Returns:
        list: List of files downloaded, or None if failed.
    """
    import gdown

    files = gdown.download_folder(
        url, id, output, quiet, proxy, speed, use_cookies, remaining_ok
    )
    return files

download_from_gdrive(gfile_url, file_name, out_dir='.', unzip=True, verbose=True)

Download a file shared via Google Drive (e.g., https://drive.google.com/file/d/18SUo_HcDGltuWYZs1s7PpOmOq_FvFn04/view?usp=sharing)

Parameters:

Name Type Description Default
gfile_url str

The Google Drive shared file URL

required
file_name str

The output file name to use.

required
out_dir str

The output directory. Defaults to '.'.

'.'
unzip bool

Whether to unzip the output file if it is a zip file. Defaults to True.

True
verbose bool

Whether to display or not the output of the function

True
Source code in leafmap/common.py
def download_from_gdrive(gfile_url, file_name, out_dir=".", unzip=True, verbose=True):
    """Download a file shared via Google Drive
       (e.g., https://drive.google.com/file/d/18SUo_HcDGltuWYZs1s7PpOmOq_FvFn04/view?usp=sharing)

    Args:
        gfile_url (str): The Google Drive shared file URL
        file_name (str): The output file name to use.
        out_dir (str, optional): The output directory. Defaults to '.'.
        unzip (bool, optional): Whether to unzip the output file if it is a zip file. Defaults to True.
        verbose (bool, optional): Whether to display or not the output of the function
    """
    try:
        from google_drive_downloader import GoogleDriveDownloader as gdd
    except ImportError:
        raise ImportError(
            'Please install googledrivedownloader using "pip install googledrivedownloader"'
        )

    file_id = gfile_url.split("/")[5]
    if verbose:
        print("Google Drive file id: {}".format(file_id))

    out_dir = check_dir(out_dir)
    dest_path = os.path.join(out_dir, file_name)
    gdd.download_file_from_google_drive(file_id, dest_path, True, unzip)

download_from_url(url, out_file_name=None, out_dir='.', unzip=True, verbose=True)

Download a file from a URL (e.g., https://github.com/giswqs/whitebox-python/raw/master/examples/testdata.zip)

Parameters:

Name Type Description Default
url str

The HTTP URL to download.

required
out_file_name str

The output file name to use. Defaults to None.

None
out_dir str

The output directory to use. Defaults to '.'.

'.'
unzip bool

Whether to unzip the downloaded file if it is a zip file. Defaults to True.

True
verbose bool

Whether to display or not the output of the function

True
Source code in leafmap/common.py
def download_from_url(url, out_file_name=None, out_dir=".", unzip=True, verbose=True):
    """Download a file from a URL (e.g., https://github.com/giswqs/whitebox-python/raw/master/examples/testdata.zip)

    Args:
        url (str): The HTTP URL to download.
        out_file_name (str, optional): The output file name to use. Defaults to None.
        out_dir (str, optional): The output directory to use. Defaults to '.'.
        unzip (bool, optional): Whether to unzip the downloaded file if it is a zip file. Defaults to True.
        verbose (bool, optional): Whether to display or not the output of the function
    """
    in_file_name = os.path.basename(url)
    out_dir = check_dir(out_dir)

    if out_file_name is None:
        out_file_name = in_file_name
    out_file_path = os.path.join(out_dir, out_file_name)

    if verbose:
        print("Downloading {} ...".format(url))

    try:
        urllib.request.urlretrieve(url, out_file_path)
    except Exception:
        raise Exception("The URL is invalid. Please double check the URL.")

    final_path = out_file_path

    if unzip:
        # if it is a zip file
        if ".zip" in out_file_name:
            if verbose:
                print("Unzipping {} ...".format(out_file_name))
            with zipfile.ZipFile(out_file_path, "r") as zip_ref:
                zip_ref.extractall(out_dir)
            final_path = os.path.join(
                os.path.abspath(out_dir), out_file_name.replace(".zip", "")
            )

        # if it is a tar file
        if ".tar" in out_file_name:
            if verbose:
                print("Unzipping {} ...".format(out_file_name))
            with tarfile.open(out_file_path, "r") as tar_ref:
                tar_ref.extractall(out_dir)
            final_path = os.path.join(
                os.path.abspath(out_dir), out_file_name.replace(".tart", "")
            )

    if verbose:
        print("Data downloaded to: {}".format(final_path))

edit_download_html(htmlWidget, filename, title='Click here to download: ')

Downloads a file from voila. Adopted from https://github.com/voila-dashboards/voila/issues/578#issuecomment-617668058

Parameters:

Name Type Description Default
htmlWidget object

The HTML widget to display the URL.

required
filename str

File path to download.

required
title str

Download description. Defaults to "Click here to download: ".

'Click here to download: '
Source code in leafmap/common.py
def edit_download_html(htmlWidget, filename, title="Click here to download: "):
    """Downloads a file from voila. Adopted from https://github.com/voila-dashboards/voila/issues/578#issuecomment-617668058

    Args:
        htmlWidget (object): The HTML widget to display the URL.
        filename (str): File path to download.
        title (str, optional): Download description. Defaults to "Click here to download: ".
    """

    # from IPython.display import HTML
    # import ipywidgets as widgets
    import base64

    # Change widget html temporarily to a font-awesome spinner
    htmlWidget.value = '<i class="fa fa-spinner fa-spin fa-2x fa-fw"></i><span class="sr-only">Loading...</span>'

    # Process raw data
    data = open(filename, "rb").read()
    b64 = base64.b64encode(data)
    payload = b64.decode()

    basename = os.path.basename(filename)

    # Create and assign html to widget
    html = '<a download="{filename}" href="data:text/csv;base64,{payload}" target="_blank">{title}</a>'
    htmlWidget.value = html.format(
        payload=payload, title=title + basename, filename=basename
    )

explode(coords)

Explode a GeoJSON geometry's coordinates object and yield coordinate tuples. As long as the input is conforming, the type of the geometry doesn't matter. From Fiona 1.4.8

Parameters:

Name Type Description Default
coords list

A list of coordinates.

required

Yields:

Type Description
[type]

[description]

Source code in leafmap/common.py
def explode(coords):
    """Explode a GeoJSON geometry's coordinates object and yield
    coordinate tuples. As long as the input is conforming, the type of
    the geometry doesn't matter.  From Fiona 1.4.8

    Args:
        coords (list): A list of coordinates.

    Yields:
        [type]: [description]
    """

    for e in coords:
        if isinstance(e, (float, int)):
            yield coords
            break
        else:
            for f in explode(e):
                yield f

gdf_bounds(gdf, return_geom=False)

Returns the bounding box of a GeoDataFrame.

Parameters:

Name Type Description Default
gdf gpd.GeoDataFrame

A GeoDataFrame.

required
return_geom bool

Whether to return the bounding box as a GeoDataFrame. Defaults to False.

False

Returns:

Type Description
list | gpd.GeoDataFrame

A bounding box in the form of a list (minx, miny, maxx, maxy) or GeoDataFrame.

Source code in leafmap/common.py
def gdf_bounds(gdf, return_geom=False):
    """Returns the bounding box of a GeoDataFrame.

    Args:
        gdf (gpd.GeoDataFrame): A GeoDataFrame.
        return_geom (bool, optional): Whether to return the bounding box as a GeoDataFrame. Defaults to False.

    Returns:
        list | gpd.GeoDataFrame: A bounding box in the form of a list (minx, miny, maxx, maxy) or GeoDataFrame.
    """
    bounds = gdf.total_bounds
    if return_geom:
        return bbox_to_gdf(bbox=bounds)
    else:
        return bounds

gdf_centroid(gdf, return_geom=False)

Returns the centroid of a GeoDataFrame.

Parameters:

Name Type Description Default
gdf gpd.GeoDataFrame

A GeoDataFrame.

required
return_geom bool

Whether to return the bounding box as a GeoDataFrame. Defaults to False.

False

Returns:

Type Description
list | gpd.GeoDataFrame

A bounding box in the form of a list (lon, lat) or GeoDataFrame.

Source code in leafmap/common.py
def gdf_centroid(gdf, return_geom=False):
    """Returns the centroid of a GeoDataFrame.

    Args:
        gdf (gpd.GeoDataFrame): A GeoDataFrame.
        return_geom (bool, optional): Whether to return the bounding box as a GeoDataFrame. Defaults to False.

    Returns:
        list | gpd.GeoDataFrame: A bounding box in the form of a list (lon, lat) or GeoDataFrame.
    """
    import warnings

    warnings.filterwarnings("ignore")

    centroid = gdf_bounds(gdf, return_geom=True).centroid
    if return_geom:
        return centroid
    else:
        return centroid.x[0], centroid.y[0]

gdf_geom_type(gdf, first_only=True)

Returns the geometry type of a GeoDataFrame.

Parameters:

Name Type Description Default
gdf gpd.GeoDataFrame

A GeoDataFrame.

required
first_only bool

Whether to return the geometry type of the first feature in the GeoDataFrame. Defaults to True.

True

Returns:

Type Description
str

The geometry type of the GeoDataFrame.

Source code in leafmap/common.py
def gdf_geom_type(gdf, first_only=True):
    """Returns the geometry type of a GeoDataFrame.

    Args:
        gdf (gpd.GeoDataFrame): A GeoDataFrame.
        first_only (bool, optional): Whether to return the geometry type of the first feature in the GeoDataFrame. Defaults to True.

    Returns:
        str: The geometry type of the GeoDataFrame.
    """
    import geopandas as gpd

    if first_only:
        return gdf.geometry.type[0]
    else:
        return gdf.geometry.type

gdf_to_df(gdf, drop_geom=True)

Converts a GeoDataFrame to a pandas DataFrame.

Parameters:

Name Type Description Default
gdf gpd.GeoDataFrame

A GeoDataFrame.

required
drop_geom bool

Whether to drop the geometry column. Defaults to True.

True

Returns:

Type Description
pd.DataFrame

A pandas DataFrame containing the GeoDataFrame.

Source code in leafmap/common.py
def gdf_to_df(gdf, drop_geom=True):
    """Converts a GeoDataFrame to a pandas DataFrame.

    Args:
        gdf (gpd.GeoDataFrame): A GeoDataFrame.
        drop_geom (bool, optional): Whether to drop the geometry column. Defaults to True.

    Returns:
        pd.DataFrame: A pandas DataFrame containing the GeoDataFrame.
    """
    import pandas as pd

    if drop_geom:
        df = pd.DataFrame(gdf.drop(columns=["geometry"]))
    else:
        df = pd.DataFrame(gdf)

    return df

gdf_to_geojson(gdf, out_geojson=None, epsg=None, tuple_to_list=False, encoding='utf-8')

Converts a GeoDataFame to GeoJSON.

Parameters:

Name Type Description Default
gdf GeoDataFrame

A GeoPandas GeoDataFrame.

required
out_geojson str

File path to he output GeoJSON. Defaults to None.

None
epsg str

An EPSG string, e.g., "4326". Defaults to None.

None
tuple_to_list bool

Whether to convert tuples to lists. Defaults to False.

False
encoding str

The encoding to use for the GeoJSON. Defaults to "utf-8".

'utf-8'

Exceptions:

Type Description
TypeError

When the output file extension is incorrect.

Exception

When the conversion fails.

Returns:

Type Description
dict

When the out_json is None returns a dict.

Source code in leafmap/common.py
def gdf_to_geojson(
    gdf, out_geojson=None, epsg=None, tuple_to_list=False, encoding="utf-8"
):
    """Converts a GeoDataFame to GeoJSON.

    Args:
        gdf (GeoDataFrame): A GeoPandas GeoDataFrame.
        out_geojson (str, optional): File path to he output GeoJSON. Defaults to None.
        epsg (str, optional): An EPSG string, e.g., "4326". Defaults to None.
        tuple_to_list (bool, optional): Whether to convert tuples to lists. Defaults to False.
        encoding (str, optional): The encoding to use for the GeoJSON. Defaults to "utf-8".

    Raises:
        TypeError: When the output file extension is incorrect.
        Exception: When the conversion fails.

    Returns:
        dict: When the out_json is None returns a dict.
    """
    check_package(name="geopandas", URL="https://geopandas.org")

    def listit(t):
        return list(map(listit, t)) if isinstance(t, (list, tuple)) else t

    try:
        if epsg is not None:
            if gdf.crs is not None and gdf.crs.to_epsg() != epsg:
                gdf = gdf.to_crs(epsg=epsg)
        geojson = gdf.__geo_interface__

        if tuple_to_list:
            for feature in geojson["features"]:
                feature["geometry"]["coordinates"] = listit(
                    feature["geometry"]["coordinates"]
                )

        if out_geojson is None:
            return geojson
        else:
            ext = os.path.splitext(out_geojson)[1]
            if ext.lower() not in [".json", ".geojson"]:
                raise TypeError(
                    "The output file extension must be either .json or .geojson"
                )
            out_dir = os.path.dirname(out_geojson)
            if not os.path.exists(out_dir):
                os.makedirs(out_dir)

            gdf.to_file(out_geojson, driver="GeoJSON", encoding=encoding)
    except Exception as e:
        raise Exception(e)

geojson_to_df(in_geojson, encoding='utf-8', drop_geometry=True)

Converts a GeoJSON object to a pandas DataFrame.

Parameters:

Name Type Description Default
in_geojson str | dict

The input GeoJSON file or dict.

required
encoding str

The encoding of the GeoJSON object. Defaults to "utf-8".

'utf-8'
drop_geometry bool

Whether to drop the geometry column. Defaults to True.

True

Exceptions:

Type Description
FileNotFoundError

If the input GeoJSON file could not be found.

Returns:

Type Description
pd.DataFrame

A pandas DataFrame containing the GeoJSON object.

Source code in leafmap/common.py
def geojson_to_df(in_geojson, encoding="utf-8", drop_geometry=True):
    """Converts a GeoJSON object to a pandas DataFrame.

    Args:
        in_geojson (str | dict): The input GeoJSON file or dict.
        encoding (str, optional): The encoding of the GeoJSON object. Defaults to "utf-8".
        drop_geometry (bool, optional): Whether to drop the geometry column. Defaults to True.

    Raises:
        FileNotFoundError: If the input GeoJSON file could not be found.

    Returns:
        pd.DataFrame: A pandas DataFrame containing the GeoJSON object.
    """

    import json
    import pandas as pd
    from urllib.request import urlopen

    if isinstance(in_geojson, str):

        if in_geojson.startswith("http"):
            with urlopen(in_geojson) as f:
                data = json.load(f)
        else:
            in_geojson = os.path.abspath(in_geojson)
            if not os.path.exists(in_geojson):
                raise FileNotFoundError("The provided GeoJSON file could not be found.")

            with open(in_geojson, encoding=encoding) as f:
                data = json.load(f)

    elif isinstance(in_geojson, dict):
        data = in_geojson

    df = pd.json_normalize(data["features"])
    df.columns = [col.replace("properties.", "") for col in df.columns]
    if drop_geometry:
        df = df[df.columns.drop(list(df.filter(regex="geometry")))]
    return df

geojson_to_gpkg(in_geojson, out_gpkg, **kwargs)

Converts a GeoJSON object to GeoPackage.

Parameters:

Name Type Description Default
in_geojson str | dict

The input GeoJSON file or dict.

required
out_gpkg str

The output GeoPackage path.

required
Source code in leafmap/common.py
def geojson_to_gpkg(in_geojson, out_gpkg, **kwargs):
    """Converts a GeoJSON object to GeoPackage.

    Args:
        in_geojson (str | dict): The input GeoJSON file or dict.
        out_gpkg (str): The output GeoPackage path.
    """
    import geopandas as gpd
    import json

    ext = os.path.splitext(out_gpkg)[1]
    if ext.lower() != ".gpkg":
        out_gpkg = out_gpkg + ".gpkg"
    out_gpkg = check_file_path(out_gpkg)

    if isinstance(in_geojson, dict):
        out_file = temp_file_path(extension="geojson")
        with open(out_file, "w") as f:
            json.dump(in_geojson, f)
            in_geojson = out_file

    gdf = gpd.read_file(in_geojson, **kwargs)
    name = os.path.splitext(os.path.basename(out_gpkg))[0]
    gdf.to_file(out_gpkg, layer=name, driver="GPKG")

geojson_to_shp(in_geojson, out_shp, **kwargs)

Converts a GeoJSON object to GeoPandas GeoDataFrame.

Parameters:

Name Type Description Default
in_geojson str | dict

The input GeoJSON file or dict.

required
out_shp str

The output shapefile path.

required
Source code in leafmap/common.py
def geojson_to_shp(in_geojson, out_shp, **kwargs):
    """Converts a GeoJSON object to GeoPandas GeoDataFrame.

    Args:
        in_geojson (str | dict): The input GeoJSON file or dict.
        out_shp (str): The output shapefile path.
    """
    import geopandas as gpd
    import json

    ext = os.path.splitext(out_shp)[1]
    if ext != ".shp":
        out_shp = out_shp + ".shp"
    out_shp = check_file_path(out_shp)

    if isinstance(in_geojson, dict):
        out_file = temp_file_path(extension="geojson")
        with open(out_file, "w") as f:
            json.dump(in_geojson, f)
            in_geojson = out_file

    gdf = gpd.read_file(in_geojson, **kwargs)
    gdf.to_file(out_shp)

geom_type(in_geojson, encoding='utf-8')

Returns the geometry type of a GeoJSON object.

Parameters:

Name Type Description Default
in_geojson dict

A GeoJSON object.

required
encoding str

The encoding of the GeoJSON object. Defaults to "utf-8".

'utf-8'

Returns:

Type Description
str

The geometry type of the GeoJSON object.

Source code in leafmap/common.py
def geom_type(in_geojson, encoding="utf-8"):
    """Returns the geometry type of a GeoJSON object.

    Args:
        in_geojson (dict): A GeoJSON object.
        encoding (str, optional): The encoding of the GeoJSON object. Defaults to "utf-8".

    Returns:
        str: The geometry type of the GeoJSON object.
    """
    import json

    try:

        if isinstance(in_geojson, str):

            if in_geojson.startswith("http"):
                data = requests.get(in_geojson).json()
            else:
                in_geojson = os.path.abspath(in_geojson)
                if not os.path.exists(in_geojson):
                    raise FileNotFoundError(
                        "The provided GeoJSON file could not be found."
                    )

                with open(in_geojson, encoding=encoding) as f:
                    data = json.load(f)
        elif isinstance(in_geojson, dict):
            data = in_geojson
        else:
            raise TypeError("The input geojson must be a type of str or dict.")

        return data["features"][0]["geometry"]["type"]

    except Exception as e:
        raise Exception(e)

get_api_key(token_name, m=None)

Retrieves an API key based on a system environmen variable.

Parameters:

Name Type Description Default
token_name str

The token name.

required
m ipyleaflet.Map | folium.Map

A Map instance. Defaults to None.

None

Returns:

Type Description
str

The API key.

Source code in leafmap/common.py
def get_api_key(token_name, m=None):
    """Retrieves an API key based on a system environmen variable.

    Args:
        token_name (str): The token name.
        m (ipyleaflet.Map | folium.Map, optional): A Map instance. Defaults to None.

    Returns:
        str: The API key.
    """
    api_key = os.environ.get(token_name)
    if m is not None and token_name in m.api_keys:
        api_key = m.api_keys[token_name]

    return api_key

get_bounds(geometry, north_up=True, transform=None)

Bounding box of a GeoJSON geometry, GeometryCollection, or FeatureCollection. left, bottom, right, top not xmin, ymin, xmax, ymax If not north_up, y will be switched to guarantee the above. Source code adapted from https://github.com/mapbox/rasterio/blob/master/rasterio/features.py#L361

Parameters:

Name Type Description Default
geometry dict

A GeoJSON dict.

required
north_up bool

. Defaults to True.

True
transform [type]

. Defaults to None.

None

Returns:

Type Description
list

A list of coordinates representing [left, bottom, right, top]

Source code in leafmap/common.py
def get_bounds(geometry, north_up=True, transform=None):
    """Bounding box of a GeoJSON geometry, GeometryCollection, or FeatureCollection.
    left, bottom, right, top
    *not* xmin, ymin, xmax, ymax
    If not north_up, y will be switched to guarantee the above.
    Source code adapted from https://github.com/mapbox/rasterio/blob/master/rasterio/features.py#L361

    Args:
        geometry (dict): A GeoJSON dict.
        north_up (bool, optional): . Defaults to True.
        transform ([type], optional): . Defaults to None.

    Returns:
        list: A list of coordinates representing [left, bottom, right, top]
    """

    if "bbox" in geometry:
        return tuple(geometry["bbox"])

    geometry = geometry.get("geometry") or geometry

    # geometry must be a geometry, GeometryCollection, or FeatureCollection
    if not (
        "coordinates" in geometry or "geometries" in geometry or "features" in geometry
    ):
        raise ValueError(
            "geometry must be a GeoJSON-like geometry, GeometryCollection, "
            "or FeatureCollection"
        )

    if "features" in geometry:
        # Input is a FeatureCollection
        xmins = []
        ymins = []
        xmaxs = []
        ymaxs = []
        for feature in geometry["features"]:
            xmin, ymin, xmax, ymax = get_bounds(feature["geometry"])
            xmins.append(xmin)
            ymins.append(ymin)
            xmaxs.append(xmax)
            ymaxs.append(ymax)
        if north_up:
            return min(xmins), min(ymins), max(xmaxs), max(ymaxs)
        else:
            return min(xmins), max(ymaxs), max(xmaxs), min(ymins)

    elif "geometries" in geometry:
        # Input is a geometry collection
        xmins = []
        ymins = []
        xmaxs = []
        ymaxs = []
        for geometry in geometry["geometries"]:
            xmin, ymin, xmax, ymax = get_bounds(geometry)
            xmins.append(xmin)
            ymins.append(ymin)
            xmaxs.append(xmax)
            ymaxs.append(ymax)
        if north_up:
            return min(xmins), min(ymins), max(xmaxs), max(ymaxs)
        else:
            return min(xmins), max(ymaxs), max(xmaxs), min(ymins)

    elif "coordinates" in geometry:
        # Input is a singular geometry object
        if transform is not None:
            xyz = list(explode(geometry["coordinates"]))
            xyz_px = [transform * point for point in xyz]
            xyz = tuple(zip(*xyz_px))
            return min(xyz[0]), max(xyz[1]), max(xyz[0]), min(xyz[1])
        else:
            xyz = tuple(zip(*list(explode(geometry["coordinates"]))))
            if north_up:
                return min(xyz[0]), min(xyz[1]), max(xyz[0]), max(xyz[1])
            else:
                return min(xyz[0]), max(xyz[1]), max(xyz[0]), min(xyz[1])

    # all valid inputs returned above, so whatever falls through is an error
    raise ValueError(
        "geometry must be a GeoJSON-like geometry, GeometryCollection, "
        "or FeatureCollection"
    )

get_census_dict(reset=False)

Returns a dictionary of Census data.

Parameters:

Name Type Description Default
reset bool

Reset the dictionary. Defaults to False.

False

Returns:

Type Description
dict

A dictionary of Census data.

Source code in leafmap/common.py
def get_census_dict(reset=False):
    """Returns a dictionary of Census data.

    Args:
        reset (bool, optional): Reset the dictionary. Defaults to False.

    Returns:
        dict: A dictionary of Census data.
    """
    import json
    import pkg_resources

    pkg_dir = os.path.dirname(pkg_resources.resource_filename("leafmap", "leafmap.py"))
    census_data = os.path.join(pkg_dir, "data/census_data.json")

    if reset:

        try:
            from owslib.wms import WebMapService
        except ImportError:
            raise ImportError("Please install owslib using 'pip install owslib'.")

        census_dict = {}

        names = [
            "Current",
            "ACS 2021",
            "ACS 2019",
            "ACS 2018",
            "ACS 2017",
            "ACS 2016",
            "ACS 2015",
            "ACS 2014",
            "ACS 2013",
            "ACS 2012",
            "ECON 2012",
            "Census 2020",
            "Census 2010",
            "Physical Features",
            "Decennial Census 2020",
            "Decennial Census 2010",
            "Decennial Census 2000",
            "Decennial Physical Features",
        ]

        links = {}

        print("Retrieving data. Please wait ...")
        for name in names:
            if "Decennial" not in name:
                links[
                    name
                ] = f"https://tigerweb.geo.census.gov/arcgis/services/TIGERweb/tigerWMS_{name.replace(' ', '')}/MapServer/WMSServer"
            else:
                links[
                    name
                ] = f"https://tigerweb.geo.census.gov/arcgis/services/Census2020/tigerWMS_{name.replace('Decennial', '').replace(' ', '')}/MapServer/WMSServer"

            wms = WebMapService(links[name], timeout=300)
            layers = list(wms.contents)
            layers.sort()
            census_dict[name] = {
                "url": links[name],
                "layers": layers,
                # "title": wms.identification.title,
                # "abstract": wms.identification.abstract,
            }

        with open(census_data, "w") as f:
            json.dump(census_dict, f, indent=4)

    else:

        with open(census_data, "r") as f:
            census_dict = json.load(f)

    return census_dict

get_center(geometry, north_up=True, transform=None)

Get the centroid of a GeoJSON.

Parameters:

Name Type Description Default
geometry dict

A GeoJSON dict.

required
north_up bool

. Defaults to True.

True
transform [type]

. Defaults to None.

None

Returns:

Type Description
list

[lon, lat]

Source code in leafmap/common.py
def get_center(geometry, north_up=True, transform=None):
    """Get the centroid of a GeoJSON.

    Args:
        geometry (dict): A GeoJSON dict.
        north_up (bool, optional): . Defaults to True.
        transform ([type], optional): . Defaults to None.

    Returns:
        list: [lon, lat]
    """
    bounds = get_bounds(geometry, north_up, transform)
    center = ((bounds[0] + bounds[2]) / 2, (bounds[1] + bounds[3]) / 2)  # (lat, lon)
    return center

get_local_tile_layer(source, port='default', debug=False, projection='EPSG:3857', band=None, palette=None, vmin=None, vmax=None, nodata=None, attribution=None, tile_format='ipyleaflet', layer_name='Local COG', return_client=False, **kwargs)

Generate an ipyleaflet/folium TileLayer from a local raster dataset or remote Cloud Optimized GeoTIFF (COG). If you are using this function in JupyterHub on a remote server (e.g., Binder, Microsoft Planetary Computer), try adding to following two lines to the beginning of the notebook if the raster does not render properly.

1
2
import os
os.environ['LOCALTILESERVER_CLIENT_PREFIX'] = f'{os.environ['JUPYTERHUB_SERVICE_PREFIX'].lstrip('/')}/proxy/{{port}}'

Parameters:

Name Type Description Default
source str

The path to the GeoTIFF file or the URL of the Cloud Optimized GeoTIFF.

required
port str

The port to use for the server. Defaults to "default".

'default'
debug bool

If True, the server will be started in debug mode. Defaults to False.

False
projection str

The projection of the GeoTIFF. Defaults to "EPSG:3857".

'EPSG:3857'
band int

The band to use. Band indexing starts at 1. Defaults to None.

None
palette str

The name of the color palette from palettable to use when plotting a single band. See https://jiffyclub.github.io/palettable. Default is greyscale

None
vmin float

The minimum value to use when colormapping the palette when plotting a single band. Defaults to None.

None
vmax float

The maximum value to use when colormapping the palette when plotting a single band. Defaults to None.

None
nodata float

The value from the band to use to interpret as not valid data. Defaults to None.

None
attribution str

Attribution for the source raster. This defaults to a message about it being a local file.. Defaults to None.

None
tile_format str

The tile layer format. Can be either ipyleaflet or folium. Defaults to "ipyleaflet".

'ipyleaflet'
layer_name str

The layer name to use. Defaults to None.

'Local COG'
return_client bool

If True, the tile client will be returned. Defaults to False.

False

Returns:

Type Description
ipyleaflet.TileLayer | folium.TileLayer

An ipyleaflet.TileLayer or folium.TileLayer.

Source code in leafmap/common.py
def get_local_tile_layer(
    source,
    port="default",
    debug=False,
    projection="EPSG:3857",
    band=None,
    palette=None,
    vmin=None,
    vmax=None,
    nodata=None,
    attribution=None,
    tile_format="ipyleaflet",
    layer_name="Local COG",
    return_client=False,
    **kwargs,
):
    """Generate an ipyleaflet/folium TileLayer from a local raster dataset or remote Cloud Optimized GeoTIFF (COG).
        If you are using this function in JupyterHub on a remote server (e.g., Binder, Microsoft Planetary Computer),
        try adding to following two lines to the beginning of the notebook if the raster does not render properly.

        import os
        os.environ['LOCALTILESERVER_CLIENT_PREFIX'] = f'{os.environ['JUPYTERHUB_SERVICE_PREFIX'].lstrip('/')}/proxy/{{port}}'

    Args:
        source (str): The path to the GeoTIFF file or the URL of the Cloud Optimized GeoTIFF.
        port (str, optional): The port to use for the server. Defaults to "default".
        debug (bool, optional): If True, the server will be started in debug mode. Defaults to False.
        projection (str, optional): The projection of the GeoTIFF. Defaults to "EPSG:3857".
        band (int, optional): The band to use. Band indexing starts at 1. Defaults to None.
        palette (str, optional): The name of the color palette from `palettable` to use when plotting a single band. See https://jiffyclub.github.io/palettable. Default is greyscale
        vmin (float, optional): The minimum value to use when colormapping the palette when plotting a single band. Defaults to None.
        vmax (float, optional): The maximum value to use when colormapping the palette when plotting a single band. Defaults to None.
        nodata (float, optional): The value from the band to use to interpret as not valid data. Defaults to None.
        attribution (str, optional): Attribution for the source raster. This defaults to a message about it being a local file.. Defaults to None.
        tile_format (str, optional): The tile layer format. Can be either ipyleaflet or folium. Defaults to "ipyleaflet".
        layer_name (str, optional): The layer name to use. Defaults to None.
        return_client (bool, optional): If True, the tile client will be returned. Defaults to False.

    Returns:
        ipyleaflet.TileLayer | folium.TileLayer: An ipyleaflet.TileLayer or folium.TileLayer.
    """

    check_package(
        "localtileserver", URL="https://github.com/banesullivan/localtileserver"
    )

    # Make it compatible with binder and JupyterHub
    if os.environ.get("JUPYTERHUB_SERVICE_PREFIX") is not None:
        os.environ[
            "LOCALTILESERVER_CLIENT_PREFIX"
        ] = f"{os.environ['JUPYTERHUB_SERVICE_PREFIX'].lstrip('/')}/proxy/{{port}}"

    from localtileserver import (
        get_leaflet_tile_layer,
        get_folium_tile_layer,
        TileClient,
    )

    if isinstance(source, str):
        if not source.startswith("http"):
            if source.startswith("~"):
                source = os.path.expanduser(source)
            else:
                source = os.path.abspath(source)
            if not os.path.exists(source):
                raise ValueError("The source path does not exist.")
    else:
        raise ValueError("The source must either be a string or TileClient")

    if isinstance(palette, str):

        palette = get_palette_colors(palette, hashtag=True)

    if tile_format not in ["ipyleaflet", "folium"]:
        raise ValueError("The tile format must be either ipyleaflet or folium.")

    if layer_name is None:
        if source.startswith("http"):
            layer_name = "RemoteTile_" + random_string(3)
        else:
            layer_name = "LocalTile_" + random_string(3)

    tile_client = TileClient(source, port=port, debug=debug)

    if tile_format == "ipyleaflet":
        tile_layer = get_leaflet_tile_layer(
            tile_client,
            port=port,
            debug=debug,
            projection=projection,
            band=band,
            palette=palette,
            vmin=vmin,
            vmax=vmax,
            nodata=nodata,
            attribution=attribution,
            name=layer_name,
            **kwargs,
        )
    else:
        tile_layer = get_folium_tile_layer(
            tile_client,
            port=port,
            debug=debug,
            projection=projection,
            band=band,
            palette=palette,
            vmin=vmin,
            vmax=vmax,
            nodata=nodata,
            attr=attribution,
            overlay=True,
            name=layer_name,
            **kwargs,
        )

    if return_client:
        return tile_layer, tile_client
    else:
        return tile_layer

    # center = tile_client.center()
    # bounds = tile_client.bounds()  # [ymin, ymax, xmin, xmax]
    # bounds = (bounds[2], bounds[0], bounds[3], bounds[1])  # [minx, miny, maxx, maxy]

    # if get_center and get_bounds:
    #     return tile_layer, center, bounds
    # elif get_center:
    #     return tile_layer, center
    # elif get_bounds:
    #     return tile_layer, bounds
    # else:
    #     return tile_layer

get_palettable(types=None)

Get a list of palettable color palettes.

Parameters:

Name Type Description Default
types list

A list of palettable types to return, e.g., types=['matplotlib', 'cartocolors']. Defaults to None.

None

Returns:

Type Description
list

A list of palettable color palettes.

Source code in leafmap/common.py
def get_palettable(types=None):
    """Get a list of palettable color palettes.

    Args:
        types (list, optional): A list of palettable types to return, e.g., types=['matplotlib', 'cartocolors']. Defaults to None.

    Returns:
        list: A list of palettable color palettes.
    """
    try:
        import palettable
    except ImportError:
        raise ImportError(
            "Please install the palettable package using 'pip install palettable'."
        )

    if types is not None and (not isinstance(types, list)):
        raise ValueError("The types must be a list.")

    allowed_palettes = [
        "cartocolors",
        "cmocean",
        "colorbrewer",
        "cubehelix",
        "lightbartlein",
        "matplotlib",
        "mycarta",
        "scientific",
        "tableau",
        "wesanderson",
    ]

    if types is None:
        types = allowed_palettes[:]

    if all(x in allowed_palettes for x in types):
        pass
    else:
        raise ValueError(
            "The types must be one of the following: " + ", ".join(allowed_palettes)
        )

    palettes = []

    if "cartocolors" in types:

        cartocolors_diverging = [
            f"cartocolors.diverging.{c}"
            for c in dir(palettable.cartocolors.diverging)[:-19]
        ]
        cartocolors_qualitative = [
            f"cartocolors.qualitative.{c}"
            for c in dir(palettable.cartocolors.qualitative)[:-19]
        ]
        cartocolors_sequential = [
            f"cartocolors.sequential.{c}"
            for c in dir(palettable.cartocolors.sequential)[:-41]
        ]

        palettes = (
            palettes
            + cartocolors_diverging
            + cartocolors_qualitative
            + cartocolors_sequential
        )

    if "cmocean" in types:

        cmocean_diverging = [
            f"cmocean.diverging.{c}" for c in dir(palettable.cmocean.diverging)[:-19]
        ]
        cmocean_sequential = [
            f"cmocean.sequential.{c}" for c in dir(palettable.cmocean.sequential)[:-19]
        ]

        palettes = palettes + cmocean_diverging + cmocean_sequential

    if "colorbrewer" in types:

        colorbrewer_diverging = [
            f"colorbrewer.diverging.{c}"
            for c in dir(palettable.colorbrewer.diverging)[:-19]
        ]
        colorbrewer_qualitative = [
            f"colorbrewer.qualitative.{c}"
            for c in dir(palettable.colorbrewer.qualitative)[:-19]
        ]
        colorbrewer_sequential = [
            f"colorbrewer.sequential.{c}"
            for c in dir(palettable.colorbrewer.sequential)[:-41]
        ]

        palettes = (
            palettes
            + colorbrewer_diverging
            + colorbrewer_qualitative
            + colorbrewer_sequential
        )

    if "cubehelix" in types:
        cubehelix = [
            "classic_16",
            "cubehelix1_16",
            "cubehelix2_16",
            "cubehelix3_16",
            "jim_special_16",
            "perceptual_rainbow_16",
            "purple_16",
            "red_16",
        ]
        cubehelix = [f"cubehelix.{c}" for c in cubehelix]
        palettes = palettes + cubehelix

    if "lightbartlein" in types:
        lightbartlein_diverging = [
            f"lightbartlein.diverging.{c}"
            for c in dir(palettable.lightbartlein.diverging)[:-19]
        ]
        lightbartlein_sequential = [
            f"lightbartlein.sequential.{c}"
            for c in dir(palettable.lightbartlein.sequential)[:-19]
        ]

        palettes = palettes + lightbartlein_diverging + lightbartlein_sequential

    if "matplotlib" in types:
        matplotlib_colors = [
            f"matplotlib.{c}" for c in dir(palettable.matplotlib)[:-16]
        ]
        palettes = palettes + matplotlib_colors

    if "mycarta" in types:
        mycarta = [f"mycarta.{c}" for c in dir(palettable.mycarta)[:-16]]
        palettes = palettes + mycarta

    if "scientific" in types:
        scientific_diverging = [
            f"scientific.diverging.{c}"
            for c in dir(palettable.scientific.diverging)[:-19]
        ]
        scientific_sequential = [
            f"scientific.sequential.{c}"
            for c in dir(palettable.scientific.sequential)[:-19]
        ]

        palettes = palettes + scientific_diverging + scientific_sequential

    if "tableau" in types:
        tableau = [f"tableau.{c}" for c in dir(palettable.tableau)[:-14]]
        palettes = palettes + tableau

    return palettes

get_palette_colors(cmap_name=None, n_class=None, hashtag=False)

Get a palette from a matplotlib colormap. See the list of colormaps at https://matplotlib.org/stable/tutorials/colors/colormaps.html.

Parameters:

Name Type Description Default
cmap_name str

The name of the matplotlib colormap. Defaults to None.

None
n_class int

The number of colors. Defaults to None.

None
hashtag bool

Whether to return a list of hex colors. Defaults to False.

False

Returns:

Type Description
list

A list of hex colors.

Source code in leafmap/common.py
def get_palette_colors(cmap_name=None, n_class=None, hashtag=False):
    """Get a palette from a matplotlib colormap. See the list of colormaps at https://matplotlib.org/stable/tutorials/colors/colormaps.html.

    Args:
        cmap_name (str, optional): The name of the matplotlib colormap. Defaults to None.
        n_class (int, optional): The number of colors. Defaults to None.
        hashtag (bool, optional): Whether to return a list of hex colors. Defaults to False.

    Returns:
        list: A list of hex colors.
    """
    import matplotlib as mpl
    import matplotlib.pyplot as plt

    cmap = plt.cm.get_cmap(cmap_name, n_class)
    colors = [mpl.colors.rgb2hex(cmap(i))[1:] for i in range(cmap.N)]
    if hashtag:
        colors = ["#" + i for i in colors]
    return colors

get_stac_collections(url)

Retrieve a list of STAC collections from a URL. This function is adapted from https://github.com/mykolakozyr/stacdiscovery/blob/a5d1029aec9c428a7ce7ae615621ea8915162824/app.py#L31. Credits to Mykola Kozyr.

Parameters:

Name Type Description Default
url str

A URL to a STAC catalog.

required

Returns:

Type Description
list

A list of STAC collections.

Source code in leafmap/common.py
def get_stac_collections(url):
    """Retrieve a list of STAC collections from a URL.
    This function is adapted from https://github.com/mykolakozyr/stacdiscovery/blob/a5d1029aec9c428a7ce7ae615621ea8915162824/app.py#L31.
    Credits to Mykola Kozyr.

    Args:
        url (str): A URL to a STAC catalog.

    Returns:
        list: A list of STAC collections.
    """
    from pystac_client import Client

    # Expensive function. Added cache for it.

    # Empty list that would be used for a dataframe to collect and visualize info about collections
    root_catalog = Client.open(url)
    collections_list = []
    # Reading collections in the Catalog
    collections = list(root_catalog.get_collections())
    print(collections)
    for collection in collections:
        id = collection.id
        title = collection.title
        # bbox = collection.extent.spatial.bboxes # not in use for the first release
        # interval = collection.extent.temporal.intervals # not in use for the first release
        description = collection.description

        # creating a list of lists of values
        collections_list.append([id, title, description])
    return collections_list

get_stac_items(url, collection, limit=None, bbox=None, datetime=None, intersects=None, ids=None, **kwargs)

Retrieve a list of STAC items from a URL and a collection. This function is adapted from https://github.com/mykolakozyr/stacdiscovery/blob/a5d1029aec9c428a7ce7ae615621ea8915162824/app.py#L49. Credits to Mykola Kozyr. Available parameters can be found at https://github.com/radiantearth/stac-api-spec/tree/master/item-search

Parameters:

Name Type Description Default
url str

A URL to a STAC catalog.

required
collection str

A STAC collection ID.

required
limit int

The maximum number of results to return (page size). Defaults to None.

None
bbox tuple

Requested bounding box in the format of (minx, miny, maxx, maxy). Defaults to None.

None
datetime str

Single date+time, or a range ('/' separator), formatted to RFC 3339, section 5.6. Use double dots .. for open date ranges.

None
intersects dict

A dictionary representing a GeoJSON Geometry. Searches items by performing intersection between their geometry and provided GeoJSON geometry. All GeoJSON geometry types must be supported.

None
ids list

A list of item ids to return.

None

Returns:

Type Description
GeoPandas.GeoDataFraem

A GeoDataFrame with the STAC items.

Source code in leafmap/common.py
def get_stac_items(
    url,
    collection,
    limit=None,
    bbox=None,
    datetime=None,
    intersects=None,
    ids=None,
    **kwargs,
):
    """Retrieve a list of STAC items from a URL and a collection.
    This function is adapted from https://github.com/mykolakozyr/stacdiscovery/blob/a5d1029aec9c428a7ce7ae615621ea8915162824/app.py#L49.
    Credits to Mykola Kozyr.
    Available parameters can be found at https://github.com/radiantearth/stac-api-spec/tree/master/item-search

    Args:
        url (str): A URL to a STAC catalog.
        collection (str): A STAC collection ID.
        limit (int, optional): The maximum number of results to return (page size). Defaults to None.
        bbox (tuple, optional): Requested bounding box in the format of (minx, miny, maxx, maxy). Defaults to None.
        datetime (str, optional): Single date+time, or a range ('/' separator), formatted to RFC 3339, section 5.6. Use double dots .. for open date ranges.
        intersects (dict, optional): A dictionary representing a GeoJSON Geometry. Searches items by performing intersection between their geometry and provided GeoJSON geometry. All GeoJSON geometry types must be supported.
        ids (list, optional): A list of item ids to return.

    Returns:
        GeoPandas.GeoDataFraem: A GeoDataFrame with the STAC items.
    """

    import itertools
    import geopandas as gpd
    from shapely.geometry import shape
    from pystac_client import Client

    # Empty list that would be used for a dataframe to collect and visualize info about collections
    items_list = []
    root_catalog = Client.open(url)

    if limit:
        kwargs["limit"] = limit
    if bbox:
        kwargs["bbox"] = bbox
    if datetime:
        kwargs["datetime"] = datetime
    if intersects:
        kwargs["intersects"] = intersects
    if ids:
        kwargs["ids"] = ids

    if kwargs:
        try:
            catalog = root_catalog.search(collections=collection, **kwargs)
        except NotImplementedError:
            catalog = root_catalog
    else:
        catalog = root_catalog

    iterable = catalog.get_all_items()
    items = list(
        itertools.islice(iterable, limit)
    )  # getting first 25000 items. To Do some smarter logic
    if len(items) == 0:
        try:
            catalog = root_catalog.get_child(collection)
            iterable = catalog.get_all_items()
            items = list(itertools.islice(iterable, limit))
        except Exception as _:
            print("Ooops, it looks like this collection does not have items.")
            return None
    # Iterating over items to collect main information
    for item in items:
        id = item.id
        geometry = shape(item.geometry)
        datetime = (
            item.datetime
            or item.properties["datetime"]
            or item.properties["end_datetime"]
            or item.properties["start_datetime"]
        )
        links = item.links
        for link in links:
            if link.rel == "self":
                self_url = link.target
        assets_list = []
        assets = item.assets
        for asset in assets:
            assets_list.append(asset)

        # creating a list of lists of values
        items_list.append([id, geometry, datetime, self_url, assets_list])

    if limit is not None:
        items_list = items_list[:limit]
    items_df = gpd.GeoDataFrame(items_list)
    items_df.columns = ["id", "geometry", "datetime", "self_url", "assets_list"]

    items_gdf = items_df.set_geometry("geometry")
    items_gdf["datetime"] = items_gdf["datetime"].astype(
        str
    )  # specifically for KeplerGL. See https://github.com/keplergl/kepler.gl/issues/602
    # items_gdf["assets_list"] = items_gdf["assets_list"].astype(str) #specifically for KeplerGL. See https://github.com/keplergl/kepler.gl/issues/602
    items_gdf.set_crs(epsg=4326, inplace=True)
    return items_gdf

get_wms_layers(url)

Returns a list of WMS layers from a WMS service.

Parameters:

Name Type Description Default
url str

The URL of the WMS service.

required

Returns:

Type Description
list

A list of WMS layers.

Source code in leafmap/common.py
def get_wms_layers(url):
    """Returns a list of WMS layers from a WMS service.

    Args:
        url (str): The URL of the WMS service.

    Returns:
        list: A list of WMS layers.
    """
    try:
        from owslib.wms import WebMapService
    except ImportError:
        raise ImportError("Please install owslib using 'pip install owslib'.")

    wms = WebMapService(url)
    layers = list(wms.contents)
    layers.sort()
    return layers

has_transparency(img)

Checks whether an image has transparency.

Parameters:

Name Type Description Default
img object

a PIL Image object.

required

Returns:

Type Description
bool

True if it has transparency, False otherwise.

Source code in leafmap/common.py
def has_transparency(img):
    """Checks whether an image has transparency.

    Args:
        img (object):  a PIL Image object.

    Returns:
        bool: True if it has transparency, False otherwise.
    """

    if img.mode == "P":
        transparent = img.info.get("transparency", -1)
        for _, index in img.getcolors():
            if index == transparent:
                return True
    elif img.mode == "RGBA":
        extrema = img.getextrema()
        if extrema[3][0] < 255:
            return True

    return False

hex_to_rgb(value='FFFFFF')

Converts hex color to RGB color.

Parameters:

Name Type Description Default
value str

Hex color code as a string. Defaults to 'FFFFFF'.

'FFFFFF'

Returns:

Type Description
tuple

RGB color as a tuple.

Source code in leafmap/common.py
def hex_to_rgb(value="FFFFFF"):
    """Converts hex color to RGB color.

    Args:
        value (str, optional): Hex color code as a string. Defaults to 'FFFFFF'.

    Returns:
        tuple: RGB color as a tuple.
    """
    value = value.lstrip("#")
    lv = len(value)
    return tuple(int(value[i : i + lv // 3], 16) for i in range(0, lv, lv // 3))

html_to_streamlit(html, width=800, height=600, responsive=True, scrolling=False, token_name=None, token_value=None, **kwargs)

Renders an HTML file in a Streamlit app. This method is a static Streamlit Component, meaning, no information is passed back from Leaflet on browser interaction.

Parameters:

Name Type Description Default
html str

The HTML file to render. It can a local file path or a URL.

required
width int

Width of the map. Defaults to 800.

800
height int

Height of the map. Defaults to 600.

600
responsive bool

Whether to make the map responsive. Defaults to True.

True
scrolling bool

Whether to allow the map to scroll. Defaults to False.

False
token_name str

The name of the token in the HTML file to be replaced. Defaults to None.

None
token_value str

The value of the token to pass to the HTML file. Defaults to None.

None

Returns:

Type Description
streamlit.components

components.html object.

Source code in leafmap/common.py
def html_to_streamlit(
    html,
    width=800,
    height=600,
    responsive=True,
    scrolling=False,
    token_name=None,
    token_value=None,
    **kwargs,
):
    """Renders an HTML file in a Streamlit app. This method is a static Streamlit Component, meaning, no information is passed back from Leaflet on browser interaction.

    Args:
        html (str): The HTML file to render. It can a local file path or a URL.
        width (int, optional): Width of the map. Defaults to 800.
        height (int, optional): Height of the map. Defaults to 600.
        responsive (bool, optional): Whether to make the map responsive. Defaults to True.
        scrolling (bool, optional): Whether to allow the map to scroll. Defaults to False.
        token_name (str, optional): The name of the token in the HTML file to be replaced. Defaults to None.
        token_value (str, optional): The value of the token to pass to the HTML file. Defaults to None.

    Returns:
        streamlit.components: components.html object.
    """

    try:
        import streamlit as st
        import streamlit.components.v1 as components

        if isinstance(html, str):

            temp_path = None
            if html.startswith("http") and html.endswith(".html"):
                temp_path = temp_file_path(".html")
                out_file = os.path.basename(temp_path)
                out_dir = os.path.dirname(temp_path)
                download_from_url(html, out_file, out_dir)
                html = temp_path

            elif not os.path.exists(html):
                raise FileNotFoundError("The specified input html does not exist.")

            with open(html) as f:
                lines = f.readlines()
                if (token_name is not None) and (token_value is not None):
                    lines = [line.replace(token_name, token_value) for line in lines]
                html_str = "".join(lines)

            if temp_path is not None:
                os.remove(temp_path)

            if responsive:
                make_map_responsive = """
                <style>
                [title~="st.iframe"] { width: 100%}
                </style>
                """
                st.markdown(make_map_responsive, unsafe_allow_html=True)
            return components.html(
                html_str, width=width, height=height, scrolling=scrolling
            )
        else:
            raise TypeError("The html must be a string.")

    except Exception as e:
        raise Exception(e)

image_to_cog(source, dst_path=None, profile='deflate', **kwargs)

Converts an image to a COG file.

Parameters:

Name Type Description Default
source str

A dataset path, URL or rasterio.io.DatasetReader object.

required
dst_path str

An output dataset path or or PathLike object. Defaults to None.

None
profile str

COG profile. More at https://cogeotiff.github.io/rio-cogeo/profile. Defaults to "deflate".

'deflate'

Exceptions:

Type Description
ImportError

If rio-cogeo is not installed.

FileNotFoundError

If the source file could not be found.

Source code in leafmap/common.py
def image_to_cog(source, dst_path=None, profile="deflate", **kwargs):
    """Converts an image to a COG file.

    Args:
        source (str): A dataset path, URL or rasterio.io.DatasetReader object.
        dst_path (str, optional): An output dataset path or or PathLike object. Defaults to None.
        profile (str, optional): COG profile. More at https://cogeotiff.github.io/rio-cogeo/profile. Defaults to "deflate".

    Raises:
        ImportError: If rio-cogeo is not installed.
        FileNotFoundError: If the source file could not be found.
    """
    try:
        from rio_cogeo.cogeo import cog_translate
        from rio_cogeo.profiles import cog_profiles

    except ImportError:
        raise ImportError(
            "The rio-cogeo package is not installed. Please install it with `pip install rio-cogeo` or `conda install rio-cogeo -c conda-forge`."
        )

    if not source.startswith("http"):
        source = check_file_path(source)

        if not os.path.exists(source):
            raise FileNotFoundError("The provided input file could not be found.")

    if dst_path is None:
        if not source.startswith("http"):
            dst_path = os.path.splitext(source)[0] + "_cog.tif"
        else:
            dst_path = temp_file_path(extension=".tif")

    dst_path = check_file_path(dst_path)

    dst_profile = cog_profiles.get(profile)
    cog_translate(source, dst_path, dst_profile, **kwargs)

image_to_numpy(image)

Converts an image to a numpy array.

Parameters:

Name Type Description Default
image str

A dataset path, URL or rasterio.io.DatasetReader object.

required

Exceptions:

Type Description
FileNotFoundError

If the provided file could not be found.

Returns:

Type Description
np.array

A numpy array.

Source code in leafmap/common.py
def image_to_numpy(image):
    """Converts an image to a numpy array.

    Args:
        image (str): A dataset path, URL or rasterio.io.DatasetReader object.

    Raises:
        FileNotFoundError: If the provided file could not be found.

    Returns:
        np.array: A numpy array.
    """
    import rasterio

    if not os.path.exists(image):
        raise FileNotFoundError("The provided input file could not be found.")

    with rasterio.open(image, "r") as ds:
        arr = ds.read()  # read all raster values

    return arr

kml_to_geojson(in_kml, out_geojson=None)

Converts a KML to GeoJSON.

Parameters:

Name Type Description Default
in_kml str

The file path to the input KML.

required
out_geojson str

The file path to the output GeoJSON. Defaults to None.

None

Exceptions:

Type Description
FileNotFoundError

The input KML could not be found.

TypeError

The output must be a GeoJSON.

Source code in leafmap/common.py
def kml_to_geojson(in_kml, out_geojson=None):
    """Converts a KML to GeoJSON.

    Args:
        in_kml (str): The file path to the input KML.
        out_geojson (str): The file path to the output GeoJSON. Defaults to None.

    Raises:
        FileNotFoundError: The input KML could not be found.
        TypeError: The output must be a GeoJSON.
    """
    import warnings

    warnings.filterwarnings("ignore")

    in_kml = os.path.abspath(in_kml)
    if not os.path.exists(in_kml):
        raise FileNotFoundError("The input KML could not be found.")

    if out_geojson is not None:
        out_geojson = os.path.abspath(out_geojson)
        ext = os.path.splitext(out_geojson)[1].lower()
        if ext not in [".json", ".geojson"]:
            raise TypeError("The output file must be a GeoJSON.")

        out_dir = os.path.dirname(out_geojson)
        if not os.path.exists(out_dir):
            os.makedirs(out_dir)

    check_package(name="geopandas", URL="https://geopandas.org")

    import geopandas as gpd

    # import fiona
    # print(fiona.supported_drivers)
    gpd.io.file.fiona.drvsupport.supported_drivers["KML"] = "rw"
    gdf = gpd.read_file(in_kml, driver="KML")

    if out_geojson is not None:
        gdf.to_file(out_geojson, driver="GeoJSON")
    else:
        return gdf.__geo_interface__

kml_to_shp(in_kml, out_shp)

Converts a KML to shapefile.

Parameters:

Name Type Description Default
in_kml str

The file path to the input KML.

required
out_shp str

The file path to the output shapefile.

required

Exceptions:

Type Description
FileNotFoundError

The input KML could not be found.

TypeError

The output must be a shapefile.

Source code in leafmap/common.py
def kml_to_shp(in_kml, out_shp):
    """Converts a KML to shapefile.

    Args:
        in_kml (str): The file path to the input KML.
        out_shp (str): The file path to the output shapefile.

    Raises:
        FileNotFoundError: The input KML could not be found.
        TypeError: The output must be a shapefile.
    """
    import warnings

    warnings.filterwarnings("ignore")

    in_kml = os.path.abspath(in_kml)
    if not os.path.exists(in_kml):
        raise FileNotFoundError("The input KML could not be found.")

    out_shp = os.path.abspath(out_shp)
    if not out_shp.endswith(".shp"):
        raise TypeError("The output must be a shapefile.")

    out_dir = os.path.dirname(out_shp)
    if not os.path.exists(out_dir):
        os.makedirs(out_dir)

    check_package(name="geopandas", URL="https://geopandas.org")

    import geopandas as gpd

    # import fiona
    # print(fiona.supported_drivers)
    gpd.io.file.fiona.drvsupport.supported_drivers["KML"] = "rw"
    df = gpd.read_file(in_kml, driver="KML")
    df.to_file(out_shp)

list_palettes(add_extra=False, lowercase=False)

List all available colormaps. See a complete lost of colormaps at https://matplotlib.org/stable/tutorials/colors/colormaps.html.

Returns:

Type Description
list

The list of colormap names.

Source code in leafmap/common.py
def list_palettes(add_extra=False, lowercase=False):
    """List all available colormaps. See a complete lost of colormaps at https://matplotlib.org/stable/tutorials/colors/colormaps.html.

    Returns:
        list: The list of colormap names.
    """
    import matplotlib.pyplot as plt

    result = plt.colormaps()
    if add_extra:
        result += ["dem", "ndvi", "ndwi"]
    if lowercase:
        result = [i.lower() for i in result]
    result.sort()
    return result

local_tile_bands(source)

Get band names from COG.

Parameters:

Name Type Description Default
source str | TileClient

A local COG file path or TileClient

required

Returns:

Type Description
list

A list of band names.

Source code in leafmap/common.py
def local_tile_bands(source):
    """Get band names from COG.

    Args:
        source (str | TileClient): A local COG file path or TileClient

    Returns:
        list: A list of band names.
    """
    check_package("localtileserver", "https://github.com/banesullivan/localtileserver")
    from localtileserver import TileClient

    if isinstance(source, str):
        tile_client = TileClient(source)
    elif isinstance(source, TileClient):
        tile_client = source
    else:
        raise ValueError("source must be a string or TileClient object.")

    bandnames = list(tile_client.metadata()["bands"].keys())
    return bandnames

local_tile_pixel_value(lon, lat, tile_client, verbose=True, **kwargs)

Get pixel value from COG.

Parameters:

Name Type Description Default
lon float

Longitude of the pixel.

required
lat float

Latitude of the pixel.

required
url str

HTTP URL to a COG, e.g., 'https://opendata.digitalglobe.com/events/california-fire-2020/pre-event/2018-02-16/pine-gulch-fire20/1030010076004E00.tif'

required
bidx str

Dataset band indexes (e.g bidx=1, bidx=1&bidx=2&bidx=3). Defaults to None.

required
titiler_endpoint str

Titiler endpoint, e.g., "https://titiler.xyz", "planetary-computer", "pc". Defaults to None.

required
verbose bool

Print status messages. Defaults to True.

True

Returns:

Type Description
list

A dictionary of band info.

Source code in leafmap/common.py
def local_tile_pixel_value(
    lon,
    lat,
    tile_client,
    verbose=True,
    **kwargs,
):
    """Get pixel value from COG.

    Args:
        lon (float): Longitude of the pixel.
        lat (float): Latitude of the pixel.
        url (str): HTTP URL to a COG, e.g., 'https://opendata.digitalglobe.com/events/california-fire-2020/pre-event/2018-02-16/pine-gulch-fire20/1030010076004E00.tif'
        bidx (str, optional): Dataset band indexes (e.g bidx=1, bidx=1&bidx=2&bidx=3). Defaults to None.
        titiler_endpoint (str, optional): Titiler endpoint, e.g., "https://titiler.xyz", "planetary-computer", "pc". Defaults to None.
        verbose (bool, optional): Print status messages. Defaults to True.

    Returns:
        list: A dictionary of band info.
    """

    r = tile_client.pixel(lat, lon, units="EPSG:4326", **kwargs)
    if "bands" in r:
        return r["bands"]
    else:
        if verbose:
            print("No pixel value found.")
        return None

local_tile_vmin_vmax(source, bands=None, **kwargs)

Get vmin and vmax from COG.

Parameters:

Name Type Description Default
source str | TileClient

A local COG file path or TileClient object.

required
bands str | list

A list of band names. Defaults to None.

None

Exceptions:

Type Description
ValueError

If source is not a TileClient object or a local COG file path.

Returns:

Type Description
tuple

A tuple of vmin and vmax.

Source code in leafmap/common.py
def local_tile_vmin_vmax(
    source,
    bands=None,
    **kwargs,
):
    """Get vmin and vmax from COG.

    Args:
        source (str | TileClient): A local COG file path or TileClient object.
        bands (str | list, optional): A list of band names. Defaults to None.

    Raises:
        ValueError: If source is not a TileClient object or a local COG file path.

    Returns:
        tuple: A tuple of vmin and vmax.
    """
    check_package("localtileserver", "https://github.com/banesullivan/localtileserver")
    from localtileserver import TileClient

    if isinstance(source, str):
        tile_client = TileClient(source)
    elif isinstance(source, TileClient):
        tile_client = source
    else:
        raise ValueError("source must be a string or TileClient object.")

    stats = tile_client.metadata()["bands"]
    bandnames = list(stats.keys())

    if isinstance(bands, str):
        bands = [bands]
    elif isinstance(bands, list):
        pass
    elif bands is None:
        bands = bandnames

    if all(b in bandnames for b in bands):
        vmin = min([stats[b]["min"] for b in bands])
        vmax = max([stats[b]["max"] for b in bands])
    else:
        vmin = min([stats[b]["min"] for b in bandnames])
        vmax = max([stats[b]["max"] for b in bandnames])
    return vmin, vmax

mosaic_bounds(url, titiler_endpoint=None, **kwargs)

Get the bounding box of a MosaicJSON.

Parameters:

Name Type Description Default
url str

HTTP URL to a MosaicJSON.

required
titiler_endpoint str

Titiler endpoint, e.g., "https://titiler.xyz". Defaults to None.

None

Returns:

Type Description
list

A list of values representing [left, bottom, right, top]

Source code in leafmap/common.py
def mosaic_bounds(url, titiler_endpoint=None, **kwargs):
    """Get the bounding box of a MosaicJSON.

    Args:
        url (str): HTTP URL to a MosaicJSON.
        titiler_endpoint (str, optional): Titiler endpoint, e.g., "https://titiler.xyz". Defaults to None.

    Returns:
        list: A list of values representing [left, bottom, right, top]
    """

    if titiler_endpoint is None:
        titiler_endpoint = "https://titiler.xyz"

    if isinstance(url, str) and url.startswith("http"):
        kwargs["url"] = url
    else:
        raise ValueError("url must be a string and start with http.")

    if isinstance(titiler_endpoint, str):
        r = requests.get(
            f"{titiler_endpoint}/mosaicjson/bounds",
            params=kwargs,
        ).json()
    else:
        raise ValueError("titiler_endpoint must be a string.")

    return r["bounds"]

mosaic_info(url, titiler_endpoint=None, **kwargs)

Get the info of a MosaicJSON.

Parameters:

Name Type Description Default
url str

HTTP URL to a MosaicJSON.

required
titiler_endpoint str

Titiler endpoint, e.g., "https://titiler.xyz". Defaults to None.

None

Returns:

Type Description
dict

A dictionary containing bounds, center, minzoom, maxzoom, and name as keys.

Source code in leafmap/common.py
def mosaic_info(url, titiler_endpoint=None, **kwargs):
    """Get the info of a MosaicJSON.

    Args:
        url (str): HTTP URL to a MosaicJSON.
        titiler_endpoint (str, optional): Titiler endpoint, e.g., "https://titiler.xyz". Defaults to None.

    Returns:
        dict: A dictionary containing bounds, center, minzoom, maxzoom, and name as keys.
    """

    if titiler_endpoint is None:
        titiler_endpoint = "https://titiler.xyz"

    if isinstance(url, str) and url.startswith("http"):
        kwargs["url"] = url
    else:
        raise ValueError("url must be a string and start with http.")

    if isinstance(titiler_endpoint, str):
        r = requests.get(
            f"{titiler_endpoint}/mosaicjson/info",
            params=kwargs,
        ).json()
    else:
        raise ValueError("titiler_endpoint must be a string.")

    return r

mosaic_info_geojson(url, titiler_endpoint=None, **kwargs)

Get the info of a MosaicJSON.

Parameters:

Name Type Description Default
url str

HTTP URL to a MosaicJSON.

required
titiler_endpoint str

Titiler endpoint, e.g., "https://titiler.xyz". Defaults to None.

None

Returns:

Type Description
dict

A dictionary representing a dict of GeoJSON.

Source code in leafmap/common.py
def mosaic_info_geojson(url, titiler_endpoint=None, **kwargs):
    """Get the info of a MosaicJSON.

    Args:
        url (str): HTTP URL to a MosaicJSON.
        titiler_endpoint (str, optional): Titiler endpoint, e.g., "https://titiler.xyz". Defaults to None.

    Returns:
        dict: A dictionary representing a dict of GeoJSON.
    """

    if titiler_endpoint is None:
        titiler_endpoint = "https://titiler.xyz"

    if isinstance(url, str) and url.startswith("http"):
        kwargs["url"] = url
    else:
        raise ValueError("url must be a string and start with http.")

    if isinstance(titiler_endpoint, str):
        r = requests.get(
            f"{titiler_endpoint}/mosaicjson/info.geojson",
            params=kwargs,
        ).json()
    else:
        raise ValueError("titiler_endpoint must be a string.")

    return r

mosaic_tile(url, titiler_endpoint=None, **kwargs)

Get the tile URL from a MosaicJSON.

Parameters:

Name Type Description Default
url str

HTTP URL to a MosaicJSON.

required
titiler_endpoint str

Titiler endpoint, e.g., "https://titiler.xyz". Defaults to None.

None

Returns:

Type Description
str

The tile URL.

Source code in leafmap/common.py
def mosaic_tile(url, titiler_endpoint=None, **kwargs):
    """Get the tile URL from a MosaicJSON.

    Args:
        url (str): HTTP URL to a MosaicJSON.
        titiler_endpoint (str, optional): Titiler endpoint, e.g., "https://titiler.xyz". Defaults to None.

    Returns:
        str: The tile URL.
    """

    if titiler_endpoint is None:
        titiler_endpoint = "https://titiler.xyz"

    if isinstance(url, str) and url.startswith("http"):
        kwargs["url"] = url
    else:
        raise ValueError("url must be a string and start with http.")

    if isinstance(titiler_endpoint, str):
        r = requests.get(
            f"{titiler_endpoint}/mosaicjson/tilejson.json",
            params=kwargs,
        ).json()
    else:
        raise ValueError("titiler_endpoint must be a string.")

    return r["tiles"][0]

netcdf_tile_layer(filename, variables=None, palette=None, vmin=None, vmax=None, nodata=None, port='default', debug=False, projection='EPSG:3857', attribution=None, tile_format='ipyleaflet', layer_name='NetCDF layer', return_client=False, shift_lon=True, lat='lat', lon='lon', **kwargs)

Generate an ipyleaflet/folium TileLayer from a netCDF file. If you are using this function in JupyterHub on a remote server (e.g., Binder, Microsoft Planetary Computer), try adding to following two lines to the beginning of the notebook if the raster does not render properly.

1
2
import os
os.environ['LOCALTILESERVER_CLIENT_PREFIX'] = f'{os.environ['JUPYTERHUB_SERVICE_PREFIX'].lstrip('/')}/proxy/{{port}}'

Parameters:

Name Type Description Default
filename str

File path or HTTP URL to the netCDF file.

required
variables int

The variable/band names to extract data from the netCDF file. Defaults to None. If None, all variables will be extracted.

None
port str

The port to use for the server. Defaults to "default".

'default'
palette str

The name of the color palette from palettable to use when plotting a single band. See https://jiffyclub.github.io/palettable. Default is greyscale

None
vmin float

The minimum value to use when colormapping the palette when plotting a single band. Defaults to None.

None
vmax float

The maximum value to use when colormapping the palette when plotting a single band. Defaults to None.

None
nodata float

The value from the band to use to interpret as not valid data. Defaults to None.

None
debug bool

If True, the server will be started in debug mode. Defaults to False.

False
projection str

The projection of the GeoTIFF. Defaults to "EPSG:3857".

'EPSG:3857'
attribution str

Attribution for the source raster. This defaults to a message about it being a local file.. Defaults to None.

None
tile_format str

The tile layer format. Can be either ipyleaflet or folium. Defaults to "ipyleaflet".

'ipyleaflet'
layer_name str

The layer name to use. Defaults to "NetCDF layer".

'NetCDF layer'
return_client bool

If True, the tile client will be returned. Defaults to False.

False
shift_lon bool

Flag to shift longitude values from [0, 360] to the range [-180, 180]. Defaults to True.

True
lat str

Name of the latitude variable. Defaults to 'lat'.

'lat'
lon str

Name of the longitude variable. Defaults to 'lon'.

'lon'

Returns:

Type Description
ipyleaflet.TileLayer | folium.TileLayer

An ipyleaflet.TileLayer or folium.TileLayer.

Source code in leafmap/common.py
def netcdf_tile_layer(
    filename,
    variables=None,
    palette=None,
    vmin=None,
    vmax=None,
    nodata=None,
    port="default",
    debug=False,
    projection="EPSG:3857",
    attribution=None,
    tile_format="ipyleaflet",
    layer_name="NetCDF layer",
    return_client=False,
    shift_lon=True,
    lat="lat",
    lon="lon",
    **kwargs,
):
    """Generate an ipyleaflet/folium TileLayer from a netCDF file.
        If you are using this function in JupyterHub on a remote server (e.g., Binder, Microsoft Planetary Computer),
        try adding to following two lines to the beginning of the notebook if the raster does not render properly.

        import os
        os.environ['LOCALTILESERVER_CLIENT_PREFIX'] = f'{os.environ['JUPYTERHUB_SERVICE_PREFIX'].lstrip('/')}/proxy/{{port}}'

    Args:
        filename (str): File path or HTTP URL to the netCDF file.
        variables (int, optional): The variable/band names to extract data from the netCDF file. Defaults to None. If None, all variables will be extracted.
        port (str, optional): The port to use for the server. Defaults to "default".
        palette (str, optional): The name of the color palette from `palettable` to use when plotting a single band. See https://jiffyclub.github.io/palettable. Default is greyscale
        vmin (float, optional): The minimum value to use when colormapping the palette when plotting a single band. Defaults to None.
        vmax (float, optional): The maximum value to use when colormapping the palette when plotting a single band. Defaults to None.
        nodata (float, optional): The value from the band to use to interpret as not valid data. Defaults to None.
        debug (bool, optional): If True, the server will be started in debug mode. Defaults to False.
        projection (str, optional): The projection of the GeoTIFF. Defaults to "EPSG:3857".
        attribution (str, optional): Attribution for the source raster. This defaults to a message about it being a local file.. Defaults to None.
        tile_format (str, optional): The tile layer format. Can be either ipyleaflet or folium. Defaults to "ipyleaflet".
        layer_name (str, optional): The layer name to use. Defaults to "NetCDF layer".
        return_client (bool, optional): If True, the tile client will be returned. Defaults to False.
        shift_lon (bool, optional): Flag to shift longitude values from [0, 360] to the range [-180, 180]. Defaults to True.
        lat (str, optional): Name of the latitude variable. Defaults to 'lat'.
        lon (str, optional): Name of the longitude variable. Defaults to 'lon'.

    Returns:
        ipyleaflet.TileLayer | folium.TileLayer: An ipyleaflet.TileLayer or folium.TileLayer.
    """

    check_package(
        "localtileserver", URL="https://github.com/banesullivan/localtileserver"
    )

    try:
        import xarray as xr
    except ImportError as e:
        raise ImportError(e)

    if filename.startswith("http"):
        filename = download_file(filename)

    if not os.path.exists(filename):
        raise FileNotFoundError(f"{filename} does not exist.")

    output = filename.replace(".nc", ".tif")

    xds = xr.open_dataset(filename, **kwargs)

    if shift_lon:
        xds.coords[lon] = (xds.coords[lon] + 180) % 360 - 180
        xds = xds.sortby(xds.lon)

    allowed_vars = list(xds.data_vars.keys())
    if isinstance(variables, str):
        if variables not in allowed_vars:
            raise ValueError(f"{variables} is not a subset of {allowed_vars}.")
        variables = [variables]

    if variables is not None and len(variables) > 3:
        raise ValueError("Only 3 variables can be plotted at a time.")

    if variables is not None and (not set(variables).issubset(allowed_vars)):
        raise ValueError(f"{variables} must be a subset of {allowed_vars}.")

    xds.rio.set_spatial_dims(x_dim=lon, y_dim=lat).rio.to_raster(output)
    if variables is None:
        if len(allowed_vars) >= 3:
            band_idx = [1, 2, 3]
        else:
            band_idx = [1]
    else:
        band_idx = [allowed_vars.index(var) + 1 for var in variables]

    tile_layer = get_local_tile_layer(
        output,
        port=port,
        debug=debug,
        projection=projection,
        band=band_idx,
        palette=palette,
        vmin=vmin,
        vmax=vmax,
        nodata=nodata,
        attribution=attribution,
        tile_format=tile_format,
        layer_name=layer_name,
        return_client=return_client,
    )
    return tile_layer

netcdf_to_tif(filename, output=None, variables=None, shift_lon=True, lat='lat', lon='lon', lev='lev', level_index=0, time=0, return_vars=False, **kwargs)

Convert a netcdf file to a GeoTIFF file.

Parameters:

Name Type Description Default
filename str

Path to the netcdf file.

required
output str

Path to the output GeoTIFF file. Defaults to None. If None, the output file will be the same as the input file with the extension changed to .tif.

None
variables str | list

Name of the variable or a list of variables to extract. Defaults to None. If None, all variables will be extracted.

None
shift_lon bool

Flag to shift longitude values from [0, 360] to the range [-180, 180]. Defaults to True.

True
lat str

Name of the latitude variable. Defaults to 'lat'.

'lat'
lon str

Name of the longitude variable. Defaults to 'lon'.

'lon'
lev str

Name of the level variable. Defaults to 'lev'.

'lev'
level_index int

Index of the level dimension. Defaults to 0'.

0
time int

Index of the time dimension. Defaults to 0'.

0
return_vars bool

Flag to return all variables. Defaults to False.

False

Exceptions:

Type Description
ImportError

If the xarray or rioxarray package is not installed.

FileNotFoundError

If the netcdf file is not found.

ValueError

If the variable is not found in the netcdf file.

Source code in leafmap/common.py
def netcdf_to_tif(
    filename,
    output=None,
    variables=None,
    shift_lon=True,
    lat="lat",
    lon="lon",
    lev="lev",
    level_index=0,
    time=0,
    return_vars=False,
    **kwargs,
):
    """Convert a netcdf file to a GeoTIFF file.

    Args:
        filename (str): Path to the netcdf file.
        output (str, optional): Path to the output GeoTIFF file. Defaults to None. If None, the output file will be the same as the input file with the extension changed to .tif.
        variables (str | list, optional): Name of the variable or a list of variables to extract. Defaults to None. If None, all variables will be extracted.
        shift_lon (bool, optional): Flag to shift longitude values from [0, 360] to the range [-180, 180]. Defaults to True.
        lat (str, optional): Name of the latitude variable. Defaults to 'lat'.
        lon (str, optional): Name of the longitude variable. Defaults to 'lon'.
        lev (str, optional): Name of the level variable. Defaults to 'lev'.
        level_index (int, optional): Index of the level dimension. Defaults to 0'.
        time (int, optional): Index of the time dimension. Defaults to 0'.
        return_vars (bool, optional): Flag to return all variables. Defaults to False.

    Raises:
        ImportError: If the xarray or rioxarray package is not installed.
        FileNotFoundError: If the netcdf file is not found.
        ValueError: If the variable is not found in the netcdf file.
    """
    try:
        import xarray as xr
    except ImportError as e:
        raise ImportError(e)

    if filename.startswith("http"):
        filename = download_file(filename)

    if not os.path.exists(filename):
        raise FileNotFoundError(f"{filename} does not exist.")

    if output is None:
        ext = os.path.splitext(filename)[1].lower()
        if ext not in [".nc", ".nc4"]:
            raise TypeError(
                "The output file must be a netCDF with extension .nc or .nc4."
            )
        output = filename.replace(ext, ".tif")
    else:
        output = check_file_path(output)

    xds = xr.open_dataset(filename, **kwargs)

    coords = list(xds.coords.keys())
    if "time" in coords:
        xds = xds.isel(time=time, drop=True)

    if lev in coords:
        xds = xds.isel(lev=level_index, drop=True)

    if shift_lon:
        xds.coords[lon] = (xds.coords[lon] + 180) % 360 - 180
        xds = xds.sortby(xds.lon)

    allowed_vars = list(xds.data_vars.keys())
    if isinstance(variables, str):
        if variables not in allowed_vars:
            raise ValueError(f"{variables} is not a valid variable.")
        variables = [variables]

    if variables is not None and (not set(variables).issubset(allowed_vars)):
        raise ValueError(f"{variables} must be a subset of {allowed_vars}.")

    if variables is None:
        xds.rio.set_spatial_dims(x_dim=lon, y_dim=lat).rio.to_raster(output)
    else:
        xds[variables].rio.set_spatial_dims(x_dim=lon, y_dim=lat).rio.to_raster(output)

    if return_vars:
        return output, allowed_vars
    else:
        return output

numpy_to_cog(np_array, out_cog, bounds=None, profile=None, dtype=None, crs='epsg:4326')

Converts a numpy array to a COG file.

Parameters:

Name Type Description Default
np_array np.array

A numpy array representing the image.

required
out_cog str

The output COG file path.

required
bounds tuple

The bounds of the image in the format of (minx, miny, maxx, maxy). Defaults to None.

None
profile str | dict

File path to an existing COG file or a dictionary representing the profile. Defaults to None.

None
dtype str

The data type of the output COG file. Defaults to None.

None
crs str

The coordinate reference system of the output COG file. Defaults to "epsg:4326".

'epsg:4326'
Source code in leafmap/common.py
def numpy_to_cog(
    np_array, out_cog, bounds=None, profile=None, dtype=None, crs="epsg:4326"
):
    """Converts a numpy array to a COG file.

    Args:
        np_array (np.array): A numpy array representing the image.
        out_cog (str): The output COG file path.
        bounds (tuple, optional): The bounds of the image in the format of (minx, miny, maxx, maxy). Defaults to None.
        profile (str | dict, optional): File path to an existing COG file or a dictionary representing the profile. Defaults to None.
        dtype (str, optional): The data type of the output COG file. Defaults to None.
        crs (str, optional): The coordinate reference system of the output COG file. Defaults to "epsg:4326".

    """
    import warnings
    import numpy as np
    import rasterio
    from rasterio.io import MemoryFile
    from rasterio.transform import from_bounds

    from rio_cogeo.cogeo import cog_translate
    from rio_cogeo.profiles import cog_profiles

    warnings.filterwarnings("ignore")
    if not isinstance(np_array, np.ndarray):
        raise TypeError("The input array must be a numpy array.")

    out_dir = os.path.dirname(out_cog)
    check_dir(out_dir)

    if profile is not None:
        if isinstance(profile, str):
            if not os.path.exists(profile):
                raise FileNotFoundError("The provided file could not be found.")
            with rasterio.open(profile) as ds:
                bounds = ds.bounds
        elif isinstance(profile, rasterio.profiles.Profile):
            profile = dict(profile)
        elif not isinstance(profile, dict):
            raise TypeError("The provided profile must be a file path or a dictionary.")

    if bounds is None:
        bounds = (-180.0, -85.0511287798066, 180.0, 85.0511287798066)

    if not isinstance(bounds, tuple) and len(bounds) != 4:
        raise TypeError("The provided bounds must be a tuple of length 4.")

    # Rasterio uses numpy array of shape of `(bands, height, width)`

    if len(np_array.shape) == 3:
        nbands = np_array.shape[0]
        height = np_array.shape[1]
        width = np_array.shape[2]
    elif len(np_array.shape) == 2:
        nbands = 1
        height = np_array.shape[0]
        width = np_array.shape[1]
        np_array = np_array.reshape((1, height, width))
    else:
        raise ValueError("The input array must be a 2D or 3D numpy array.")

    src_transform = from_bounds(*bounds, width=width, height=height)
    if dtype is None:
        dtype = str(np_array.dtype)

    if isinstance(profile, dict):
        src_profile = profile
        src_profile["count"] = nbands
    else:
        src_profile = dict(
            driver="GTiff",
            dtype=dtype,
            count=nbands,
            height=height,
            width=width,
            crs=crs,
            transform=src_transform,
        )

    with MemoryFile() as memfile:
        with memfile.open(**src_profile) as mem:
            # Populate the input file with numpy array
            mem.write(np_array)

            dst_profile = cog_profiles.get("deflate")
            cog_translate(
                mem,
                out_cog,
                dst_profile,
                in_memory=True,
                quiet=True,
            )

open_image_from_url(url)

Loads an image from the specified URL.

Parameters:

Name Type Description Default
url str

URL of the image.

required

Returns:

Type Description
object

Image object.

Source code in leafmap/common.py
def open_image_from_url(url):
    """Loads an image from the specified URL.

    Args:
        url (str): URL of the image.

    Returns:
        object: Image object.
    """
    from PIL import Image

    from io import BytesIO

    # from urllib.parse import urlparse

    try:
        response = requests.get(url)
        img = Image.open(BytesIO(response.content))
        return img
    except Exception as e:
        print(e)

pandas_to_geojson(df, out_geojson=None, latitude='latitude', longitude='longitude', encoding='utf-8')

Creates points for a Pandas DataFrame and exports data as a GeoJSON.

Parameters:

Name Type Description Default
df pandas.DataFrame

The input Pandas DataFrame.

required
out_geojson str

The file path to the exported GeoJSON. Default to None.

None
latitude str

The name of the column containing latitude coordinates. Defaults to "latitude".

'latitude'
longitude str

The name of the column containing longitude coordinates. Defaults to "longitude".

'longitude'
encoding str

The encoding of characters. Defaults to "utf-8".

'utf-8'
Source code in leafmap/common.py
def pandas_to_geojson(
    df,
    out_geojson=None,
    latitude="latitude",
    longitude="longitude",
    encoding="utf-8",
):
    """Creates points for a Pandas DataFrame and exports data as a GeoJSON.

    Args:
        df (pandas.DataFrame): The input Pandas DataFrame.
        out_geojson (str): The file path to the exported GeoJSON. Default to None.
        latitude (str, optional): The name of the column containing latitude coordinates. Defaults to "latitude".
        longitude (str, optional): The name of the column containing longitude coordinates. Defaults to "longitude".
        encoding (str, optional): The encoding of characters. Defaults to "utf-8".

    """

    import json
    from geojson import Feature, FeatureCollection, Point

    if out_geojson is not None:
        out_dir = os.path.dirname(os.path.abspath(out_geojson))
        if not os.path.exists(out_dir):
            os.makedirs(out_dir)

    features = df.apply(
        lambda row: Feature(
            geometry=Point((float(row[longitude]), float(row[latitude]))),
            properties=dict(row),
        ),
        axis=1,
    ).tolist()

    geojson = FeatureCollection(features=features)

    if out_geojson is None:
        return geojson
    else:
        with open(out_geojson, "w", encoding=encoding) as f:
            f.write(json.dumps(geojson))

planet_biannual_tiles_tropical(api_key=None, token_name='PLANET_API_KEY', tile_format='ipyleaflet')

Generates Planet bi-annual imagery TileLayer based on an API key. See https://assets.planet.com/docs/NICFI_UserGuidesFAQ.pdf

Parameters:

Name Type Description Default
api_key str

The Planet API key. Defaults to None.

None
token_name str

The environment variable name of the API key. Defaults to "PLANET_API_KEY".

'PLANET_API_KEY'
tile_format str

The TileLayer format, can be either ipyleaflet or folium. Defaults to "ipyleaflet".

'ipyleaflet'

Exceptions:

Type Description
ValueError

If the tile layer format is invalid.

Returns:

Type Description
dict

A dictionary of TileLayer.

Source code in leafmap/common.py
def planet_biannual_tiles_tropical(
    api_key=None, token_name="PLANET_API_KEY", tile_format="ipyleaflet"
):
    """Generates Planet  bi-annual imagery TileLayer based on an API key. See https://assets.planet.com/docs/NICFI_UserGuidesFAQ.pdf

    Args:
        api_key (str, optional): The Planet API key. Defaults to None.
        token_name (str, optional): The environment variable name of the API key. Defaults to "PLANET_API_KEY".
        tile_format (str, optional): The TileLayer format, can be either ipyleaflet or folium. Defaults to "ipyleaflet".

    Raises:
        ValueError: If the tile layer format is invalid.

    Returns:
        dict: A dictionary of TileLayer.
    """

    if tile_format not in ["ipyleaflet", "folium"]:
        raise ValueError("The tile format must be either ipyleaflet or folium.")

    tiles = {}
    link = planet_biannual_tropical(api_key, token_name)
    for url in link:
        index = url.find("20")
        name = "Planet_" + url[index : index + 15]
        if tile_format == "ipyleaflet":
            tile = ipyleaflet.TileLayer(url=url, attribution="Planet", name=name)
        else:
            tile = folium.TileLayer(
                tiles=url,
                attr="Planet",
                name=name,
                overlay=True,
                control=True,
            )
        tiles[name] = tile

    return tiles

planet_biannual_tropical(api_key=None, token_name='PLANET_API_KEY')

Generates Planet bi-annual imagery URLs based on an API key. See https://assets.planet.com/docs/NICFI_UserGuidesFAQ.pdf

Parameters:

Name Type Description Default
api_key str

The Planet API key. Defaults to None.

None
token_name str

The environment variable name of the API key. Defaults to "PLANET_API_KEY".

'PLANET_API_KEY'

Exceptions:

Type Description
ValueError

If the API key could not be found.

Returns:

Type Description
list

A list of tile URLs.

Source code in leafmap/common.py
def planet_biannual_tropical(api_key=None, token_name="PLANET_API_KEY"):
    """Generates Planet bi-annual imagery URLs based on an API key. See https://assets.planet.com/docs/NICFI_UserGuidesFAQ.pdf

    Args:
        api_key (str, optional): The Planet API key. Defaults to None.
        token_name (str, optional): The environment variable name of the API key. Defaults to "PLANET_API_KEY".

    Raises:
        ValueError: If the API key could not be found.

    Returns:
        list: A list of tile URLs.
    """

    if api_key is None:
        api_key = os.environ.get(token_name)
        if api_key is None:
            raise ValueError("The Planet API Key must be provided.")

    dates = [
        "2015-12_2016-05",
        "2016-06_2016-11",
        "2016-12_2017-05",
        "2017-06_2017-11",
        "2017-12_2018-05",
        "2018-06_2018-11",
        "2018-12_2019-05",
        "2019-06_2019-11",
        "2019-12_2020-05",
        "2020-06_2020-08",
    ]

    link = []
    prefix = "https://tiles.planet.com/basemaps/v1/planet-tiles/planet_medres_normalized_analytic_"
    subfix = "_mosaic/gmap/{z}/{x}/{y}.png?api_key="

    for d in dates:
        url = f"{prefix}{d}{subfix}{api_key}"
        link.append(url)

    return link

planet_by_month(year=2016, month=1, api_key=None, token_name='PLANET_API_KEY')

Gets Planet global mosaic tile url by month. To get a Planet API key, see https://developers.planet.com/quickstart/apis/

Parameters:

Name Type Description Default
year int

The year of Planet global mosaic, must be >=2016. Defaults to 2016.

2016
month int

The month of Planet global mosaic, must be 1-12. Defaults to 1.

1
api_key str

The Planet API key. Defaults to None.

None
token_name str

The environment variable name of the API key. Defaults to "PLANET_API_KEY".

'PLANET_API_KEY'

Exceptions:

Type Description
ValueError

The Planet API key is not provided.

ValueError

The year is invalid.

ValueError

The month is invalid.

ValueError

The month is invalid.

Returns:

Type Description
str

A Planet global mosaic tile url.

Source code in leafmap/common.py
def planet_by_month(
    year=2016,
    month=1,
    api_key=None,
    token_name="PLANET_API_KEY",
):
    """Gets Planet global mosaic tile url by month. To get a Planet API key, see https://developers.planet.com/quickstart/apis/

    Args:
        year (int, optional): The year of Planet global mosaic, must be >=2016. Defaults to 2016.
        month (int, optional): The month of Planet global mosaic, must be 1-12. Defaults to 1.
        api_key (str, optional): The Planet API key. Defaults to None.
        token_name (str, optional): The environment variable name of the API key. Defaults to "PLANET_API_KEY".

    Raises:
        ValueError: The Planet API key is not provided.
        ValueError: The year is invalid.
        ValueError: The month is invalid.
        ValueError: The month is invalid.

    Returns:
        str: A Planet global mosaic tile url.
    """
    from datetime import date

    if api_key is None:
        api_key = os.environ.get(token_name)
        if api_key is None:
            raise ValueError("The Planet API Key must be provided.")

    today = date.today()
    year_now = int(today.strftime("%Y"))
    month_now = int(today.strftime("%m"))
    # quarter_now = (month_now - 1) // 3 + 1

    if year > year_now:
        raise ValueError(f"Year must be between 2016 and {year_now}.")
    elif year == year_now and month >= month_now:
        raise ValueError(f"Month must be less than {month_now} for year {year_now}")

    if month < 1 or month > 12:
        raise ValueError("Month must be between 1 and 12.")

    prefix = "https://tiles.planet.com/basemaps/v1/planet-tiles/global_monthly_"
    subfix = "_mosaic/gmap/{z}/{x}/{y}.png?api_key="

    m_str = str(year) + "_" + str(month).zfill(2)
    url = f"{prefix}{m_str}{subfix}{api_key}"

    return url

planet_by_quarter(year=2016, quarter=1, api_key=None, token_name='PLANET_API_KEY')

Gets Planet global mosaic tile url by quarter. To get a Planet API key, see https://developers.planet.com/quickstart/apis/

Parameters:

Name Type Description Default
year int

The year of Planet global mosaic, must be >=2016. Defaults to 2016.

2016
quarter int

The quarter of Planet global mosaic, must be 1-4. Defaults to 1.

1
api_key str

The Planet API key. Defaults to None.

None
token_name str

The environment variable name of the API key. Defaults to "PLANET_API_KEY".

'PLANET_API_KEY'

Exceptions:

Type Description
ValueError

The Planet API key is not provided.

ValueError

The year is invalid.

ValueError

The quarter is invalid.

ValueError

The quarter is invalid.

Returns:

Type Description
str

A Planet global mosaic tile url.

Source code in leafmap/common.py
def planet_by_quarter(
    year=2016,
    quarter=1,
    api_key=None,
    token_name="PLANET_API_KEY",
):
    """Gets Planet global mosaic tile url by quarter. To get a Planet API key, see https://developers.planet.com/quickstart/apis/

    Args:
        year (int, optional): The year of Planet global mosaic, must be >=2016. Defaults to 2016.
        quarter (int, optional): The quarter of Planet global mosaic, must be 1-4. Defaults to 1.
        api_key (str, optional): The Planet API key. Defaults to None.
        token_name (str, optional): The environment variable name of the API key. Defaults to "PLANET_API_KEY".

    Raises:
        ValueError: The Planet API key is not provided.
        ValueError: The year is invalid.
        ValueError: The quarter is invalid.
        ValueError: The quarter is invalid.

    Returns:
        str: A Planet global mosaic tile url.
    """
    from datetime import date

    if api_key is None:
        api_key = os.environ.get(token_name)
        if api_key is None:
            raise ValueError("The Planet API Key must be provided.")

    today = date.today()
    year_now = int(today.strftime("%Y"))
    month_now = int(today.strftime("%m"))
    quarter_now = (month_now - 1) // 3 + 1

    if year > year_now:
        raise ValueError(f"Year must be between 2016 and {year_now}.")
    elif year == year_now and quarter >= quarter_now:
        raise ValueError(f"Quarter must be less than {quarter_now} for year {year_now}")

    if quarter < 1 or quarter > 4:
        raise ValueError("Quarter must be between 1 and 4.")

    prefix = "https://tiles.planet.com/basemaps/v1/planet-tiles/global_quarterly_"
    subfix = "_mosaic/gmap/{z}/{x}/{y}.png?api_key="

    m_str = str(year) + "q" + str(quarter)
    url = f"{prefix}{m_str}{subfix}{api_key}"

    return url

planet_catalog(api_key=None, token_name='PLANET_API_KEY')

Generates Planet bi-annual and monthly imagery URLs based on an API key. See https://assets.planet.com/docs/NICFI_UserGuidesFAQ.pdf

Parameters:

Name Type Description Default
api_key str

The Planet API key. Defaults to None.

None
token_name str

The environment variable name of the API key. Defaults to "PLANET_API_KEY".

'PLANET_API_KEY'

Returns:

Type Description
list

A list of tile URLs.

Source code in leafmap/common.py
def planet_catalog(api_key=None, token_name="PLANET_API_KEY"):
    """Generates Planet bi-annual and monthly imagery URLs based on an API key. See https://assets.planet.com/docs/NICFI_UserGuidesFAQ.pdf

    Args:
        api_key (str, optional): The Planet API key. Defaults to None.
        token_name (str, optional): The environment variable name of the API key. Defaults to "PLANET_API_KEY".

    Returns:
        list: A list of tile URLs.
    """
    quarterly = planet_quarterly(api_key, token_name)
    monthly = planet_monthly(api_key, token_name)
    return quarterly + monthly

planet_catalog_tropical(api_key=None, token_name='PLANET_API_KEY')

Generates Planet bi-annual and monthly imagery URLs based on an API key. See https://assets.planet.com/docs/NICFI_UserGuidesFAQ.pdf

Parameters:

Name Type Description Default
api_key str

The Planet API key. Defaults to None.

None
token_name str

The environment variable name of the API key. Defaults to "PLANET_API_KEY".

'PLANET_API_KEY'

Returns:

Type Description
list

A list of tile URLs.

Source code in leafmap/common.py
def planet_catalog_tropical(api_key=None, token_name="PLANET_API_KEY"):
    """Generates Planet bi-annual and monthly imagery URLs based on an API key. See https://assets.planet.com/docs/NICFI_UserGuidesFAQ.pdf

    Args:
        api_key (str, optional): The Planet API key. Defaults to None.
        token_name (str, optional): The environment variable name of the API key. Defaults to "PLANET_API_KEY".

    Returns:
        list: A list of tile URLs.
    """
    biannual = planet_biannual_tropical(api_key, token_name)
    monthly = planet_monthly_tropical(api_key, token_name)
    return biannual + monthly

planet_monthly(api_key=None, token_name='PLANET_API_KEY')

Generates Planet monthly imagery URLs based on an API key. To get a Planet API key, see https://developers.planet.com/quickstart/apis/

Parameters:

Name Type Description Default
api_key str

The Planet API key. Defaults to None.

None
token_name str

The environment variable name of the API key. Defaults to "PLANET_API_KEY".

'PLANET_API_KEY'

Exceptions:

Type Description
ValueError

If the API key could not be found.

Returns:

Type Description
list

A list of tile URLs.

Source code in leafmap/common.py
def planet_monthly(api_key=None, token_name="PLANET_API_KEY"):
    """Generates Planet monthly imagery URLs based on an API key. To get a Planet API key, see https://developers.planet.com/quickstart/apis/

    Args:
        api_key (str, optional): The Planet API key. Defaults to None.
        token_name (str, optional): The environment variable name of the API key. Defaults to "PLANET_API_KEY".

    Raises:
        ValueError: If the API key could not be found.

    Returns:
        list: A list of tile URLs.
    """
    from datetime import date

    if api_key is None:
        api_key = os.environ.get(token_name)
        if api_key is None:
            raise ValueError("The Planet API Key must be provided.")

    today = date.today()
    year_now = int(today.strftime("%Y"))
    month_now = int(today.strftime("%m"))

    link = []
    prefix = "https://tiles.planet.com/basemaps/v1/planet-tiles/global_monthly_"
    subfix = "_mosaic/gmap/{z}/{x}/{y}.png?api_key="

    for year in range(2016, year_now + 1):

        for month in range(1, 13):
            m_str = str(year) + "_" + str(month).zfill(2)

            if year == year_now and month >= month_now:
                break

            url = f"{prefix}{m_str}{subfix}{api_key}"
            link.append(url)

    return link

planet_monthly_tiles(api_key=None, token_name='PLANET_API_KEY', tile_format='ipyleaflet')

Generates Planet monthly imagery TileLayer based on an API key. To get a Planet API key, see https://developers.planet.com/quickstart/apis/

Parameters:

Name Type Description Default
api_key str

The Planet API key. Defaults to None.

None
token_name str

The environment variable name of the API key. Defaults to "PLANET_API_KEY".

'PLANET_API_KEY'
tile_format str

The TileLayer format, can be either ipyleaflet or folium. Defaults to "ipyleaflet".

'ipyleaflet'

Exceptions:

Type Description
ValueError

If the tile layer format is invalid.

Returns:

Type Description
dict

A dictionary of TileLayer.

Source code in leafmap/common.py
def planet_monthly_tiles(
    api_key=None, token_name="PLANET_API_KEY", tile_format="ipyleaflet"
):
    """Generates Planet monthly imagery TileLayer based on an API key. To get a Planet API key, see https://developers.planet.com/quickstart/apis/

    Args:
        api_key (str, optional): The Planet API key. Defaults to None.
        token_name (str, optional): The environment variable name of the API key. Defaults to "PLANET_API_KEY".
        tile_format (str, optional): The TileLayer format, can be either ipyleaflet or folium. Defaults to "ipyleaflet".

    Raises:
        ValueError: If the tile layer format is invalid.

    Returns:
        dict: A dictionary of TileLayer.
    """

    if tile_format not in ["ipyleaflet", "folium"]:
        raise ValueError("The tile format must be either ipyleaflet or folium.")

    tiles = {}
    link = planet_monthly(api_key, token_name)

    for url in link:
        index = url.find("20")
        name = "Planet_" + url[index : index + 7]

        if tile_format == "ipyleaflet":
            tile = ipyleaflet.TileLayer(url=url, attribution="Planet", name=name)
        else:
            tile = folium.TileLayer(
                tiles=url,
                attr="Planet",
                name=name,
                overlay=True,
                control=True,
            )

        tiles[name] = tile

    return tiles

planet_monthly_tiles_tropical(api_key=None, token_name='PLANET_API_KEY', tile_format='ipyleaflet')

Generates Planet monthly imagery TileLayer based on an API key. See https://assets.planet.com/docs/NICFI_UserGuidesFAQ.pdf

Parameters:

Name Type Description Default
api_key str

The Planet API key. Defaults to None.

None
token_name str

The environment variable name of the API key. Defaults to "PLANET_API_KEY".

'PLANET_API_KEY'
tile_format str

The TileLayer format, can be either ipyleaflet or folium. Defaults to "ipyleaflet".

'ipyleaflet'

Exceptions:

Type Description
ValueError

If the tile layer format is invalid.

Returns:

Type Description
dict

A dictionary of TileLayer.

Source code in leafmap/common.py
def planet_monthly_tiles_tropical(
    api_key=None, token_name="PLANET_API_KEY", tile_format="ipyleaflet"
):
    """Generates Planet  monthly imagery TileLayer based on an API key. See https://assets.planet.com/docs/NICFI_UserGuidesFAQ.pdf

    Args:
        api_key (str, optional): The Planet API key. Defaults to None.
        token_name (str, optional): The environment variable name of the API key. Defaults to "PLANET_API_KEY".
        tile_format (str, optional): The TileLayer format, can be either ipyleaflet or folium. Defaults to "ipyleaflet".

    Raises:
        ValueError: If the tile layer format is invalid.

    Returns:
        dict: A dictionary of TileLayer.
    """

    if tile_format not in ["ipyleaflet", "folium"]:
        raise ValueError("The tile format must be either ipyleaflet or folium.")

    tiles = {}
    link = planet_monthly_tropical(api_key, token_name)
    for url in link:
        index = url.find("20")
        name = "Planet_" + url[index : index + 7]

        if tile_format == "ipyleaflet":
            tile = ipyleaflet.TileLayer(url=url, attribution="Planet", name=name)
        else:
            tile = folium.TileLayer(
                tiles=url,
                attr="Planet",
                name=name,
                overlay=True,
                control=True,
            )

        tiles[name] = tile

    return tiles

planet_monthly_tropical(api_key=None, token_name='PLANET_API_KEY')

Generates Planet monthly imagery URLs based on an API key. See https://assets.planet.com/docs/NICFI_UserGuidesFAQ.pdf

Parameters:

Name Type Description Default
api_key str

The Planet API key. Defaults to None.

None
token_name str

The environment variable name of the API key. Defaults to "PLANET_API_KEY".

'PLANET_API_KEY'

Exceptions:

Type Description
ValueError

If the API key could not be found.

Returns:

Type Description
list

A list of tile URLs.

Source code in leafmap/common.py
def planet_monthly_tropical(api_key=None, token_name="PLANET_API_KEY"):
    """Generates Planet monthly imagery URLs based on an API key. See https://assets.planet.com/docs/NICFI_UserGuidesFAQ.pdf

    Args:
        api_key (str, optional): The Planet API key. Defaults to None.
        token_name (str, optional): The environment variable name of the API key. Defaults to "PLANET_API_KEY".

    Raises:
        ValueError: If the API key could not be found.

    Returns:
        list: A list of tile URLs.
    """
    from datetime import date

    if api_key is None:
        api_key = os.environ.get(token_name)
        if api_key is None:
            raise ValueError("The Planet API Key must be provided.")

    today = date.today()
    year_now = int(today.strftime("%Y"))
    month_now = int(today.strftime("%m"))

    links = []
    prefix = "https://tiles.planet.com/basemaps/v1/planet-tiles/planet_medres_normalized_analytic_"
    subfix = "_mosaic/gmap/{z}/{x}/{y}.png?api_key="

    for year in range(2020, year_now + 1):

        for month in range(1, 13):
            m_str = str(year) + "-" + str(month).zfill(2)

            if year == 2020 and month < 9:
                continue
            if year == year_now and month >= month_now:
                break

            url = f"{prefix}{m_str}{subfix}{api_key}"
            links.append(url)

    return links

planet_quarterly(api_key=None, token_name='PLANET_API_KEY')

Generates Planet quarterly imagery URLs based on an API key. To get a Planet API key, see https://developers.planet.com/quickstart/apis/

Parameters:

Name Type Description Default
api_key str

The Planet API key. Defaults to None.

None
token_name str

The environment variable name of the API key. Defaults to "PLANET_API_KEY".

'PLANET_API_KEY'

Exceptions:

Type Description
ValueError

If the API key could not be found.

Returns:

Type Description
list

A list of tile URLs.

Source code in leafmap/common.py
def planet_quarterly(api_key=None, token_name="PLANET_API_KEY"):
    """Generates Planet quarterly imagery URLs based on an API key. To get a Planet API key, see https://developers.planet.com/quickstart/apis/

    Args:
        api_key (str, optional): The Planet API key. Defaults to None.
        token_name (str, optional): The environment variable name of the API key. Defaults to "PLANET_API_KEY".

    Raises:
        ValueError: If the API key could not be found.

    Returns:
        list: A list of tile URLs.
    """
    from datetime import date

    if api_key is None:
        api_key = os.environ.get(token_name)
        if api_key is None:
            raise ValueError("The Planet API Key must be provided.")

    today = date.today()
    year_now = int(today.strftime("%Y"))
    month_now = int(today.strftime("%m"))
    quarter_now = (month_now - 1) // 3 + 1

    link = []
    prefix = "https://tiles.planet.com/basemaps/v1/planet-tiles/global_quarterly_"
    subfix = "_mosaic/gmap/{z}/{x}/{y}.png?api_key="

    for year in range(2016, year_now + 1):

        for quarter in range(1, 5):
            m_str = str(year) + "q" + str(quarter)

            if year == year_now and quarter >= quarter_now:
                break

            url = f"{prefix}{m_str}{subfix}{api_key}"
            link.append(url)

    return link

planet_quarterly_tiles(api_key=None, token_name='PLANET_API_KEY', tile_format='ipyleaflet')

Generates Planet quarterly imagery TileLayer based on an API key. To get a Planet API key, see https://developers.planet.com/quickstart/apis/

Parameters:

Name Type Description Default
api_key str

The Planet API key. Defaults to None.

None
token_name str

The environment variable name of the API key. Defaults to "PLANET_API_KEY".

'PLANET_API_KEY'
tile_format str

The TileLayer format, can be either ipyleaflet or folium. Defaults to "ipyleaflet".

'ipyleaflet'

Exceptions:

Type Description
ValueError

If the tile layer format is invalid.

Returns:

Type Description
dict

A dictionary of TileLayer.

Source code in leafmap/common.py
def planet_quarterly_tiles(
    api_key=None, token_name="PLANET_API_KEY", tile_format="ipyleaflet"
):
    """Generates Planet  quarterly imagery TileLayer based on an API key. To get a Planet API key, see https://developers.planet.com/quickstart/apis/

    Args:
        api_key (str, optional): The Planet API key. Defaults to None.
        token_name (str, optional): The environment variable name of the API key. Defaults to "PLANET_API_KEY".
        tile_format (str, optional): The TileLayer format, can be either ipyleaflet or folium. Defaults to "ipyleaflet".

    Raises:
        ValueError: If the tile layer format is invalid.

    Returns:
        dict: A dictionary of TileLayer.
    """

    if tile_format not in ["ipyleaflet", "folium"]:
        raise ValueError("The tile format must be either ipyleaflet or folium.")

    tiles = {}
    links = planet_quarterly(api_key, token_name)

    for url in links:
        index = url.find("20")
        name = "Planet_" + url[index : index + 6]

        if tile_format == "ipyleaflet":
            tile = ipyleaflet.TileLayer(url=url, attribution="Planet", name=name)
        else:
            tile = folium.TileLayer(
                tiles=url,
                attr="Planet",
                name=name,
                overlay=True,
                control=True,
            )

        tiles[name] = tile

    return tiles

planet_tile_by_month(year=2016, month=1, name=None, api_key=None, token_name='PLANET_API_KEY', tile_format='ipyleaflet')

Generates Planet monthly imagery TileLayer based on an API key. To get a Planet API key, see https://developers.planet.com/quickstart/apis

Parameters:

Name Type Description Default
year int

The year of Planet global mosaic, must be >=2016. Defaults to 2016.

2016
month int

The month of Planet global mosaic, must be 1-12. Defaults to 1.

1
name str

The layer name to use. Defaults to None.

None
api_key str

The Planet API key. Defaults to None.

None
token_name str

The environment variable name of the API key. Defaults to "PLANET_API_KEY".

'PLANET_API_KEY'
tile_format str

The TileLayer format, can be either ipyleaflet or folium. Defaults to "ipyleaflet".

'ipyleaflet'

Exceptions:

Type Description
ValueError

If the tile layer format is invalid.

Returns:

Type Description
dict

A dictionary of TileLayer.

Source code in leafmap/common.py
def planet_tile_by_month(
    year=2016,
    month=1,
    name=None,
    api_key=None,
    token_name="PLANET_API_KEY",
    tile_format="ipyleaflet",
):
    """Generates Planet monthly imagery TileLayer based on an API key. To get a Planet API key, see https://developers.planet.com/quickstart/apis

    Args:
        year (int, optional): The year of Planet global mosaic, must be >=2016. Defaults to 2016.
        month (int, optional): The month of Planet global mosaic, must be 1-12. Defaults to 1.
        name (str, optional): The layer name to use. Defaults to None.
        api_key (str, optional): The Planet API key. Defaults to None.
        token_name (str, optional): The environment variable name of the API key. Defaults to "PLANET_API_KEY".
        tile_format (str, optional): The TileLayer format, can be either ipyleaflet or folium. Defaults to "ipyleaflet".

    Raises:
        ValueError: If the tile layer format is invalid.

    Returns:
        dict: A dictionary of TileLayer.
    """

    if tile_format not in ["ipyleaflet", "folium"]:
        raise ValueError("The tile format must be either ipyleaflet or folium.")

    url = planet_by_month(year, month, api_key, token_name)

    if name is None:
        name = "Planet_" + str(year) + "_" + str(month).zfill(2)

    if tile_format == "ipyleaflet":
        tile = ipyleaflet.TileLayer(url=url, attribution="Planet", name=name)
    else:
        tile = folium.TileLayer(
            tiles=url,
            attr="Planet",
            name=name,
            overlay=True,
            control=True,
        )

    return tile

planet_tile_by_quarter(year=2016, quarter=1, name=None, api_key=None, token_name='PLANET_API_KEY', tile_format='ipyleaflet')

Generates Planet quarterly imagery TileLayer based on an API key. To get a Planet API key, see https://developers.planet.com/quickstart/apis

Parameters:

Name Type Description Default
year int

The year of Planet global mosaic, must be >=2016. Defaults to 2016.

2016
quarter int

The quarter of Planet global mosaic, must be 1-4. Defaults to 1.

1
name str

The layer name to use. Defaults to None.

None
api_key str

The Planet API key. Defaults to None.

None
token_name str

The environment variable name of the API key. Defaults to "PLANET_API_KEY".

'PLANET_API_KEY'
tile_format str

The TileLayer format, can be either ipyleaflet or folium. Defaults to "ipyleaflet".

'ipyleaflet'

Exceptions:

Type Description
ValueError

If the tile layer format is invalid.

Returns:

Type Description
dict

A dictionary of TileLayer.

Source code in leafmap/common.py
def planet_tile_by_quarter(
    year=2016,
    quarter=1,
    name=None,
    api_key=None,
    token_name="PLANET_API_KEY",
    tile_format="ipyleaflet",
):
    """Generates Planet quarterly imagery TileLayer based on an API key. To get a Planet API key, see https://developers.planet.com/quickstart/apis

    Args:
        year (int, optional): The year of Planet global mosaic, must be >=2016. Defaults to 2016.
        quarter (int, optional): The quarter of Planet global mosaic, must be 1-4. Defaults to 1.
        name (str, optional): The layer name to use. Defaults to None.
        api_key (str, optional): The Planet API key. Defaults to None.
        token_name (str, optional): The environment variable name of the API key. Defaults to "PLANET_API_KEY".
        tile_format (str, optional): The TileLayer format, can be either ipyleaflet or folium. Defaults to "ipyleaflet".

    Raises:
        ValueError: If the tile layer format is invalid.

    Returns:
        dict: A dictionary of TileLayer.
    """

    if tile_format not in ["ipyleaflet", "folium"]:
        raise ValueError("The tile format must be either ipyleaflet or folium.")

    url = planet_by_quarter(year, quarter, api_key, token_name)

    if name is None:
        name = "Planet_" + str(year) + "_q" + str(quarter)

    if tile_format == "ipyleaflet":
        tile = ipyleaflet.TileLayer(url=url, attribution="Planet", name=name)
    else:
        tile = folium.TileLayer(
            tiles=url,
            attr="Planet",
            name=name,
            overlay=True,
            control=True,
        )

    return tile

planet_tiles(api_key=None, token_name='PLANET_API_KEY', tile_format='ipyleaflet')

Generates Planet imagery TileLayer based on an API key. To get a Planet API key, see https://developers.planet.com/quickstart/apis/

Parameters:

Name Type Description Default
api_key str

The Planet API key. Defaults to None.

None
token_name str

The environment variable name of the API key. Defaults to "PLANET_API_KEY".

'PLANET_API_KEY'
tile_format str

The TileLayer format, can be either ipyleaflet or folium. Defaults to "ipyleaflet".

'ipyleaflet'

Exceptions:

Type Description
ValueError

If the tile layer format is invalid.

Returns:

Type Description
dict

A dictionary of TileLayer.

Source code in leafmap/common.py
def planet_tiles(api_key=None, token_name="PLANET_API_KEY", tile_format="ipyleaflet"):
    """Generates Planet imagery TileLayer based on an API key. To get a Planet API key, see https://developers.planet.com/quickstart/apis/

    Args:
        api_key (str, optional): The Planet API key. Defaults to None.
        token_name (str, optional): The environment variable name of the API key. Defaults to "PLANET_API_KEY".
        tile_format (str, optional): The TileLayer format, can be either ipyleaflet or folium. Defaults to "ipyleaflet".

    Raises:
        ValueError: If the tile layer format is invalid.

    Returns:
        dict: A dictionary of TileLayer.
    """

    catalog = {}
    quarterly = planet_quarterly_tiles(api_key, token_name, tile_format)
    monthly = planet_monthly_tiles(api_key, token_name, tile_format)

    for key in quarterly:
        catalog[key] = quarterly[key]

    for key in monthly:
        catalog[key] = monthly[key]

    return catalog

planet_tiles_tropical(api_key=None, token_name='PLANET_API_KEY', tile_format='ipyleaflet')

Generates Planet monthly imagery TileLayer based on an API key. See https://assets.planet.com/docs/NICFI_UserGuidesFAQ.pdf

Parameters:

Name Type Description Default
api_key str

The Planet API key. Defaults to None.

None
token_name str

The environment variable name of the API key. Defaults to "PLANET_API_KEY".

'PLANET_API_KEY'
tile_format str

The TileLayer format, can be either ipyleaflet or folium. Defaults to "ipyleaflet".

'ipyleaflet'

Exceptions:

Type Description
ValueError

If the tile layer format is invalid.

Returns:

Type Description
dict

A dictionary of TileLayer.

Source code in leafmap/common.py
def planet_tiles_tropical(
    api_key=None, token_name="PLANET_API_KEY", tile_format="ipyleaflet"
):
    """Generates Planet  monthly imagery TileLayer based on an API key. See https://assets.planet.com/docs/NICFI_UserGuidesFAQ.pdf

    Args:
        api_key (str, optional): The Planet API key. Defaults to None.
        token_name (str, optional): The environment variable name of the API key. Defaults to "PLANET_API_KEY".
        tile_format (str, optional): The TileLayer format, can be either ipyleaflet or folium. Defaults to "ipyleaflet".

    Raises:
        ValueError: If the tile layer format is invalid.

    Returns:
        dict: A dictionary of TileLayer.
    """

    catalog = {}
    biannul = planet_biannual_tiles_tropical(api_key, token_name, tile_format)
    monthly = planet_monthly_tiles_tropical(api_key, token_name, tile_format)

    for key in biannul:
        catalog[key] = biannul[key]

    for key in monthly:
        catalog[key] = monthly[key]

    return catalog

plot_raster(image, band=None, cmap='terrain', proj='EPSG:3857', figsize=None, open_kwargs={}, **kwargs)

Plot a raster image.

Parameters:

Name Type Description Default
image str | xarray.DataArray

The input raster image, can be a file path, HTTP URL, or xarray.DataArray.

required
band int

The band index, starting from zero. Defaults to None.

None
cmap str

The matplotlib colormap to use. Defaults to "terrain".

'terrain'
proj str

The EPSG projection code. Defaults to "EPSG:3857".

'EPSG:3857'
figsize tuple

The figure size as a tuple, such as (10, 8). Defaults to None.

None
open_kwargs dict

The keyword arguments to pass to rioxarray.open_rasterio. Defaults to {}.

{}
**kwargs

Additional keyword arguments to pass to xarray.DataArray.plot().

{}
Source code in leafmap/common.py
def plot_raster(
    image,
    band=None,
    cmap="terrain",
    proj="EPSG:3857",
    figsize=None,
    open_kwargs={},
    **kwargs,
):
    """Plot a raster image.

    Args:
        image (str | xarray.DataArray ): The input raster image, can be a file path, HTTP URL, or xarray.DataArray.
        band (int, optional): The band index, starting from zero. Defaults to None.
        cmap (str, optional): The matplotlib colormap to use. Defaults to "terrain".
        proj (str, optional): The EPSG projection code. Defaults to "EPSG:3857".
        figsize (tuple, optional): The figure size as a tuple, such as (10, 8). Defaults to None.
        open_kwargs (dict, optional): The keyword arguments to pass to rioxarray.open_rasterio. Defaults to {}.
        **kwargs: Additional keyword arguments to pass to xarray.DataArray.plot().

    """
    if os.environ.get("USE_MKDOCS") is not None:
        return

    try:
        import pvxarray
        import rioxarray
        import xarray
    except ImportError:
        raise ImportError(
            "pyxarray and rioxarray are required for plotting. Please install them using 'pip install rioxarray pyvista-xarray'."
        )

    if isinstance(image, str):
        da = rioxarray.open_rasterio(image, **open_kwargs)
    elif isinstance(image, xarray.DataArray):
        da = image
    else:
        raise ValueError("image must be a string or xarray.Dataset.")

    if band is not None:
        da = da[dict(band=band)]

    da = da.rio.reproject(proj)
    kwargs["cmap"] = cmap
    kwargs["figsize"] = figsize
    da.plot(**kwargs)

plot_raster_3d(image, band=None, cmap='terrain', factor=1.0, proj='EPSG:3857', background=None, open_kwargs={}, mesh_kwargs={}, **kwargs)

Plot a raster image in 3D.

Parameters:

Name Type Description Default
image str | xarray.DataArray

The input raster image, can be a file path, HTTP URL, or xarray.DataArray.

required
band int

The band index, starting from zero. Defaults to None.

None
cmap str

The matplotlib colormap to use. Defaults to "terrain".

'terrain'
factor float

The scaling factor for the raster. Defaults to 1.0.

1.0
proj str

The EPSG projection code. Defaults to "EPSG:3857".

'EPSG:3857'
background str

The background color. Defaults to None.

None
open_kwargs dict

The keyword arguments to pass to rioxarray.open_rasterio. Defaults to {}.

{}
mesh_kwargs dict

The keyword arguments to pass to pyvista.mesh.warp_by_scalar(). Defaults to {}.

{}
**kwargs

Additional keyword arguments to pass to xarray.DataArray.plot().

{}
Source code in leafmap/common.py
def plot_raster_3d(
    image,
    band=None,
    cmap="terrain",
    factor=1.0,
    proj="EPSG:3857",
    background=None,
    open_kwargs={},
    mesh_kwargs={},
    **kwargs,
):
    """Plot a raster image in 3D.

    Args:
        image (str | xarray.DataArray ): The input raster image, can be a file path, HTTP URL, or xarray.DataArray.
        band (int, optional): The band index, starting from zero. Defaults to None.
        cmap (str, optional): The matplotlib colormap to use. Defaults to "terrain".
        factor (float, optional): The scaling factor for the raster. Defaults to 1.0.
        proj (str, optional): The EPSG projection code. Defaults to "EPSG:3857".
        background (str, optional): The background color. Defaults to None.
        open_kwargs (dict, optional): The keyword arguments to pass to rioxarray.open_rasterio. Defaults to {}.
        mesh_kwargs (dict, optional): The keyword arguments to pass to pyvista.mesh.warp_by_scalar(). Defaults to {}.
        **kwargs: Additional keyword arguments to pass to xarray.DataArray.plot().
    """

    if os.environ.get("USE_MKDOCS") is not None:
        return

    try:
        import pvxarray
        import pyvista
        import rioxarray
        import xarray
    except ImportError:
        raise ImportError(
            "pyxarray and rioxarray are required for plotting. Please install them using 'pip install rioxarray pyvista-xarray'."
        )

    if isinstance(background, str):
        pyvista.global_theme.background = background

    if isinstance(image, str):
        da = rioxarray.open_rasterio(image, **open_kwargs)
    elif isinstance(image, xarray.DataArray):
        da = image
    else:
        raise ValueError("image must be a string or xarray.Dataset.")

    if band is not None:
        da = da[dict(band=band)]

    da = da.rio.reproject(proj)
    mesh_kwargs["factor"] = factor
    kwargs["cmap"] = cmap

    # Grab the mesh object for use with PyVista
    mesh = da.pyvista.mesh

    # Warp top and plot in 3D
    mesh.warp_by_scalar(**mesh_kwargs).plot(**kwargs)

points_from_xy(data, x='longitude', y='latitude', z=None, crs=None, **kwargs)

Create a GeoPandas GeoDataFrame from a csv or Pandas DataFrame containing x, y, z values.

Parameters:

Name Type Description Default
data str | pd.DataFrame

A csv or Pandas DataFrame containing x, y, z values.

required
x str

The column name for the x values. Defaults to "longitude".

'longitude'
y str

The column name for the y values. Defaults to "latitude".

'latitude'
z str

The column name for the z values. Defaults to None.

None
crs str | int

The coordinate reference system for the GeoDataFrame. Defaults to None.

None

Returns:

Type Description
geopandas.GeoDataFrame

A GeoPandas GeoDataFrame containing x, y, z values.

Source code in leafmap/common.py
def points_from_xy(data, x="longitude", y="latitude", z=None, crs=None, **kwargs):
    """Create a GeoPandas GeoDataFrame from a csv or Pandas DataFrame containing x, y, z values.

    Args:
        data (str | pd.DataFrame): A csv or Pandas DataFrame containing x, y, z values.
        x (str, optional): The column name for the x values. Defaults to "longitude".
        y (str, optional): The column name for the y values. Defaults to "latitude".
        z (str, optional): The column name for the z values. Defaults to None.
        crs (str | int, optional): The coordinate reference system for the GeoDataFrame. Defaults to None.

    Returns:
        geopandas.GeoDataFrame: A GeoPandas GeoDataFrame containing x, y, z values.
    """
    check_package(name="geopandas", URL="https://geopandas.org")
    import geopandas as gpd
    import pandas as pd

    if crs is None:
        crs = "epsg:4326"

    if isinstance(data, pd.DataFrame):
        df = data
    elif isinstance(data, str):
        if not data.startswith("http") and (not os.path.exists(data)):
            raise FileNotFoundError("The specified input csv does not exist.")
        else:
            df = pd.read_csv(data, **kwargs)
    else:
        raise TypeError("The data must be a pandas DataFrame or a csv file path.")

    gdf = gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(df[x], df[y], z=z, crs=crs))

    return gdf

random_string(string_length=3)

Generates a random string of fixed length.

Parameters:

Name Type Description Default
string_length int

Fixed length. Defaults to 3.

3

Returns:

Type Description
str

A random string

Source code in leafmap/common.py
def random_string(string_length=3):
    """Generates a random string of fixed length.

    Args:
        string_length (int, optional): Fixed length. Defaults to 3.

    Returns:
        str: A random string
    """
    import random
    import string

    # random.seed(1001)
    letters = string.ascii_lowercase
    return "".join(random.choice(letters) for i in range(string_length))

read_file_from_url(url, return_type='list', encoding='utf-8')

Reads a file from a URL.

Parameters:

Name Type Description Default
url str

The URL of the file.

required
return_type str

The return type, can either be string or list. Defaults to "list".

'list'
encoding str

The encoding of the file. Defaults to "utf-8".

'utf-8'

Exceptions:

Type Description
ValueError

The return type must be either list or string.

Returns:

Type Description
str | list

The contents of the file.

Source code in leafmap/common.py
def read_file_from_url(url, return_type="list", encoding="utf-8"):
    """Reads a file from a URL.

    Args:
        url (str): The URL of the file.
        return_type (str, optional): The return type, can either be string or list. Defaults to "list".
        encoding (str, optional): The encoding of the file. Defaults to "utf-8".

    Raises:
        ValueError: The return type must be either list or string.

    Returns:
        str | list: The contents of the file.
    """
    from urllib.request import urlopen

    if return_type == "list":
        return [line.decode(encoding).rstrip() for line in urlopen(url).readlines()]
    elif return_type == "string":
        return urlopen(url).read().decode(encoding)
    else:
        raise ValueError("The return type must be either list or string.")

read_lidar(filename, **kwargs)

Read a LAS file.

Parameters:

Name Type Description Default
filename str

Path to a LAS file.

required

Returns:

Type Description
LasData

The LasData object return by laspy.read.

Source code in leafmap/common.py
def read_lidar(filename, **kwargs):
    """Read a LAS file.

    Args:
        filename (str): Path to a LAS file.

    Returns:
        LasData: The LasData object return by laspy.read.
    """
    try:
        import laspy
    except ImportError:
        print(
            "The laspy package is required for this function. Use pip install laspy to install it."
        )
        return

    return laspy.read(filename, **kwargs)

read_netcdf(filename, **kwargs)

Read a netcdf file.

Parameters:

Name Type Description Default
filename str

File path or HTTP URL to the netcdf file.

required

Exceptions:

Type Description
ImportError

If the xarray or rioxarray package is not installed.

FileNotFoundError

If the netcdf file is not found.

Returns:

Type Description
xarray.Dataset

The netcdf file as an xarray dataset.

Source code in leafmap/common.py
def read_netcdf(filename, **kwargs):
    """Read a netcdf file.

    Args:
        filename (str): File path or HTTP URL to the netcdf file.

    Raises:
        ImportError: If the xarray or rioxarray package is not installed.
        FileNotFoundError: If the netcdf file is not found.

    Returns:
        xarray.Dataset: The netcdf file as an xarray dataset.
    """
    try:
        import xarray as xr
    except ImportError as e:
        raise ImportError(e)

    if filename.startswith("http"):
        filename = download_file(filename)

    if not os.path.exists(filename):
        raise FileNotFoundError(f"{filename} does not exist.")

    xds = xr.open_dataset(filename, **kwargs)
    return xds

read_postgis(sql, con, geom_col='geom', crs=None, **kwargs)

Reads data from a PostGIS database and returns a GeoDataFrame.

Parameters:

Name Type Description Default
sql str

SQL query to execute in selecting entries from database, or name of the table to read from the database.

required
con sqlalchemy.engine.Engine

Active connection to the database to query.

required
geom_col str

Column name to convert to shapely geometries. Defaults to "geom".

'geom'
crs str | dict

CRS to use for the returned GeoDataFrame; if not set, tries to determine CRS from the SRID associated with the first geometry in the database, and assigns that to all geometries. Defaults to None.

None

Returns:

Type Description
[type]

[description]

Source code in leafmap/common.py
def read_postgis(sql, con, geom_col="geom", crs=None, **kwargs):
    """Reads data from a PostGIS database and returns a GeoDataFrame.

    Args:
        sql (str): SQL query to execute in selecting entries from database, or name of the table to read from the database.
        con (sqlalchemy.engine.Engine): Active connection to the database to query.
        geom_col (str, optional): Column name to convert to shapely geometries. Defaults to "geom".
        crs (str | dict, optional): CRS to use for the returned GeoDataFrame; if not set, tries to determine CRS from the SRID associated with the first geometry in the database, and assigns that to all geometries. Defaults to None.

    Returns:
        [type]: [description]
    """
    check_package(name="geopandas", URL="https://geopandas.org")

    import geopandas as gpd

    gdf = gpd.read_postgis(sql, con, geom_col, crs, **kwargs)
    return gdf

rgb_to_hex(rgb=(255, 255, 255))

Converts RGB to hex color. In RGB color R stands for Red, G stands for Green, and B stands for Blue, and it ranges from the decimal value of 0 – 255.

Parameters:

Name Type Description Default
rgb tuple

RGB color code as a tuple of (red, green, blue). Defaults to (255, 255, 255).

(255, 255, 255)

Returns:

Type Description
str

hex color code

Source code in leafmap/common.py
def rgb_to_hex(rgb=(255, 255, 255)):
    """Converts RGB to hex color. In RGB color R stands for Red, G stands for Green, and B stands for Blue, and it ranges from the decimal value of 0 – 255.

    Args:
        rgb (tuple, optional): RGB color code as a tuple of (red, green, blue). Defaults to (255, 255, 255).

    Returns:
        str: hex color code
    """
    return "%02x%02x%02x" % rgb

save_data(data, file_ext=None, file_name=None)

Save data in the memory to a file.

Parameters:

Name Type Description Default
data object

The data to be saved.

required
file_ext str

The file extension of the file.

None
file_name str

The name of the file to be saved. Defaults to None.

None

Returns:

Type Description
str

The path of the file.

Source code in leafmap/common.py
def save_data(data, file_ext=None, file_name=None):
    """Save data in the memory to a file.

    Args:
        data (object): The data to be saved.
        file_ext (str): The file extension of the file.
        file_name (str, optional): The name of the file to be saved. Defaults to None.

    Returns:
        str: The path of the file.
    """
    import tempfile
    import uuid

    try:

        if file_ext is None:
            if hasattr(data, "name"):
                _, file_ext = os.path.splitext(data.name)
        else:
            if not file_ext.startswith("."):
                file_ext = "." + file_ext

        if file_name is not None:
            file_path = os.path.abspath(file_name)
            if not file_path.endswith(file_ext):
                file_path = file_path + file_ext
        else:
            file_id = str(uuid.uuid4())
            file_path = os.path.join(tempfile.gettempdir(), f"{file_id}{file_ext}")

        with open(file_path, "wb") as file:
            file.write(data.getbuffer())
        return file_path
    except Exception as e:
        print(e)
        return None

screen_capture(outfile, monitor=1)

Takes a full screenshot of the selected monitor.

Parameters:

Name Type Description Default
outfile str

The output file path to the screenshot.

required
monitor int

The monitor to take the screenshot. Defaults to 1.

1
Source code in leafmap/common.py
def screen_capture(outfile, monitor=1):
    """Takes a full screenshot of the selected monitor.

    Args:
        outfile (str): The output file path to the screenshot.
        monitor (int, optional): The monitor to take the screenshot. Defaults to 1.
    """
    try:
        from mss import mss
    except ImportError:
        raise ImportError("Please install mss using 'pip install mss'")

    out_dir = os.path.dirname(outfile)
    if not os.path.exists(out_dir):
        os.makedirs(out_dir)

    if not isinstance(monitor, int):
        print("The monitor number must be an integer.")
        return

    try:
        with mss() as sct:
            sct.shot(output=outfile, mon=monitor)
            return outfile

    except Exception as e:
        raise Exception(e)

search_qms(keyword, limit=10, list_only=True, add_prefix=True)

Search for QMS tile providers from Quick Map Services.

Parameters:

Name Type Description Default
keyword str

The keyword to search for.

required
limit int

The maximum number of results to return. Defaults to 10.

10
list_only bool

If True, only the list of services will be returned. Defaults to True.

True
add_prefix bool

If True, the prefix "qms." will be added to the service name. Defaults to True.

True

Returns:

Type Description
list

A list of QMS tile providers.

Source code in leafmap/common.py
def search_qms(keyword, limit=10, list_only=True, add_prefix=True):
    """Search for QMS tile providers from Quick Map Services.

    Args:
        keyword (str): The keyword to search for.
        limit (int, optional): The maximum number of results to return. Defaults to 10.
        list_only (bool, optional): If True, only the list of services will be returned. Defaults to True.
        add_prefix (bool, optional): If True, the prefix "qms." will be added to the service name. Defaults to True.

    Returns:
        list: A list of QMS tile providers.
    """

    QMS_API = "https://qms.nextgis.com/api/v1/geoservices"
    services = requests.get(
        f"{QMS_API}/?search={keyword}&type=tms&epsg=3857&limit={limit}"
    )
    services = services.json()
    if services["results"]:
        providers = services["results"]
        if list_only:
            if add_prefix:
                return ["qms." + provider["name"] for provider in providers]
            else:
                return [provider["name"] for provider in providers]
        else:
            return providers
    else:
        return None

search_xyz_services(keyword, name=None, list_only=True, add_prefix=True)

Search for XYZ tile providers from xyzservices.

Parameters:

Name Type Description Default
keyword str

The keyword to search for.

required
name str

The name of the xyz tile. Defaults to None.

None
list_only bool

If True, only the list of services will be returned. Defaults to True.

True
add_prefix bool

If True, the prefix "xyz." will be added to the service name. Defaults to True.

True

Returns:

Type Description
list

A list of XYZ tile providers.

Source code in leafmap/common.py
def search_xyz_services(keyword, name=None, list_only=True, add_prefix=True):
    """Search for XYZ tile providers from xyzservices.

    Args:
        keyword (str): The keyword to search for.
        name (str, optional): The name of the xyz tile. Defaults to None.
        list_only (bool, optional): If True, only the list of services will be returned. Defaults to True.
        add_prefix (bool, optional): If True, the prefix "xyz." will be added to the service name. Defaults to True.

    Returns:
        list: A list of XYZ tile providers.
    """

    import xyzservices.providers as xyz

    if name is None:
        providers = xyz.filter(keyword=keyword).flatten()
    else:
        providers = xyz.filter(name=name).flatten()

    if list_only:
        if add_prefix:
            return ["xyz." + provider for provider in providers]
        else:
            return [provider for provider in providers]
    else:
        return providers

set_api_key(token_name, api_key, m=None)

Sets an API key as an environment variable.

Parameters:

Name Type Description Default
token_name str

The token name.

required
api_key str

The API key.

required
m ipyleaflet.Map | folium.Map

A Map instance.. Defaults to None.

None
Source code in leafmap/common.py
def set_api_key(token_name, api_key, m=None):
    """Sets an API key as an environment variable.

    Args:
        token_name (str): The token name.
        api_key (str): The API key.
        m (ipyleaflet.Map | folium.Map, optional): A Map instance.. Defaults to None.
    """
    os.environ[token_name] = api_key
    if m is not None:
        m.api_keys[token_name] = api_key

set_proxy(port=1080, ip='http://127.0.0.1')

Sets proxy if needed. This is only needed for countries where Google services are not available.

Parameters:

Name Type Description Default
port int

The proxy port number. Defaults to 1080.

1080
ip str

The IP address. Defaults to 'http://127.0.0.1'.

'http://127.0.0.1'
Source code in leafmap/common.py
def set_proxy(port=1080, ip="http://127.0.0.1"):
    """Sets proxy if needed. This is only needed for countries where Google services are not available.

    Args:
        port (int, optional): The proxy port number. Defaults to 1080.
        ip (str, optional): The IP address. Defaults to 'http://127.0.0.1'.
    """

    try:

        if not ip.startswith("http"):
            ip = "http://" + ip
        proxy = "{}:{}".format(ip, port)

        os.environ["HTTP_PROXY"] = proxy
        os.environ["HTTPS_PROXY"] = proxy

        a = requests.get("https://google.com")

        if a.status_code != 200:
            print(
                "Failed to connect to Google services. Please double check the port number and ip address."
            )

    except Exception as e:
        raise Exception(e)

show_image(img_path, width=None, height=None)

Shows an image within Jupyter notebook.

Parameters:

Name Type Description Default
img_path str

The image file path.

required
width int

Width of the image in pixels. Defaults to None.

None
height int

Height of the image in pixels. Defaults to None.

None
Source code in leafmap/common.py
def show_image(img_path, width=None, height=None):
    """Shows an image within Jupyter notebook.

    Args:
        img_path (str): The image file path.
        width (int, optional): Width of the image in pixels. Defaults to None.
        height (int, optional): Height of the image in pixels. Defaults to None.

    """
    from IPython.display import display

    try:
        out = widgets.Output()
        # layout={'border': '1px solid black'})
        # layout={'border': '1px solid black', 'width': str(width + 20) + 'px', 'height': str(height + 10) + 'px'},)
        out.clear_output(wait=True)
        display(out)
        with out:
            file = open(img_path, "rb")
            image = file.read()
            if (width is None) and (height is None):
                display(widgets.Image(value=image))
            elif (width is not None) and (height is not None):
                display(widgets.Image(value=image, width=width, height=height))
            else:
                print("You need set both width and height.")
                return
    except Exception as e:
        raise Exception(e)

shp_to_gdf(in_shp)

Converts a shapefile to Geopandas dataframe.

Parameters:

Name Type Description Default
in_shp str

File path to the input shapefile.

required

Exceptions:

Type Description
FileNotFoundError

The provided shp could not be found.

Returns:

Type Description
gpd.GeoDataFrame

geopandas.GeoDataFrame

Source code in leafmap/common.py
def shp_to_gdf(in_shp):
    """Converts a shapefile to Geopandas dataframe.

    Args:
        in_shp (str): File path to the input shapefile.

    Raises:
        FileNotFoundError: The provided shp could not be found.

    Returns:
        gpd.GeoDataFrame: geopandas.GeoDataFrame
    """
    import warnings

    warnings.filterwarnings("ignore")

    in_shp = os.path.abspath(in_shp)
    if not os.path.exists(in_shp):
        raise FileNotFoundError("The provided shp could not be found.")

    check_package(name="geopandas", URL="https://geopandas.org")

    import geopandas as gpd

    try:
        return gpd.read_file(in_shp)
    except Exception as e:
        raise Exception(e)

shp_to_geojson(in_shp, out_json=None, encoding='utf-8', **kwargs)

Converts a shapefile to GeoJSON.

Parameters:

Name Type Description Default
in_shp str

File path of the input shapefile.

required
out_json str

File path of the output GeoJSON. Defaults to None.

None

Returns:

Type Description
object

The json object representing the shapefile.

Source code in leafmap/common.py
def shp_to_geojson(in_shp, out_json=None, encoding="utf-8", **kwargs):
    """Converts a shapefile to GeoJSON.

    Args:
        in_shp (str): File path of the input shapefile.
        out_json (str, optional): File path of the output GeoJSON. Defaults to None.

    Returns:
        object: The json object representing the shapefile.
    """
    try:
        import shapefile

        in_shp = os.path.abspath(in_shp)

        if out_json is not None:
            ext = os.path.splitext(out_json)[1]
            print(ext)
            if ext.lower() not in [".json", ".geojson"]:
                raise TypeError("The output file extension must the .json or .geojson.")

            if not os.path.exists(os.path.dirname(out_json)):
                os.makedirs(os.path.dirname(out_json))

        if not is_GCS(in_shp):
            try:
                import geopandas as gpd

            except Exception:
                raise ImportError(
                    "Geopandas is required to perform reprojection of the data. See https://geopandas.org/install.html"
                )

            try:
                in_gdf = gpd.read_file(in_shp, encoding=encoding)
                out_gdf = in_gdf.to_crs(epsg="4326")
                out_shp = in_shp.replace(".shp", "_gcs.shp")
                out_gdf.to_file(out_shp)
                in_shp = out_shp
            except Exception as e:
                raise Exception(e)

        kwargs["encoding"] = encoding
        if "encoding" in kwargs:
            reader = shapefile.Reader(in_shp, encoding=kwargs.pop("encoding"))
        else:
            reader = shapefile.Reader(in_shp)
        out_dict = reader.__geo_interface__

        if out_json is not None:
            import json

            with open(out_json, "w") as geojson:
                geojson.write(json.dumps(out_dict, indent=2) + "\n")
        else:
            return out_dict

    except Exception as e:
        raise Exception(e)

st_download_button(label, data, file_name=None, mime=None, key=None, help=None, on_click=None, args=None, csv_sep=',', **kwargs)

Streamlit function to create a download button.

Parameters:

Name Type Description Default
label str

A short label explaining to the user what this button is for..

required
data str | list

The contents of the file to be downloaded. See example below for caching techniques to avoid recomputing this data unnecessarily.

required
file_name str

An optional string to use as the name of the file to be downloaded, such as 'my_file.csv'. If not specified, the name will be automatically generated. Defaults to None.

None
mime str

The MIME type of the data. If None, defaults to "text/plain" (if data is of type str or is a textual file) or "application/octet-stream" (if data is of type bytes or is a binary file). Defaults to None.

None
key str

An optional string or integer to use as the unique key for the widget. If this is omitted, a key will be generated for the widget based on its content. Multiple widgets of the same type may not share the same key. Defaults to None.

None
help str

An optional tooltip that gets displayed when the button is hovered over. Defaults to None.

None
on_click str

An optional callback invoked when this button is clicked. Defaults to None.

None
args list

An optional tuple of args to pass to the callback. Defaults to None.

None
kwargs dict

An optional tuple of args to pass to the callback.

{}
Source code in leafmap/common.py
def st_download_button(
    label,
    data,
    file_name=None,
    mime=None,
    key=None,
    help=None,
    on_click=None,
    args=None,
    csv_sep=",",
    **kwargs,
):
    """Streamlit function to create a download button.

    Args:
        label (str): A short label explaining to the user what this button is for..
        data (str | list): The contents of the file to be downloaded. See example below for caching techniques to avoid recomputing this data unnecessarily.
        file_name (str, optional): An optional string to use as the name of the file to be downloaded, such as 'my_file.csv'. If not specified, the name will be automatically generated. Defaults to None.
        mime (str, optional): The MIME type of the data. If None, defaults to "text/plain" (if data is of type str or is a textual file) or "application/octet-stream" (if data is of type bytes or is a binary file). Defaults to None.
        key (str, optional): An optional string or integer to use as the unique key for the widget. If this is omitted, a key will be generated for the widget based on its content. Multiple widgets of the same type may not share the same key. Defaults to None.
        help (str, optional): An optional tooltip that gets displayed when the button is hovered over. Defaults to None.
        on_click (str, optional): An optional callback invoked when this button is clicked. Defaults to None.
        args (list, optional): An optional tuple of args to pass to the callback. Defaults to None.
        kwargs (dict, optional): An optional tuple of args to pass to the callback.

    """
    try:
        import streamlit as st
        import pandas as pd

        if isinstance(data, str):

            if file_name is None:
                file_name = data.split("/")[-1]

            if data.endswith(".csv"):
                data = pd.read_csv(data).to_csv(sep=csv_sep, index=False)
                if mime is None:
                    mime = "text/csv"
                return st.download_button(
                    label, data, file_name, mime, key, help, on_click, args, **kwargs
                )
            elif (
                data.endswith(".gif") or data.endswith(".png") or data.endswith(".jpg")
            ):
                if mime is None:
                    mime = f"image/{os.path.splitext(data)[1][1:]}"

                with open(data, "rb") as file:
                    return st.download_button(
                        label,
                        file,
                        file_name,
                        mime,
                        key,
                        help,
                        on_click,
                        args,
                        **kwargs,
                    )
        elif isinstance(data, pd.DataFrame):
            if file_name is None:
                file_name = "data.csv"

            data = data.to_csv(sep=csv_sep, index=False)
            if mime is None:
                mime = "text/csv"
            return st.download_button(
                label, data, file_name, mime, key, help, on_click, args, **kwargs
            )

        else:
            # if mime is None:
            #     mime = "application/pdf"
            return st.download_button(
                label,
                data,
                file_name,
                mime,
                key,
                help,
                on_click,
                args,
                **kwargs,
            )

    except ImportError:
        print("Streamlit is not installed. Please run 'pip install streamlit'.")
        return
    except Exception as e:
        raise Exception(e)

stac_assets(url=None, collection=None, item=None, titiler_endpoint=None, **kwargs)

Get all assets of a STAC item.

Parameters:

Name Type Description Default
url str

HTTP URL to a STAC item, e.g., https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json

None
collection str

The Microsoft Planetary Computer STAC collection ID, e.g., landsat-8-c2-l2.

None
item str

The Microsoft Planetary Computer STAC item ID, e.g., LC08_L2SP_047027_20201204_02_T1.

None
titiler_endpoint str

Titiler endpoint, e.g., "https://titiler.xyz", "planetary-computer", "pc". Defaults to None.

None

Returns:

Type Description
list

A list of assets.

Source code in leafmap/common.py
def stac_assets(url=None, collection=None, item=None, titiler_endpoint=None, **kwargs):
    """Get all assets of a STAC item.

    Args:
        url (str): HTTP URL to a STAC item, e.g., https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json
        collection (str): The Microsoft Planetary Computer STAC collection ID, e.g., landsat-8-c2-l2.
        item (str): The Microsoft Planetary Computer STAC item ID, e.g., LC08_L2SP_047027_20201204_02_T1.
        titiler_endpoint (str, optional): Titiler endpoint, e.g., "https://titiler.xyz", "planetary-computer", "pc". Defaults to None.

    Returns:
        list: A list of assets.
    """

    if url is None and collection is None:
        raise ValueError("Either url or collection must be specified.")

    if collection is not None and titiler_endpoint is None:
        titiler_endpoint = "planetary-computer"

    if url is not None:
        kwargs["url"] = url
    if collection is not None:
        kwargs["collection"] = collection
    if item is not None:
        kwargs["item"] = item

    titiler_endpoint = check_titiler_endpoint(titiler_endpoint)
    if isinstance(titiler_endpoint, str):
        r = requests.get(f"{titiler_endpoint}/stac/assets", params=kwargs).json()
    else:
        r = requests.get(titiler_endpoint.url_for_stac_assets(), params=kwargs).json()

    return r

stac_bands(url=None, collection=None, item=None, titiler_endpoint=None, **kwargs)

Get band names of a single SpatialTemporal Asset Catalog (STAC) item.

Parameters:

Name Type Description Default
url str

HTTP URL to a STAC item, e.g., https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json

None
collection str

The Microsoft Planetary Computer STAC collection ID, e.g., landsat-8-c2-l2.

None
item str

The Microsoft Planetary Computer STAC item ID, e.g., LC08_L2SP_047027_20201204_02_T1.

None
titiler_endpoint str

Titiler endpoint, e.g., "https://titiler.xyz", "planetary-computer", "pc". Defaults to None.

None

Returns:

Type Description
list

A list of band names

Source code in leafmap/common.py
def stac_bands(url=None, collection=None, item=None, titiler_endpoint=None, **kwargs):
    """Get band names of a single SpatialTemporal Asset Catalog (STAC) item.

    Args:
        url (str): HTTP URL to a STAC item, e.g., https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json
        collection (str): The Microsoft Planetary Computer STAC collection ID, e.g., landsat-8-c2-l2.
        item (str): The Microsoft Planetary Computer STAC item ID, e.g., LC08_L2SP_047027_20201204_02_T1.
        titiler_endpoint (str, optional): Titiler endpoint, e.g., "https://titiler.xyz", "planetary-computer", "pc". Defaults to None.

    Returns:
        list: A list of band names
    """

    if url is None and collection is None:
        raise ValueError("Either url or collection must be specified.")

    if collection is not None and titiler_endpoint is None:
        titiler_endpoint = "planetary-computer"

    if url is not None:
        kwargs["url"] = url
    if collection is not None:
        kwargs["collection"] = collection
    if item is not None:
        kwargs["item"] = item

    titiler_endpoint = check_titiler_endpoint(titiler_endpoint)
    if isinstance(titiler_endpoint, str):
        r = requests.get(f"{titiler_endpoint}/stac/assets", params=kwargs).json()
    else:
        r = requests.get(titiler_endpoint.url_for_stac_assets(), params=kwargs).json()

    return r

stac_bounds(url=None, collection=None, item=None, titiler_endpoint=None, **kwargs)

Get the bounding box of a single SpatialTemporal Asset Catalog (STAC) item.

Parameters:

Name Type Description Default
url str

HTTP URL to a STAC item, e.g., https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json

None
collection str

The Microsoft Planetary Computer STAC collection ID, e.g., landsat-8-c2-l2.

None
item str

The Microsoft Planetary Computer STAC item ID, e.g., LC08_L2SP_047027_20201204_02_T1.

None
titiler_endpoint str

Titiler endpoint, e.g., "https://titiler.xyz", "planetary-computer", "pc". Defaults to None.

None

Returns:

Type Description
list

A list of values representing [left, bottom, right, top]

Source code in leafmap/common.py
def stac_bounds(url=None, collection=None, item=None, titiler_endpoint=None, **kwargs):
    """Get the bounding box of a single SpatialTemporal Asset Catalog (STAC) item.

    Args:
        url (str): HTTP URL to a STAC item, e.g., https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json
        collection (str): The Microsoft Planetary Computer STAC collection ID, e.g., landsat-8-c2-l2.
        item (str): The Microsoft Planetary Computer STAC item ID, e.g., LC08_L2SP_047027_20201204_02_T1.
        titiler_endpoint (str, optional): Titiler endpoint, e.g., "https://titiler.xyz", "planetary-computer", "pc". Defaults to None.

    Returns:
        list: A list of values representing [left, bottom, right, top]
    """

    if url is None and collection is None:
        raise ValueError("Either url or collection must be specified.")

    if collection is not None and titiler_endpoint is None:
        titiler_endpoint = "planetary-computer"

    if url is not None:
        kwargs["url"] = url
    if collection is not None:
        kwargs["collection"] = collection
    if item is not None:
        kwargs["item"] = item

    titiler_endpoint = check_titiler_endpoint(titiler_endpoint)
    if isinstance(titiler_endpoint, str):
        r = requests.get(f"{titiler_endpoint}/stac/bounds", params=kwargs).json()
    else:
        r = requests.get(titiler_endpoint.url_for_stac_bounds(), params=kwargs).json()

    bounds = r["bounds"]
    return bounds

stac_center(url=None, collection=None, item=None, titiler_endpoint=None, **kwargs)

Get the centroid of a single SpatialTemporal Asset Catalog (STAC) item.

Parameters:

Name Type Description Default
url str

HTTP URL to a STAC item, e.g., https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json

None
collection str

The Microsoft Planetary Computer STAC collection ID, e.g., landsat-8-c2-l2.

None
item str

The Microsoft Planetary Computer STAC item ID, e.g., LC08_L2SP_047027_20201204_02_T1.

None
titiler_endpoint str

Titiler endpoint, e.g., "https://titiler.xyz", "planetary-computer", "pc". Defaults to None.

None

Returns:

Type Description
tuple

A tuple representing (longitude, latitude)

Source code in leafmap/common.py
def stac_center(url=None, collection=None, item=None, titiler_endpoint=None, **kwargs):
    """Get the centroid of a single SpatialTemporal Asset Catalog (STAC) item.

    Args:
        url (str): HTTP URL to a STAC item, e.g., https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json
        collection (str): The Microsoft Planetary Computer STAC collection ID, e.g., landsat-8-c2-l2.
        item (str): The Microsoft Planetary Computer STAC item ID, e.g., LC08_L2SP_047027_20201204_02_T1.
        titiler_endpoint (str, optional): Titiler endpoint, e.g., "https://titiler.xyz", "planetary-computer", "pc". Defaults to None.

    Returns:
        tuple: A tuple representing (longitude, latitude)
    """
    bounds = stac_bounds(url, collection, item, titiler_endpoint, **kwargs)
    center = ((bounds[0] + bounds[2]) / 2, (bounds[1] + bounds[3]) / 2)  # (lon, lat)
    return center

stac_info(url=None, collection=None, item=None, assets=None, titiler_endpoint=None, **kwargs)

Get band info of a STAC item.

Parameters:

Name Type Description Default
url str

HTTP URL to a STAC item, e.g., https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json

None
collection str

The Microsoft Planetary Computer STAC collection ID, e.g., landsat-8-c2-l2.

None
item str

The Microsoft Planetary Computer STAC item ID, e.g., LC08_L2SP_047027_20201204_02_T1.

None
assets str | list

The Microsoft Planetary Computer STAC asset ID, e.g., ["SR_B7", "SR_B5", "SR_B4"].

None
titiler_endpoint str

Titiler endpoint, e.g., "https://titiler.xyz", "planetary-computer", "pc". Defaults to None.

None

Returns:

Type Description
list

A dictionary of band info.

Source code in leafmap/common.py
def stac_info(
    url=None, collection=None, item=None, assets=None, titiler_endpoint=None, **kwargs
):
    """Get band info of a STAC item.

    Args:
        url (str): HTTP URL to a STAC item, e.g., https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json
        collection (str): The Microsoft Planetary Computer STAC collection ID, e.g., landsat-8-c2-l2.
        item (str): The Microsoft Planetary Computer STAC item ID, e.g., LC08_L2SP_047027_20201204_02_T1.
        assets (str | list): The Microsoft Planetary Computer STAC asset ID, e.g., ["SR_B7", "SR_B5", "SR_B4"].
        titiler_endpoint (str, optional): Titiler endpoint, e.g., "https://titiler.xyz", "planetary-computer", "pc". Defaults to None.

    Returns:
        list: A dictionary of band info.
    """

    if url is None and collection is None:
        raise ValueError("Either url or collection must be specified.")

    if collection is not None and titiler_endpoint is None:
        titiler_endpoint = "planetary-computer"

    if url is not None:
        kwargs["url"] = url
    if collection is not None:
        kwargs["collection"] = collection
    if item is not None:
        kwargs["item"] = item
    if assets is not None:
        kwargs["assets"] = assets

    titiler_endpoint = check_titiler_endpoint(titiler_endpoint)
    if isinstance(titiler_endpoint, str):
        r = requests.get(f"{titiler_endpoint}/stac/info", params=kwargs).json()
    else:
        r = requests.get(titiler_endpoint.url_for_stac_info(), params=kwargs).json()

    return r

stac_info_geojson(url=None, collection=None, item=None, assets=None, titiler_endpoint=None, **kwargs)

Get band info of a STAC item.

Parameters:

Name Type Description Default
url str

HTTP URL to a STAC item, e.g., https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json

None
collection str

The Microsoft Planetary Computer STAC collection ID, e.g., landsat-8-c2-l2.

None
item str

The Microsoft Planetary Computer STAC item ID, e.g., LC08_L2SP_047027_20201204_02_T1.

None
assets str | list

The Microsoft Planetary Computer STAC asset ID, e.g., ["SR_B7", "SR_B5", "SR_B4"].

None
titiler_endpoint str

Titiler endpoint, e.g., "https://titiler.xyz", "planetary-computer", "pc". Defaults to None.

None

Returns:

Type Description
list

A dictionary of band info.

Source code in leafmap/common.py
def stac_info_geojson(
    url=None, collection=None, item=None, assets=None, titiler_endpoint=None, **kwargs
):
    """Get band info of a STAC item.

    Args:
        url (str): HTTP URL to a STAC item, e.g., https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json
        collection (str): The Microsoft Planetary Computer STAC collection ID, e.g., landsat-8-c2-l2.
        item (str): The Microsoft Planetary Computer STAC item ID, e.g., LC08_L2SP_047027_20201204_02_T1.
        assets (str | list): The Microsoft Planetary Computer STAC asset ID, e.g., ["SR_B7", "SR_B5", "SR_B4"].
        titiler_endpoint (str, optional): Titiler endpoint, e.g., "https://titiler.xyz", "planetary-computer", "pc". Defaults to None.

    Returns:
        list: A dictionary of band info.
    """

    if url is None and collection is None:
        raise ValueError("Either url or collection must be specified.")

    if collection is not None and titiler_endpoint is None:
        titiler_endpoint = "planetary-computer"

    if url is not None:
        kwargs["url"] = url
    if collection is not None:
        kwargs["collection"] = collection
    if item is not None:
        kwargs["item"] = item
    if assets is not None:
        kwargs["assets"] = assets

    titiler_endpoint = check_titiler_endpoint(titiler_endpoint)
    if isinstance(titiler_endpoint, str):
        r = requests.get(f"{titiler_endpoint}/stac/info.geojson", params=kwargs).json()
    else:
        r = requests.get(
            titiler_endpoint.url_for_stac_info_geojson(), params=kwargs
        ).json()

    return r

stac_pixel_value(lon, lat, url=None, collection=None, item=None, assets=None, titiler_endpoint=None, verbose=True, **kwargs)

Get pixel value from STAC assets.

Parameters:

Name Type Description Default
lon float

Longitude of the pixel.

required
lat float

Latitude of the pixel.

required
url str

HTTP URL to a STAC item, e.g., https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json

None
collection str

The Microsoft Planetary Computer STAC collection ID, e.g., landsat-8-c2-l2.

None
item str

The Microsoft Planetary Computer STAC item ID, e.g., LC08_L2SP_047027_20201204_02_T1.

None
assets str | list

The Microsoft Planetary Computer STAC asset ID, e.g., ["SR_B7", "SR_B5", "SR_B4"].

None
titiler_endpoint str

Titiler endpoint, e.g., "https://titiler.xyz", "planetary-computer", "pc". Defaults to None.

None
verbose bool

Print out the error message. Defaults to True.

True

Returns:

Type Description
list

A dictionary of pixel values for each asset.

Source code in leafmap/common.py
def stac_pixel_value(
    lon,
    lat,
    url=None,
    collection=None,
    item=None,
    assets=None,
    titiler_endpoint=None,
    verbose=True,
    **kwargs,
):
    """Get pixel value from STAC assets.

    Args:
        lon (float): Longitude of the pixel.
        lat (float): Latitude of the pixel.
        url (str): HTTP URL to a STAC item, e.g., https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json
        collection (str): The Microsoft Planetary Computer STAC collection ID, e.g., landsat-8-c2-l2.
        item (str): The Microsoft Planetary Computer STAC item ID, e.g., LC08_L2SP_047027_20201204_02_T1.
        assets (str | list): The Microsoft Planetary Computer STAC asset ID, e.g., ["SR_B7", "SR_B5", "SR_B4"].
        titiler_endpoint (str, optional): Titiler endpoint, e.g., "https://titiler.xyz", "planetary-computer", "pc". Defaults to None.
        verbose (bool, optional): Print out the error message. Defaults to True.

    Returns:
        list: A dictionary of pixel values for each asset.
    """

    if url is None and collection is None:
        raise ValueError("Either url or collection must be specified.")

    if collection is not None and titiler_endpoint is None:
        titiler_endpoint = "planetary-computer"

    if url is not None:
        kwargs["url"] = url
    if collection is not None:
        kwargs["collection"] = collection
    if item is not None:
        kwargs["item"] = item

    if assets is None:
        assets = stac_assets(
            url=url,
            collection=collection,
            item=item,
            titiler_endpoint=titiler_endpoint,
        )
        assets = ",".join(assets)
    kwargs["assets"] = assets

    titiler_endpoint = check_titiler_endpoint(titiler_endpoint)
    if isinstance(titiler_endpoint, str):
        r = requests.get(f"{titiler_endpoint}/stac/{lon},{lat}", params=kwargs).json()
    else:
        r = requests.get(
            titiler_endpoint.url_for_stac_pixel_value(lon, lat), params=kwargs
        ).json()

    if "detail" in r:
        if verbose:
            print(r["detail"])
        return None
    else:
        values = [v[0] for v in r["values"]]
        result = dict(zip(assets.split(","), values))
        return result

stac_stats(url=None, collection=None, item=None, assets=None, titiler_endpoint=None, **kwargs)

Get band statistics of a STAC item.

Parameters:

Name Type Description Default
url str

HTTP URL to a STAC item, e.g., https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json

None
collection str

The Microsoft Planetary Computer STAC collection ID, e.g., landsat-8-c2-l2.

None
item str

The Microsoft Planetary Computer STAC item ID, e.g., LC08_L2SP_047027_20201204_02_T1.

None
assets str | list

The Microsoft Planetary Computer STAC asset ID, e.g., ["SR_B7", "SR_B5", "SR_B4"].

None
titiler_endpoint str

Titiler endpoint, e.g., "https://titiler.xyz", "planetary-computer", "pc". Defaults to None.

None

Returns:

Type Description
list

A dictionary of band statistics.

Source code in leafmap/common.py
def stac_stats(
    url=None, collection=None, item=None, assets=None, titiler_endpoint=None, **kwargs
):
    """Get band statistics of a STAC item.

    Args:
        url (str): HTTP URL to a STAC item, e.g., https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json
        collection (str): The Microsoft Planetary Computer STAC collection ID, e.g., landsat-8-c2-l2.
        item (str): The Microsoft Planetary Computer STAC item ID, e.g., LC08_L2SP_047027_20201204_02_T1.
        assets (str | list): The Microsoft Planetary Computer STAC asset ID, e.g., ["SR_B7", "SR_B5", "SR_B4"].
        titiler_endpoint (str, optional): Titiler endpoint, e.g., "https://titiler.xyz", "planetary-computer", "pc". Defaults to None.

    Returns:
        list: A dictionary of band statistics.
    """

    if url is None and collection is None:
        raise ValueError("Either url or collection must be specified.")

    if collection is not None and titiler_endpoint is None:
        titiler_endpoint = "planetary-computer"

    if url is not None:
        kwargs["url"] = url
    if collection is not None:
        kwargs["collection"] = collection
    if item is not None:
        kwargs["item"] = item
    if assets is not None:
        kwargs["assets"] = assets

    titiler_endpoint = check_titiler_endpoint(titiler_endpoint)
    if isinstance(titiler_endpoint, str):
        r = requests.get(f"{titiler_endpoint}/stac/statistics", params=kwargs).json()
    else:
        r = requests.get(
            titiler_endpoint.url_for_stac_statistics(), params=kwargs
        ).json()

    return r

stac_tile(url=None, collection=None, item=None, assets=None, bands=None, titiler_endpoint=None, **kwargs)

Get a tile layer from a single SpatialTemporal Asset Catalog (STAC) item.

Parameters:

Name Type Description Default
url str

HTTP URL to a STAC item, e.g., https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json

None
collection str

The Microsoft Planetary Computer STAC collection ID, e.g., landsat-8-c2-l2.

None
item str

The Microsoft Planetary Computer STAC item ID, e.g., LC08_L2SP_047027_20201204_02_T1.

None
assets str | list

The Microsoft Planetary Computer STAC asset ID, e.g., ["SR_B7", "SR_B5", "SR_B4"].

None
bands list

A list of band names, e.g., ["SR_B7", "SR_B5", "SR_B4"]

None
titiler_endpoint str

Titiler endpoint, e.g., "https://titiler.xyz", "https://planetarycomputer.microsoft.com/api/data/v1", "planetary-computer", "pc". Defaults to None.

None

Returns:

Type Description
str

Returns the STAC Tile layer URL.

Source code in leafmap/common.py
def stac_tile(
    url=None,
    collection=None,
    item=None,
    assets=None,
    bands=None,
    titiler_endpoint=None,
    **kwargs,
):

    """Get a tile layer from a single SpatialTemporal Asset Catalog (STAC) item.

    Args:
        url (str): HTTP URL to a STAC item, e.g., https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json
        collection (str): The Microsoft Planetary Computer STAC collection ID, e.g., landsat-8-c2-l2.
        item (str): The Microsoft Planetary Computer STAC item ID, e.g., LC08_L2SP_047027_20201204_02_T1.
        assets (str | list): The Microsoft Planetary Computer STAC asset ID, e.g., ["SR_B7", "SR_B5", "SR_B4"].
        bands (list): A list of band names, e.g., ["SR_B7", "SR_B5", "SR_B4"]
        titiler_endpoint (str, optional): Titiler endpoint, e.g., "https://titiler.xyz", "https://planetarycomputer.microsoft.com/api/data/v1", "planetary-computer", "pc". Defaults to None.

    Returns:
        str: Returns the STAC Tile layer URL.
    """

    if url is None and collection is None:
        raise ValueError("Either url or collection must be specified.")

    if collection is not None and titiler_endpoint is None:
        titiler_endpoint = "planetary-computer"

    if url is not None:
        kwargs["url"] = url
    if collection is not None:
        kwargs["collection"] = collection
    if item is not None:
        kwargs["item"] = item

    if "palette" in kwargs:
        kwargs["colormap_name"] = kwargs["palette"].lower()
        del kwargs["palette"]

    if isinstance(bands, list) and len(set(bands)) == 1:
        bands = bands[0]

    if isinstance(assets, list) and len(set(assets)) == 1:
        assets = assets[0]

    titiler_endpoint = check_titiler_endpoint(titiler_endpoint)

    if isinstance(titiler_endpoint, PlanetaryComputerEndpoint):
        if isinstance(bands, str):
            bands = bands.split(",")
        if isinstance(assets, str):
            assets = assets.split(",")
        if assets is None and (bands is not None):
            assets = bands
        else:
            kwargs["bidx"] = bands

        kwargs["assets"] = assets

        # if ("expression" in kwargs) and ("rescale" not in kwargs):
        #     stats = stac_stats(
        #         collection=collection,
        #         item=item,
        #         expression=kwargs["expression"],
        #         titiler_endpoint=titiler_endpoint,
        #     )
        #     kwargs[
        #         "rescale"
        #     ] = f"{stats[0]['percentile_2']},{stats[0]['percentile_98']}"

        # if ("asset_expression" in kwargs) and ("rescale" not in kwargs):
        #     stats = stac_stats(
        #         collection=collection,
        #         item=item,
        #         expression=kwargs["asset_expression"],
        #         titiler_endpoint=titiler_endpoint,
        #     )
        #     kwargs[
        #         "rescale"
        #     ] = f"{stats[0]['percentile_2']},{stats[0]['percentile_98']}"

        if (
            (assets is not None)
            and ("asset_expression" not in kwargs)
            and ("expression" not in kwargs)
            and ("rescale" not in kwargs)
        ):
            stats = stac_stats(
                collection=collection,
                item=item,
                assets=assets,
                titiler_endpoint=titiler_endpoint,
            )
            if "detail" not in stats:

                try:
                    percentile_2 = min([stats[s]["percentile_2"] for s in stats])
                    percentile_98 = max([stats[s]["percentile_98"] for s in stats])
                except:
                    percentile_2 = min(
                        [
                            stats[s][list(stats[s].keys())[0]]["percentile_2"]
                            for s in stats
                        ]
                    )
                    percentile_98 = max(
                        [
                            stats[s][list(stats[s].keys())[0]]["percentile_98"]
                            for s in stats
                        ]
                    )
                kwargs["rescale"] = f"{percentile_2},{percentile_98}"
            else:
                print(stats["detail"])  # When operation times out.

    else:
        if isinstance(bands, str):
            bands = bands.split(",")
        if isinstance(assets, str):
            assets = assets.split(",")

        if assets is None and (bands is not None):
            assets = bands
        else:
            kwargs["asset_bidx"] = bands
        kwargs["assets"] = assets

    TileMatrixSetId = "WebMercatorQuad"
    if "TileMatrixSetId" in kwargs.keys():
        TileMatrixSetId = kwargs["TileMatrixSetId"]
        kwargs.pop("TileMatrixSetId")

    if isinstance(titiler_endpoint, str):
        r = requests.get(
            f"{titiler_endpoint}/stac/{TileMatrixSetId}/tilejson.json",
            params=kwargs,
        ).json()
    else:
        r = requests.get(titiler_endpoint.url_for_stac_item(), params=kwargs).json()

    return r["tiles"][0]

streamlit_legend(html, width=None, height=None, scrolling=True)

Streamlit function to display a legend.

Parameters:

Name Type Description Default
html str

The HTML string of the legend.

required
width str

The width of the legend. Defaults to None.

None
height str

The height of the legend. Defaults to None.

None
scrolling bool

Whether to allow scrolling in the legend. Defaults to True.

True
Source code in leafmap/common.py
def streamlit_legend(html, width=None, height=None, scrolling=True):
    """Streamlit function to display a legend.

    Args:
        html (str): The HTML string of the legend.
        width (str, optional): The width of the legend. Defaults to None.
        height (str, optional): The height of the legend. Defaults to None.
        scrolling (bool, optional): Whether to allow scrolling in the legend. Defaults to True.

    """

    try:
        import streamlit.components.v1 as components

        components.html(html, width=width, height=height, scrolling=scrolling)

    except ImportError:
        print("Streamlit is not installed. Please run 'pip install streamlit'.")
        return

system_fonts(show_full_path=False)

Gets a list of system fonts

1
2
3
4
# Common font locations:
# Linux: /usr/share/fonts/TTF/
# Windows: C:/Windows/Fonts
# macOS:  System > Library > Fonts

Parameters:

Name Type Description Default
show_full_path bool

Whether to show the full path of each system font. Defaults to False.

False

Returns:

Type Description
list

A list of system fonts.

Source code in leafmap/common.py
def system_fonts(show_full_path=False):
    """Gets a list of system fonts

        # Common font locations:
        # Linux: /usr/share/fonts/TTF/
        # Windows: C:/Windows/Fonts
        # macOS:  System > Library > Fonts

    Args:
        show_full_path (bool, optional): Whether to show the full path of each system font. Defaults to False.

    Returns:
        list: A list of system fonts.
    """
    try:
        import matplotlib.font_manager

        font_list = matplotlib.font_manager.findSystemFonts(
            fontpaths=None, fontext="ttf"
        )
        font_list.sort()

        font_names = [os.path.basename(f) for f in font_list]
        font_names.sort()

        if show_full_path:
            return font_list
        else:
            return font_names

    except Exception as e:
        raise Exception(e)

temp_file_path(extension)

Returns a temporary file path.

Parameters:

Name Type Description Default
extension str

The file extension.

required

Returns:

Type Description
str

The temporary file path.

Source code in leafmap/common.py
def temp_file_path(extension):
    """Returns a temporary file path.

    Args:
        extension (str): The file extension.

    Returns:
        str: The temporary file path.
    """

    import tempfile
    import uuid

    if not extension.startswith("."):
        extension = "." + extension
    file_id = str(uuid.uuid4())
    file_path = os.path.join(tempfile.gettempdir(), f"{file_id}{extension}")

    return file_path

to_hex_colors(colors)

Adds # to a list of hex color codes.

Parameters:

Name Type Description Default
colors list

A list of hex color codes.

required

Returns:

Type Description
list

A list of hex color codes prefixed with #.

Source code in leafmap/common.py
def to_hex_colors(colors):
    """Adds # to a list of hex color codes.

    Args:
        colors (list): A list of hex color codes.

    Returns:
        list: A list of hex color codes prefixed with #.
    """
    result = all([len(color.strip()) == 6 for color in colors])
    if result:
        return ["#" + color.strip() for color in colors]
    else:
        return colors

update_package()

Updates the leafmap package from the leafmap GitHub repository without the need to use pip or conda. In this way, I don't have to keep updating pypi and conda-forge with every minor update of the package.

Source code in leafmap/common.py
def update_package():
    """Updates the leafmap package from the leafmap GitHub repository without the need to use pip or conda.
    In this way, I don't have to keep updating pypi and conda-forge with every minor update of the package.

    """

    try:
        download_dir = os.path.join(os.path.expanduser("~"), "Downloads")
        if not os.path.exists(download_dir):
            os.makedirs(download_dir)
        _clone_repo(out_dir=download_dir)

        pkg_dir = os.path.join(download_dir, "leafmap-master")
        work_dir = os.getcwd()
        os.chdir(pkg_dir)

        if shutil.which("pip") is None:
            cmd = "pip3 install ."
        else:
            cmd = "pip install ."

        os.system(cmd)
        os.chdir(work_dir)

        print(
            "\nPlease comment out 'leafmap.update_package()' and restart the kernel to take effect:\nJupyter menu -> Kernel -> Restart & Clear Output"
        )

    except Exception as e:
        raise Exception(e)

upload_to_imgur(in_gif)

Uploads an image to imgur.com

Parameters:

Name Type Description Default
in_gif str

The file path to the image.

required
Source code in leafmap/common.py
def upload_to_imgur(in_gif):
    """Uploads an image to imgur.com

    Args:
        in_gif (str): The file path to the image.
    """
    import subprocess

    pkg_name = "imgur-uploader"
    if not _is_tool(pkg_name):
        _check_install(pkg_name)

    try:
        IMGUR_API_ID = os.environ.get("IMGUR_API_ID", None)
        IMGUR_API_SECRET = os.environ.get("IMGUR_API_SECRET", None)
        credentials_path = os.path.join(
            os.path.expanduser("~"), ".config/imgur_uploader/uploader.cfg"
        )

        if (
            (IMGUR_API_ID is not None) and (IMGUR_API_SECRET is not None)
        ) or os.path.exists(credentials_path):

            proc = subprocess.Popen(["imgur-uploader", in_gif], stdout=subprocess.PIPE)
            for _ in range(0, 2):
                line = proc.stdout.readline()
                print(line.rstrip().decode("utf-8"))
            # while True:
            #     line = proc.stdout.readline()
            #     if not line:
            #         break
            #     print(line.rstrip().decode("utf-8"))
        else:
            print(
                "Imgur API credentials could not be found. Please check https://pypi.org/project/imgur-uploader/ for instructions on how to get Imgur API credentials"
            )
            return

    except Exception as e:
        raise Exception(e)

vector_col_names(filename, **kwargs)

Retrieves the column names of a vector attribute table.

Parameters:

Name Type Description Default
filename str

The input file path.

required

Returns:

Type Description
list

The list of column names.

Source code in leafmap/common.py
def vector_col_names(