hotfix for docs

docs/source/conf.py

@@ -22,11 +22,10 @@
 # sys.path.insert(0, os.path.abspath('../../urbanpy/utils'))
 import sphinx_rtd_theme
 
-
 # -- Project information -----------------------------------------------------
 
 project = "urbanpy"
-copyright = "2020, IADB"
+copyright = "2023, IADB"
 author = "Andres Regal, Claudio Ortega & Antonio Vasquez Brust"
 
 # The full version, including alpha/beta/rc tags
@@ -38,7 +37,11 @@
 # Add any Sphinx extension module names here, as strings. They can be
 # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
 # ones.
-extensions = ["sphinx.ext.autodoc", "sphinx_rtd_theme", "numpydoc"]
+extensions = [
+    "sphinx.ext.autodoc",
+    "sphinx_rtd_theme",
+    "numpydoc",
+]
 
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ["_templates"]

docs/source/index.rst

@@ -138,12 +138,6 @@ UrbanPy's original authors are Claudio Ortega
 (`socials <https://www.linkedin.com/in/claudioortega27/>`__) and Andrés
 Regal (`socials <https://www.linkedin.com/in/andrés-regal/>`__).
 
-.. toctree::
-   :maxdepth: 6
-   :caption: Contents:
-
-   modules
-
 \*Current support is tested on Linux Ubuntu 18.04 & Mac OS Catalina,
 coming soon we will test and support Windows 10.
 

urbanpy/download/download.py

@@ -1,20 +1,22 @@
+from typing import Optional, Tuple, Union
 from warnings import warn
-import requests
+
 import geopandas as gpd
-import pandas as pd
 import numpy as np
 import osmnx as ox
-from shapely.geometry import Polygon, MultiPolygon
+import pandas as pd
+import requests
+from geopandas import GeoDataFrame, GeoSeries
 from hdx.api.configuration import Configuration
 from hdx.data.dataset import Dataset
-from typing import Optional, Union, Tuple
 from pandas import DataFrame
-from geopandas import GeoDataFrame, GeoSeries
+from shapely.geometry import MultiPolygon, Polygon
+
 from urbanpy.utils import (
-    to_overpass_query,
-    overpass_to_gdf,
-    get_hdx_label,
     HDX_POPULATION_TYPES,
+    get_hdx_label,
+    overpass_to_gdf,
+    to_overpass_query,
 )
 
 __all__ = [
@@ -176,7 +178,8 @@ def overpass(
             'key1': 'v1',
             'key2': None
         }
-    mask:
+    mask: GeoDataFrame, GeoSeries, Polygon or MultiPolygon
+        Total bounds of mask to be used for the query.
 
     Returns
     -------
@@ -185,6 +188,7 @@ def overpass(
     df: DataFrame
         Relations metadata such as ID and tags. Returns None if 'type_of_data' other than 'relation'.
     """
+
     minx, miny, maxx, maxy = mask.total_bounds
     bbox_string = f"{minx},{miny},{maxx},{maxy}"
 
@@ -353,7 +357,6 @@ def get_hdx_dataset(resources_df: DataFrame, ids: Union[int, list]) -> DataFrame
     ----------
     resources_df: pd.DataFrame
         Resources dataframe from returned by search_hdx_dataset
-
     ids: int or list
         IDs in the resources dataframe
 
@@ -373,7 +376,9 @@ def get_hdx_dataset(resources_df: DataFrame, ids: Union[int, list]) -> DataFrame
     -18.335694 | -70.387361	| 11.318147	      | 12.099885
     -18.335417 | -70.394028	| 11.318147	      | 12.099885
     -18.335139 | -70.394306	| 11.318147	      | 12.099885
+
     """
+
     urls = resources_df.loc[ids, "url"]
 
     if isinstance(ids, list) and len(ids) > 1:

urbanpy/utils/utils.py

@@ -1,14 +1,15 @@
+from math import ceil
+from typing import Optional, Tuple, Union
+
 import geopandas as gpd
-import pandas as pd
 import numpy as np
+import pandas as pd
+from geopandas import GeoDataFrame, GeoSeries
 from h3 import h3
-from math import ceil
-from shapely.geometry import Polygon, MultiPolygon
+from pandas import DataFrame
+from shapely.geometry import MultiPolygon, Polygon
 from shapely.validation import make_valid
 from sklearn.neighbors import BallTree
-from typing import Optional, Union, Tuple
-from pandas import DataFrame
-from geopandas import GeoDataFrame, GeoSeries
 
 __all__ = [
     "swap_xy",
@@ -176,22 +177,20 @@ def create_duration_labels(durations):
 
     Parameters
     ----------
-
     durations: Pandas Series
         Series containing trip durations in minutes.
 
     Returns
     -------
-
     custom_bins: list
         List of numbers with the inputs for the bins parameter of pd.cut function
-
     custom_labels: list
         List of numbers with the inputs for the labels parameter of pd.cut function
-
     """
     default_bins = [0, 15, 30, 45, 60, 90, 120]
-    default_labels = [f"{default_bins[i]}-{default_bins[i+1]}" for i in range(len(default_bins) - 1)]
+    default_labels = [
+        f"{default_bins[i]}-{default_bins[i+1]}" for i in range(len(default_bins) - 1)
+    ]
     default_labels.append(f">{default_bins[-1]}")
 
     bins_ = default_bins.copy()
@@ -346,7 +345,6 @@ def overpass_to_gdf(
     ov_keys: list. Optional
         Unique OSM keys used in Overpass query (e.g. "amenity", "shop", etc) to fill "poi_type" df column.
 
-
     Returns
     -------
     gdf: GeoDataFrame