Internals Reference#

This is the complete OSMnx internals reference for developers, including private internal modules and functions. If you are instead looking for a user guide to OSMnx’s public API, see the User Reference.

osmnx._api module#

Expose most common parts of public API directly in package namespace.

osmnx.bearing module#

Calculate graph edge bearings.

osmnx.bearing._bearings_distribution(Gu, num_bins, min_length=0, weight=None)

Compute distribution of bearings across evenly spaced bins.

Prevents bin-edge effects around common values like 0 degrees and 90 degrees by initially creating twice as many bins as desired, then merging them in pairs. For example, if num_bins=36 is provided, then each bin will represent 10 degrees around the compass, with the first bin representing 355 degrees to 5 degrees.

Parameters:

Gu (networkx.MultiGraph) – undirected, unprojected graph with bearing attributes on each edge
num_bins (int) – number of bins for the bearings histogram
min_length (float) – ignore edges with length attributes less than min_length; useful to ignore the noise of many very short edges
weight (string) – if not None, weight edges’ bearings by this (non-null) edge attribute. for example, if “length” is provided, this will return 1 bearing observation per meter per street, which could result in a very large bearings array.

Returns:

bin_counts, bin_edges – counts of bearings per bin and the bins edges

Return type:

tuple of numpy.array

osmnx.bearing._extract_edge_bearings(Gu, min_length=0, weight=None)

Extract undirected graph’s bidirectional edge bearings.

For example, if an edge has a bearing of 90 degrees then we will record bearings of both 90 degrees and 270 degrees for this edge.

Parameters:

Gu (networkx.MultiGraph) – undirected, unprojected graph with bearing attributes on each edge
min_length (float) – ignore edges with length attributes less than min_length; useful to ignore the noise of many very short edges
weight (string) – if not None, weight edges’ bearings by this (non-null) edge attribute. for example, if “length” is provided, this will return 1 bearing observation per meter per street, which could result in a very large bearings array.

Returns:

bearings – the graph’s bidirectional edge bearings

Return type:

numpy.array

osmnx.bearing.add_edge_bearings(G, precision=None)

Add compass bearing attributes to all graph edges.

Vectorized function to calculate (initial) bearing from origin node to destination node for each edge in a directed, unprojected graph then add these bearings as new edge attributes. Bearing represents angle in degrees (clockwise) between north and the geodesic line from the origin node to the destination node. Ignores self-loop edges as their bearings are undefined.

Parameters:

G (networkx.MultiDiGraph) – unprojected graph
precision (int) – deprecated, do not use

Returns:

G – graph with edge bearing attributes

Return type:

networkx.MultiDiGraph

osmnx.bearing.calculate_bearing(lat1, lon1, lat2, lon2)

Calculate the compass bearing(s) between pairs of lat-lon points.

Vectorized function to calculate initial bearings between two points’ coordinates or between arrays of points’ coordinates. Expects coordinates in decimal degrees. Bearing represents the clockwise angle in degrees between north and the geodesic line from (lat1, lon1) to (lat2, lon2).

Parameters:

lat1 (float or numpy.array of float) – first point’s latitude coordinate
lon1 (float or numpy.array of float) – first point’s longitude coordinate
lat2 (float or numpy.array of float) – second point’s latitude coordinate
lon2 (float or numpy.array of float) – second point’s longitude coordinate

Returns:

bearing – the bearing(s) in decimal degrees

Return type:

float or numpy.array of float

osmnx.bearing.orientation_entropy(Gu, num_bins=36, min_length=0, weight=None)

Calculate undirected graph’s orientation entropy.

Orientation entropy is the entropy of its edges’ bidirectional bearings across evenly spaced bins. Ignores self-loop edges as their bearings are undefined.

For more info see: Boeing, G. 2019. “Urban Spatial Order: Street Network Orientation, Configuration, and Entropy.” Applied Network Science, 4 (1), 67. https://doi.org/10.1007/s41109-019-0189-1

Parameters:

Gu (networkx.MultiGraph) – undirected, unprojected graph with bearing attributes on each edge
num_bins (int) – number of bins; for example, if num_bins=36 is provided, then each bin will represent 10 degrees around the compass
min_length (float) – ignore edges with length attributes less than min_length; useful to ignore the noise of many very short edges
weight (string) – if not None, weight edges’ bearings by this (non-null) edge attribute. for example, if “length” is provided, this will return 1 bearing observation per meter per street, which could result in a very large bearings array.

Returns:

entropy – the graph’s orientation entropy

Return type:

float

osmnx.bearing.plot_orientation(Gu, num_bins=36, min_length=0, weight=None, ax=None, figsize=(5, 5), area=True, color='#003366', edgecolor='k', linewidth=0.5, alpha=0.7, title=None, title_y=1.05, title_font=None, xtick_font=None)

Do not use: deprecated.

The plot_orientation function moved to the plot module. Calling it via the bearing module will raise an error starting in the v2.0.0 release.

Parameters:

Gu (networkx.MultiGraph) – deprecated, do not use
num_bins (int) – deprecated, do not use
min_length (float) – deprecated, do not use
weight (string) – deprecated, do not use
ax (matplotlib.axes.PolarAxesSubplot) – deprecated, do not use
figsize (tuple) – deprecated, do not use
area (bool) – deprecated, do not use
color (string) – deprecated, do not use
edgecolor (string) – deprecated, do not use
linewidth (float) – deprecated, do not use
alpha (float) – deprecated, do not use
title (string) – deprecated, do not use
title_y (float) – deprecated, do not use
title_font (dict) – deprecated, do not use
xtick_font (dict) – deprecated, do not use

Returns:

fig, ax – matplotlib figure, axis

Return type:

tuple

osmnx.convert module#

Convert spatial graphs to/from different data types.

osmnx.convert._is_duplicate_edge(data1, data2)

Check if two graph edge data dicts have the same osmid and geometry.

Parameters:

data1 (dict) – the first edge’s data
data2 (dict) – the second edge’s data

Returns:

is_dupe

Return type:

bool

osmnx.convert._is_same_geometry(ls1, ls2)

Determine if two LineString geometries are the same (in either direction).

Check both the normal and reversed orders of their constituent points.

Parameters:

ls1 (shapely.geometry.LineString) – the first LineString geometry
ls2 (shapely.geometry.LineString) – the second LineString geometry

Return type:

bool

osmnx.convert._update_edge_keys(G)

Increment key of one edge of parallel edges that differ in geometry.

For example, two streets from u to v that bow away from each other as separate streets, rather than opposite direction edges of a single street. Increment one of these edge’s keys so that they do not match across u, v, k or v, u, k so we can add both to an undirected MultiGraph.

Parameters:: G (networkx.MultiDiGraph) – input graph
Returns:: G
Return type:: networkx.MultiDiGraph

osmnx.convert.graph_from_gdfs(gdf_nodes, gdf_edges, graph_attrs=None)

Convert node and edge GeoDataFrames to a MultiDiGraph.

This function is the inverse of graph_to_gdfs and is designed to work in conjunction with it.

However, you can convert arbitrary node and edge GeoDataFrames as long as 1) gdf_nodes is uniquely indexed by osmid, 2) gdf_nodes contains x and y coordinate columns representing node geometries, 3) gdf_edges is uniquely multi-indexed by u, v, key (following normal MultiDiGraph structure). This allows you to load any node/edge shapefiles or GeoPackage layers as GeoDataFrames then convert them to a MultiDiGraph for graph analysis. Note that any geometry attribute on gdf_nodes is discarded since x and y provide the necessary node geometry information instead.

Parameters:

gdf_nodes (geopandas.GeoDataFrame) – GeoDataFrame of graph nodes uniquely indexed by osmid
gdf_edges (geopandas.GeoDataFrame) – GeoDataFrame of graph edges uniquely multi-indexed by u, v, key
graph_attrs (dict) – the new G.graph attribute dict. if None, use crs from gdf_edges as the only graph-level attribute (gdf_edges must have crs attribute set)

Returns:

Return type:

networkx.MultiDiGraph

osmnx.convert.graph_to_gdfs(G, nodes=True, edges=True, node_geometry=True, fill_edge_geometry=True)

Convert a MultiDiGraph to node and/or edge GeoDataFrames.

This function is the inverse of graph_from_gdfs.

Parameters:

G (networkx.MultiDiGraph) – input graph
nodes (bool) – if True, convert graph nodes to a GeoDataFrame and return it
edges (bool) – if True, convert graph edges to a GeoDataFrame and return it
node_geometry (bool) – if True, create a geometry column from node x and y attributes
fill_edge_geometry (bool) – if True, fill in missing edge geometry fields using nodes u and v

Returns:

gdf_nodes or gdf_edges or tuple of (gdf_nodes, gdf_edges). gdf_nodes is indexed by osmid and gdf_edges is multi-indexed by u, v, key following normal MultiDiGraph structure.

Return type:

geopandas.GeoDataFrame or tuple

osmnx.convert.to_digraph(G, weight='length')

Convert MultiDiGraph to DiGraph.

Chooses between parallel edges by minimizing weight attribute value. Note: see also to_undirected to convert MultiDiGraph to MultiGraph.

Parameters:

G (networkx.MultiDiGraph) – input graph
weight (string) – attribute value to minimize when choosing between parallel edges

Return type:

networkx.DiGraph

osmnx.convert.to_undirected(G)

Convert MultiDiGraph to undirected MultiGraph.

Maintains parallel edges only if their geometries differ. Note: see also to_digraph to convert MultiDiGraph to DiGraph.

Parameters:: G (networkx.MultiDiGraph) – input graph
Return type:: networkx.MultiGraph

osmnx.distance module#

Calculate distances and find nearest node/edge(s) to point(s).

osmnx.distance.add_edge_lengths(G, precision=None, edges=None)

Add length attribute (in meters) to each edge.

Vectorized function to calculate great-circle distance between each edge’s incident nodes. Ensure graph is in unprojected coordinates, and unsimplified to get accurate distances.

Note: this function is run by all the graph.graph_from_x functions automatically to add length attributes to all edges. It calculates edge lengths as the great-circle distance from node u to node v. When OSMnx automatically runs this function upon graph creation, it does it before simplifying the graph: thus it calculates the straight-line lengths of edge segments that are themselves all straight. Only after simplification do edges take on a (potentially) curvilinear geometry. If you wish to calculate edge lengths later, you are calculating straight-line distances which necessarily ignore the curvilinear geometry. You only want to run this function on a graph with all straight edges (such as is the case with an unsimplified graph).

Parameters:

G (networkx.MultiDiGraph) – unprojected, unsimplified input graph
precision (int) – deprecated, do not use
edges (tuple) – tuple of (u, v, k) tuples representing subset of edges to add length attributes to. if None, add lengths to all edges.

Returns:

G – graph with edge length attributes

Return type:

networkx.MultiDiGraph

osmnx.distance.euclidean(y1, x1, y2, x2)

Calculate Euclidean distances between pairs of points.

Vectorized function to calculate the Euclidean distance between two points’ coordinates or between arrays of points’ coordinates. For accurate results, use projected coordinates rather than decimal degrees.

Parameters:

y1 (float or numpy.array of float) – first point’s y coordinate
x1 (float or numpy.array of float) – first point’s x coordinate
y2 (float or numpy.array of float) – second point’s y coordinate
x2 (float or numpy.array of float) – second point’s x coordinate

Returns:

dist – distance from each (x1, y1) to each (x2, y2) in coordinates’ units

Return type:

float or numpy.array of float

osmnx.distance.euclidean_dist_vec(y1, x1, y2, x2)

Do not use, deprecated.

The euclidean_dist_vec function has been renamed euclidean. Calling euclidean_dist_vec will raise an error in the v2.0.0 release.

Parameters:

y1 (float or numpy.array of float) – first point’s y coordinate
x1 (float or numpy.array of float) – first point’s x coordinate
y2 (float or numpy.array of float) – second point’s y coordinate
x2 (float or numpy.array of float) – second point’s x coordinate

Returns:

dist – distance from each (x1, y1) to each (x2, y2) in coordinates’ units

Return type:

float or numpy.array of float

osmnx.distance.great_circle(lat1, lon1, lat2, lon2, earth_radius=6371009)

Calculate great-circle distances between pairs of points.

Vectorized function to calculate the great-circle distance between two points’ coordinates or between arrays of points’ coordinates using the haversine formula. Expects coordinates in decimal degrees.

Parameters:

lat1 (float or numpy.array of float) – first point’s latitude coordinate
lon1 (float or numpy.array of float) – first point’s longitude coordinate
lat2 (float or numpy.array of float) – second point’s latitude coordinate
lon2 (float or numpy.array of float) – second point’s longitude coordinate
earth_radius (float) – earth’s radius in units in which distance will be returned (default is meters)

Returns:

dist – distance from each (lat1, lon1) to each (lat2, lon2) in units of earth_radius

Return type:

float or numpy.array of float

osmnx.distance.great_circle_vec(lat1, lng1, lat2, lng2, earth_radius=6371009)

Do not use, deprecated.

The great_circle_vec function has been renamed great_circle. Calling great_circle_vec will raise an error in the v2.0.0 release.

Parameters:

lat1 (float or numpy.array of float) – first point’s latitude coordinate
lng1 (float or numpy.array of float) – first point’s longitude coordinate
lat2 (float or numpy.array of float) – second point’s latitude coordinate
lng2 (float or numpy.array of float) – second point’s longitude coordinate
earth_radius (float) – earth’s radius in units in which distance will be returned (default is meters)

Returns:

dist – distance from each (lat1, lng1) to each (lat2, lng2) in units of earth_radius

Return type:

float or numpy.array of float

osmnx.distance.k_shortest_paths(G, orig, dest, k, weight='length')

Do not use, deprecated.

The k_shortest_paths function has moved to the routing module. Calling it via the distance module will raise an error in the v2.0.0 release.

Parameters:

G (networkx.MultiDiGraph) – input graph
orig (int) – origin node ID
dest (int) – destination node ID
k (int) – number of shortest paths to solve
weight (string) – edge attribute to minimize when solving shortest paths. default is edge length in meters.

Yields:

path (list) – a generator of k shortest paths ordered by total weight. each path is a list of node IDs.

osmnx.distance.nearest_edges(G, X, Y, interpolate=None, return_dist=False)

Find the nearest edge to a point or to each of several points.

If X and Y are single coordinate values, this will return the nearest edge to that point. If X and Y are lists of coordinate values, this will return the nearest edge to each point. This function uses an R-tree spatial index and minimizes the euclidean distance from each point to the possible matches. For accurate results, use a projected graph and points.

Parameters:

G (networkx.MultiDiGraph) – graph in which to find nearest edges
X (float or list) – points’ x (longitude) coordinates, in same CRS/units as graph and containing no nulls
Y (float or list) – points’ y (latitude) coordinates, in same CRS/units as graph and containing no nulls
interpolate (float) – deprecated, do not use
return_dist (bool) – optionally also return distance between points and nearest edges

Returns:

ne or (ne, dist) – nearest edges as (u, v, key) or optionally a tuple where dist contains distances between the points and their nearest edges

Return type:

tuple or list

osmnx.distance.nearest_nodes(G, X, Y, return_dist=False)

Find the nearest node to a point or to each of several points.

If X and Y are single coordinate values, this will return the nearest node to that point. If X and Y are lists of coordinate values, this will return the nearest node to each point.

If the graph is projected, this uses a k-d tree for euclidean nearest neighbor search, which requires that scipy is installed as an optional dependency. If it is unprojected, this uses a ball tree for haversine nearest neighbor search, which requires that scikit-learn is installed as an optional dependency.

Parameters:

G (networkx.MultiDiGraph) – graph in which to find nearest nodes
X (float or list) – points’ x (longitude) coordinates, in same CRS/units as graph and containing no nulls
Y (float or list) – points’ y (latitude) coordinates, in same CRS/units as graph and containing no nulls
return_dist (bool) – optionally also return distance between points and nearest nodes

Returns:

nn or (nn, dist) – nearest node IDs or optionally a tuple where dist contains distances between the points and their nearest nodes

Return type:

int/list or tuple

osmnx.distance.shortest_path(G, orig, dest, weight='length', cpus=1)

Do not use, deprecated.

The shortest_path function has moved to the routing module. Calling it via the distance module will raise an error in the v2.0.0 release.

Parameters:

G (networkx.MultiDiGraph) – input graph
orig (int or list) – origin node ID, or a list of origin node IDs
dest (int or list) – destination node ID, or a list of destination node IDs
weight (string) – edge attribute to minimize when solving shortest path
cpus (int) – how many CPU cores to use; if None, use all available

Returns:

path – list of node IDs constituting the shortest path, or, if orig and dest are lists, then a list of path lists

Return type:

list

osmnx._downloader module#

Handle HTTP requests to web APIs.

osmnx._downloader._config_dns(url)

Force socket.getaddrinfo to use IP address instead of hostname.

Resolves the URL’s domain to an IP address so that we use the same server for both 1) checking the necessary pause duration and 2) sending the query itself even if there is round-robin redirecting among multiple server machines on the server-side. Mutates the getaddrinfo function so it uses the same IP address everytime it finds the hostname in the URL.

For example, the server overpass-api.de just redirects to one of the other servers (currently gall.openstreetmap.de and lambert.openstreetmap.de). So if we check the status endpoint of overpass-api.de, we may see results for server gall, but when we submit the query itself it gets redirected to server lambert. This could result in violating server lambert’s slot management timing.

Parameters:: url (string) – the URL to consistently resolve the IP address of
Return type:: None

osmnx._downloader._get_http_headers(user_agent=None, referer=None, accept_language=None)

Update the default requests HTTP headers with OSMnx info.

Parameters:

user_agent (string) – the user agent string, if None will set with OSMnx default
referer (string) – the referer string, if None will set with OSMnx default
accept_language (string) – make accept-language explicit e.g. for consistent nominatim result sorting

Returns:

headers

Return type:

dict

osmnx._downloader._hostname_from_url(url)

Extract the hostname (domain) from a URL.

Parameters:: url (string) – the url from which to extract the hostname
Returns:: hostname – the extracted hostname (domain)
Return type:: string

osmnx._downloader._parse_response(response)

Parse JSON from a requests response and log the details.

Parameters:: response (requests.response) – the response object
Returns:: response_json
Return type:: dict

osmnx._downloader._resolve_host_via_doh(hostname)

Resolve hostname to IP address via Google’s public DNS-over-HTTPS API.

Necessary fallback as socket.gethostbyname will not always work when using a proxy. See https://developers.google.com/speed/public-dns/docs/doh/json If the user has set settings.doh_url_template=None or if resolution fails (e.g., due to local network blocking DNS-over-HTTPS) the hostname itself will be returned instead. Note that this means that server slot management may be violated: see _config_dns documentation for details.

Parameters:: hostname (string) – the hostname to consistently resolve the IP address of
Returns:: ip_address – resolved IP address of host, or hostname itself if resolution failed
Return type:: string

osmnx._downloader._retrieve_from_cache(url, check_remark=True)

Retrieve a HTTP response JSON object from the cache, if it exists.

Parameters:

url (string) – the URL of the request
check_remark (string) – if True, only return filepath if cached response does not have a remark key indicating a server warning

Returns:

response_json – cached response for url if it exists in the cache, otherwise None

Return type:

dict

osmnx._downloader._save_to_cache(url, response_json, ok)

Save a HTTP response JSON object to a file in the cache folder.

Function calculates the checksum of url to generate the cache file’s name. If the request was sent to server via POST instead of GET, then URL should be a GET-style representation of request. Response is only saved to a cache file if settings.use_cache is True, response_json is not None, and ok is True.

Users should always pass OrderedDicts instead of dicts of parameters into request functions, so the parameters remain in the same order each time, producing the same URL string, and thus the same hash. Otherwise the cache will eventually contain multiple saved responses for the same request because the URL’s parameters appeared in a different order each time.

Parameters:

url (string) – the URL of the request
response_json (dict) – the JSON response
ok (bool) – requests response.ok value

Return type:

None

osmnx._downloader._url_in_cache(url)

Determine if a URL’s response exists in the cache.

Calculates the checksum of url to determine the cache file’s name.

Parameters:: url (string) – the URL to look for in the cache
Returns:: filepath – path to cached response for url if it exists, otherwise None
Return type:: pathlib.Path

osmnx.elevation module#

Add node elevations from raster files or web APIs, and calculate edge grades.

osmnx.elevation._elevation_request(url, pause)

Send a HTTP GET request to Google Maps-style Elevation API.

Parameters:

url (string) – URL for API endpoint populated with request data
pause (float) – how long to pause in seconds before request

Returns:

response_json

Return type:

dict

osmnx.elevation._query_raster(nodes, filepath, band)

Query a raster for values at coordinates in a DataFrame’s x/y columns.

Parameters:

nodes (pandas.DataFrame) – DataFrame indexed by node ID and with two columns: x and y
filepath (string or pathlib.Path) – path to the raster file or VRT to query
band (int) – which raster band to query

Returns:

nodes_values – zipped node IDs and corresponding raster values

Return type:

zip

osmnx.elevation.add_edge_grades(G, add_absolute=True, precision=None)

Add grade attribute to each graph edge.

Vectorized function to calculate the directed grade (ie, rise over run) for each edge in the graph and add it to the edge as an attribute. Nodes must already have elevation attributes to use this function.

See also the add_node_elevations_raster and add_node_elevations_google functions.

Parameters:

G (networkx.MultiDiGraph) – input graph with elevation node attribute
add_absolute (bool) – if True, also add absolute value of grade as grade_abs attribute
precision (int) – deprecated, do not use

Returns:

G – graph with edge grade (and optionally grade_abs) attributes

Return type:

networkx.MultiDiGraph

osmnx.elevation.add_node_elevations_google(G, api_key=None, batch_size=350, pause=0, max_locations_per_batch=None, precision=None, url_template=None)

Add an elevation (meters) attribute to each node using a web service.

By default, this uses the Google Maps Elevation API but you can optionally use an equivalent API with the same interface and response format, such as Open Topo Data, via the settings module’s elevation_url_template. The Google Maps Elevation API requires an API key but other providers may not.

For a free local alternative see the add_node_elevations_raster function. See also the add_edge_grades function.

Parameters:

G (networkx.MultiDiGraph) – input graph
api_key (string) – a valid API key, can be None if the API does not require a key
batch_size (int) – max number of coordinate pairs to submit in each API call (if this is too high, the server will reject the request because its character limit exceeds the max allowed)
pause (float) – time to pause between API calls, which can be increased if you get rate limited
max_locations_per_batch (int) – deprecated, do not use
precision (int) – deprecated, do not use
url_template (string) – deprecated, do not use

Returns:

G – graph with node elevation attributes

Return type:

networkx.MultiDiGraph

osmnx.elevation.add_node_elevations_raster(G, filepath, band=1, cpus=None)

Add elevation attribute to each node from local raster file(s).

If filepath is a list of paths, this will generate a virtual raster composed of the files at those paths as an intermediate step.

osmnx._errors module#

Define custom errors and exceptions.

exception osmnx._errors.CacheOnlyInterruptError: Exception for settings.cache_only_mode=True interruption.

exception osmnx._errors.GraphSimplificationError: Exception for a problem with graph simplification.

exception osmnx._errors.InsufficientResponseError: Exception for empty or too few results in server response.

exception osmnx._errors.ResponseStatusCodeError: Exception for an unhandled server response status code.

osmnx.features module#

Download OpenStreetMap geospatial features’ geometries and attributes.

Retrieve points of interest, building footprints, transit lines/stops, or any other map features from OSM, including their geometries and attribute data, then construct a GeoDataFrame of them. You can use this module to query for nodes, ways, and relations (the latter of type “multipolygon” or “boundary” only) by passing a dictionary of desired OSM tags.

For more details, see https://wiki.openstreetmap.org/wiki/Map_features and https://wiki.openstreetmap.org/wiki/Elements

Refer to the Getting Started guide for usage limitations.

osmnx.features._assemble_multipolygon_component_polygons(element, geometries)

Assemble a MultiPolygon from its component LineStrings and Polygons.

The OSM wiki suggests an algorithm for assembling multipolygon geometries https://wiki.openstreetmap.org/wiki/Relation:multipolygon/Algorithm. This method takes a simpler approach relying on the accurate tagging of component ways with ‘inner’ and ‘outer’ roles as required on this page https://wiki.openstreetmap.org/wiki/Relation:multipolygon.

Parameters:

element (dict) – element type “relation” from overpass response JSON
geometries (dict) – dict containing all linestrings and polygons generated from OSM ways

Returns:

geometry – a single MultiPolygon object

Return type:

shapely.geometry.MultiPolygon

osmnx.features._buffer_invalid_geometries(gdf)

Buffer any invalid geometries remaining in the GeoDataFrame.

Invalid geometries in the GeoDataFrame (which may accurately reproduce invalid geometries in OpenStreetMap) can cause the filtering to the query polygon and other subsequent geometric operations to fail. This function logs the ids of the invalid geometries and applies a buffer of zero to try to make them valid.

Note: the resulting geometries may differ from the originals - please check them against OpenStreetMap

Parameters:: gdf (geopandas.GeoDataFrame) – a GeoDataFrame with possibly invalid geometries
Returns:: gdf – the GeoDataFrame with .buffer(0) applied to invalid geometries
Return type:: geopandas.GeoDataFrame

osmnx.features._create_gdf(response_jsons, polygon, tags)

Parse JSON responses from the Overpass API to a GeoDataFrame.

Note: the polygon and tags arguments can both be None and the GeoDataFrame will still be created but it won’t be filtered at the end i.e. the final GeoDataFrame will contain all tagged features in the response_jsons.

Parameters:

response_jsons (list) – list of JSON responses from from the Overpass API
polygon (shapely.geometry.Polygon) – geographic boundary used for filtering the final GeoDataFrame
tags (dict) – dict of tags used for filtering the final GeoDataFrame

Returns:

gdf – GeoDataFrame of features and their associated tags

Return type:

geopandas.GeoDataFrame

osmnx.features._filter_gdf_by_polygon_and_tags(gdf, polygon, tags)

Filter the GeoDataFrame to the requested bounding polygon and tags.

Filters GeoDataFrame to query polygon and tags. Removes columns of all NaNs (that held values only in rows removed by the filters). Resets the index of GeoDataFrame, writing it into a new column called ‘unique_id’.

Parameters:

gdf (geopandas.GeoDataFrame) – the GeoDataFrame to filter
polygon (shapely.geometry.Polygon) – polygon defining the boundary of the requested area
tags (dict) – the tags requested

Returns:

gdf – final filtered GeoDataFrame

Return type:

geopandas.GeoDataFrame

osmnx.features._is_closed_way_a_polygon(element, polygon_features={'aeroway': {'polygon': 'blocklist', 'values': ['taxiway']}, 'amenity': {'polygon': 'all'}, 'area': {'polygon': 'all'}, 'area:highway': {'polygon': 'all'}, 'barrier': {'polygon': 'passlist', 'values': ['city_wall', 'ditch', 'hedge', 'retaining_wall', 'spikes']}, 'boundary': {'polygon': 'all'}, 'building': {'polygon': 'all'}, 'building:part': {'polygon': 'all'}, 'craft': {'polygon': 'all'}, 'golf': {'polygon': 'all'}, 'highway': {'polygon': 'passlist', 'values': ['services', 'rest_area', 'escape', 'elevator']}, 'historic': {'polygon': 'all'}, 'indoor': {'polygon': 'all'}, 'landuse': {'polygon': 'all'}, 'leisure': {'polygon': 'all'}, 'man_made': {'polygon': 'blocklist', 'values': ['cutline', 'embankment', 'pipeline']}, 'military': {'polygon': 'all'}, 'natural': {'polygon': 'blocklist', 'values': ['coastline', 'cliff', 'ridge', 'arete', 'tree_row']}, 'office': {'polygon': 'all'}, 'place': {'polygon': 'all'}, 'power': {'polygon': 'passlist', 'values': ['plant', 'substation', 'generator', 'transformer']}, 'public_transport': {'polygon': 'all'}, 'railway': {'polygon': 'passlist', 'values': ['station', 'turntable', 'roundhouse', 'platform']}, 'ruins': {'polygon': 'all'}, 'shop': {'polygon': 'all'}, 'tourism': {'polygon': 'all'}, 'waterway': {'polygon': 'passlist', 'values': ['riverbank', 'dock', 'boatyard', 'dam']}})

Determine whether a closed OSM way represents a Polygon, not a LineString.

Closed OSM ways may represent LineStrings (e.g. a roundabout or hedge round a field) or Polygons (e.g. a building footprint or land use area) depending on the tags applied to them.

The starting assumption is that it is not a polygon, however any polygon type tagging will return a polygon unless explicitly tagged with area:no.

It is possible for a single closed OSM way to have both LineString and Polygon type tags (e.g. both barrier=fence and landuse=agricultural). OSMnx will return a single Polygon for elements tagged in this way. For more information see: https://wiki.openstreetmap.org/wiki/One_feature,_one_OSM_element)

Parameters:

element (dict) – closed element type “way” from overpass response JSON
polygon_features (dict) – dict of tag keys with associated values and blocklist/passlist

Returns:

is_polygon – True if the tags are for a polygon type geometry

Return type:

bool

osmnx.features._parse_node_to_coords(element)

Parse coordinates from a node in the overpass response.

The coords are only used to create LineStrings and Polygons.

Parameters:: element (dict) – element type “node” from overpass response JSON
Returns:: coords – dict of latitude/longitude coordinates
Return type:: dict

osmnx.features._parse_node_to_point(element)

Parse point from a tagged node in the overpass response.

The points are geometries in their own right.

Parameters:: element (dict) – element type “node” from overpass response JSON
Returns:: point – dict of OSM ID, OSM element type, tags and geometry
Return type:: dict

osmnx.features._parse_relation_to_multipolygon(element, geometries)

Parse multipolygon from OSM relation (type:MultiPolygon).

See more information about relations from OSM documentation: https://wiki.openstreetmap.org/wiki/Relation

Parameters:

element (dict) – element type “relation” from overpass response JSON
geometries (dict) – dict containing all linestrings and polygons generated from OSM ways

Returns:

multipolygon – dict of tags and geometry for a single multipolygon

Return type:

dict

osmnx.features._parse_way_to_linestring_or_polygon(element, coords)

Parse open LineString, closed LineString or Polygon from OSM ‘way’.

Please see https://wiki.openstreetmap.org/wiki/Overpass_turbo/Polygon_Features for more information on which tags should be parsed to polygons

Parameters:

element (dict) – element type “way” from overpass response JSON
coords (dict) – dict of node IDs and their latitude/longitude coordinates

Returns:

linestring_or_polygon – dict of OSM ID, OSM element type, nodes, tags and geometry

Return type:

dict

osmnx.features._subtract_inner_polygons_from_outer_polygons(element, outer_polygons, inner_polygons)

Subtract inner polygons from outer polygons.

Creates a Polygon or MultiPolygon with holes.

Parameters:

element (dict) – element type “relation” from overpass response JSON
outer_polygons (list) – list of outer polygons that are part of a multipolygon
inner_polygons (list) – list of inner polygons that are part of a multipolygon

Returns:

geometry – a single Polygon or MultiPolygon

Return type:

shapely.geometry.Polygon or shapely.geometry.MultiPolygon

osmnx.features.features_from_address(address, tags, dist=1000)

Create GeoDataFrame of OSM features within some distance N, S, E, W of address.

You can use the settings module to retrieve a snapshot of historical OSM data as of a certain date, or to configure the Overpass server timeout, memory allocation, and other custom settings.

For more details, see: https://wiki.openstreetmap.org/wiki/Map_features

Parameters:

address (string) – the address to geocode and use as the central point around which to get the features
tags (dict) – Dict of tags used for finding elements in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
dist (numeric) – distance in meters

Returns:

gdf

Return type:

geopandas.GeoDataFrame

osmnx.features.features_from_bbox(north=None, south=None, east=None, west=None, bbox=None, tags=None)

Create a GeoDataFrame of OSM features within a N, S, E, W bounding box.

You can use the settings module to retrieve a snapshot of historical OSM data as of a certain date, or to configure the Overpass server timeout, memory allocation, and other custom settings.

For more details, see: https://wiki.openstreetmap.org/wiki/Map_features

Parameters:

north (float) – deprecated, do not use
south (float) – deprecated, do not use
east (float) – deprecated, do not use
west (float) – deprecated, do not use
bbox (tuple of floats) – bounding box as (north, south, east, west)
tags (dict) – Dict of tags used for finding elements in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.

Returns:

gdf

Return type:

geopandas.GeoDataFrame

osmnx.features.features_from_place(query, tags, which_result=None, buffer_dist=None)

Create GeoDataFrame of OSM features within boundaries of some place(s).

The query must be geocodable and OSM must have polygon boundaries for the geocode result. If OSM does not have a polygon for this place, you can instead get features within it using the features_from_address function, which geocodes the place name to a point and gets the features within some distance of that point.

If OSM does have polygon boundaries for this place but you’re not finding it, try to vary the query string, pass in a structured query dict, or vary the which_result argument to use a different geocode result. If you know the OSM ID of the place, you can retrieve its boundary polygon using the geocode_to_gdf function, then pass it to the features_from_polygon function.

You can use the settings module to retrieve a snapshot of historical OSM data as of a certain date, or to configure the Overpass server timeout, memory allocation, and other custom settings.

For more details, see: https://wiki.openstreetmap.org/wiki/Map_features

Parameters:

query (string or dict or list) – the query or queries to geocode to get place boundary polygon(s)
tags (dict) – Dict of tags used for finding elements in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
which_result (int) – which geocoding result to use. if None, auto-select the first (Multi)Polygon or raise an error if OSM doesn’t return one.
buffer_dist (float) – deprecated, do not use

Returns:

gdf

Return type:

geopandas.GeoDataFrame

osmnx.features.features_from_point(center_point, tags, dist=1000)

Create GeoDataFrame of OSM features within some distance N, S, E, W of a point.

You can use the settings module to retrieve a snapshot of historical OSM data as of a certain date, or to configure the Overpass server timeout, memory allocation, and other custom settings.

For more details, see: https://wiki.openstreetmap.org/wiki/Map_features

Parameters:

center_point (tuple) – the (lat, lon) center point around which to get the features
tags (dict) – Dict of tags used for finding elements in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
dist (numeric) – distance in meters

Returns:

gdf

Return type:

geopandas.GeoDataFrame

osmnx.features.features_from_polygon(polygon, tags)

Create GeoDataFrame of OSM features within boundaries of a (multi)polygon.

You can use the settings module to retrieve a snapshot of historical OSM data as of a certain date, or to configure the Overpass server timeout, memory allocation, and other custom settings.

For more details, see: https://wiki.openstreetmap.org/wiki/Map_features

Parameters:

polygon (shapely.geometry.Polygon or shapely.geometry.MultiPolygon) – geographic boundaries to fetch features within
tags (dict) – Dict of tags used for finding elements in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.

Returns:

gdf

Return type:

geopandas.GeoDataFrame

osmnx.features.features_from_xml(filepath, polygon=None, tags=None, encoding='utf-8')

Create a GeoDataFrame of OSM features in an OSM-formatted XML file.

Because this function creates a GeoDataFrame of features from an OSM-formatted XML file that has already been downloaded (i.e. no query is made to the Overpass API) the polygon and tags arguments are not required. If they are not supplied to the function, features_from_xml() will return features for all of the tagged elements in the file. If they are supplied they will be used to filter the final GeoDataFrame.

For more details, see: https://wiki.openstreetmap.org/wiki/Map_features

Parameters:

filepath (string or pathlib.Path) – path to file containing OSM XML data
polygon (shapely.geometry.Polygon) – optional geographic boundary to filter elements
tags (dict) – optional dict of tags for filtering elements from the XML. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
encoding (string) – the XML file’s character encoding

Returns:

gdf

Return type:

geopandas.GeoDataFrame

osmnx.folium module#

Create interactive Leaflet web maps of graphs and routes via folium.

This module is deprecated. Do not use. It will be removed in the v2.0.0 release. You can generate and explore interactive web maps of graph nodes, edges, and/or routes automatically using GeoPandas.GeoDataFrame.explore instead, for example like: ox.graph_to_gdfs(G, nodes=False).explore(). See the OSMnx examples gallery for complete details and demonstrations.

osmnx.folium._make_folium_polyline(geom, popup_val=None, **kwargs)

Turn LineString geometry into a folium PolyLine with attributes.

Parameters:

geom (shapely LineString) – geometry of the line
popup_val (string) – text to display in pop-up when a line is clicked, if None, no popup
kwargs – keyword arguments to pass to folium.PolyLine()

Returns:

Return type:

folium.PolyLine

osmnx.folium._plot_folium(gdf, m, popup_attribute, tiles, zoom, fit_bounds, **kwargs)

Plot a GeoDataFrame of LineStrings on a folium map object.

Parameters:

gdf (geopandas.GeoDataFrame) – a GeoDataFrame of LineString geometries and attributes
m (folium.folium.Map or folium.FeatureGroup) – if not None, plot on this preexisting folium map object
popup_attribute (string) – attribute to display in pop-up on-click, if None, no popup
tiles (string) – name of a folium tileset
zoom (int) – initial zoom level for the map
fit_bounds (bool) – if True, fit the map to gdf’s boundaries
kwargs – keyword arguments to pass to folium.PolyLine()

Returns:

Return type:

folium.folium.Map

osmnx.folium.plot_graph_folium(G, graph_map=None, popup_attribute=None, tiles='cartodbpositron', zoom=1, fit_bounds=True, **kwargs)

Do not use: deprecated.

You can generate and explore interactive web maps of graph nodes, edges, and/or routes automatically using GeoPandas.GeoDataFrame.explore instead, for example like: ox.graph_to_gdfs(G, nodes=False).explore(). See the OSMnx examples gallery for complete details and demonstrations.

Parameters:

G (networkx.MultiDiGraph) – deprecated
graph_map (folium.folium.Map) – deprecated
popup_attribute (string) – deprecated
tiles (string) – deprecated
zoom (int) – deprecated
fit_bounds (bool) – deprecated
kwargs – deprecated

Return type:

folium.folium.Map

osmnx.folium.plot_route_folium(G, route, route_map=None, popup_attribute=None, tiles='cartodbpositron', zoom=1, fit_bounds=True, **kwargs)

Do not use: deprecated.

Parameters:

G (networkx.MultiDiGraph) – deprecated
route (list) – deprecated
route_map (folium.folium.Map) – deprecated
popup_attribute (string) – deprecated
tiles (string) – deprecated
zoom (int) – deprecated
fit_bounds (bool) – deprecated
kwargs – deprecated

Return type:

folium.folium.Map

osmnx.geocoder module#

Geocode place names or addresses or retrieve OSM elements by place name or ID.

This module uses the Nominatim API’s “search” and “lookup” endpoints. For more details see https://wiki.openstreetmap.org/wiki/Elements and https://nominatim.org/.

osmnx.geocoder._geocode_query_to_gdf(query, which_result, by_osmid)

Geocode a single place query to a GeoDataFrame.

Parameters:

query (string or dict) – query string or structured dict to geocode
which_result (int) – which geocoding result to use. if None, auto-select the first (Multi)Polygon or raise an error if OSM doesn’t return one. to get the top match regardless of geometry type, set which_result=1. ignored if by_osmid=True.
by_osmid (bool) – if True, handle query as an OSM ID for lookup rather than text search

Returns:

gdf – a GeoDataFrame with one row containing the result of geocoding

Return type:

geopandas.GeoDataFrame

osmnx.geocoder._get_first_polygon(results, query)

Choose first result of geometry type (Multi)Polygon from list of results.

Parameters:

results (list) – list of results from _downloader._osm_place_download
query (str) – the query string or structured dict that was geocoded

Returns:

result – the chosen result

Return type:

dict

osmnx.geocoder.geocode(query)

Geocode place names or addresses to (lat, lon) with the Nominatim API.

This geocodes the query via the Nominatim “search” endpoint.

Parameters:: query (string) – the query string to geocode
Returns:: point – the (lat, lon) coordinates returned by the geocoder
Return type:: tuple

osmnx.geocoder.geocode_to_gdf(query, which_result=None, by_osmid=False, buffer_dist=None)

Retrieve OSM elements by place name or OSM ID with the Nominatim API.

If searching by place name, the query argument can be a string or structured dict, or a list of such strings/dicts to send to the geocoder. This uses the Nominatim “search” endpoint to geocode the place name to the best-matching OSM element, then returns that element and its attribute data.

You can instead query by OSM ID by passing by_osmid=True. This uses the Nominatim “lookup” endpoint to retrieve the OSM element with that ID. In this case, the function treats the query argument as an OSM ID (or list of OSM IDs), which must be prepended with their types: node (N), way (W), or relation (R) in accordance with the Nominatim API format. For example, query=[“R2192363”, “N240109189”, “W427818536”].

If query is a list, then which_result must be either a single value or a list with the same length as query. The queries you provide must be resolvable to elements in the Nominatim database. The resulting GeoDataFrame’s geometry column contains place boundaries if they exist.

Parameters:

query (string or dict or list of strings/dicts) – query string(s) or structured dict(s) to geocode
which_result (int) – which search result to return. if None, auto-select the first (Multi)Polygon or raise an error if OSM doesn’t return one. to get the top match regardless of geometry type, set which_result=1. ignored if by_osmid=True.
by_osmid (bool) – if True, treat query as an OSM ID lookup rather than text search
buffer_dist (float) – deprecated, do not use

Returns:

gdf – a GeoDataFrame with one row for each query

Return type:

geopandas.GeoDataFrame

osmnx.geometries module#

Do not use: deprecated.

The geometries module has been renamed the features module. The geometries module is deprecated and will be removed in the v2.0.0 release.

osmnx.geometries.geometries_from_address(address, tags, dist=1000)

Do not use: deprecated.

The geometries module and geometries_from_X functions have been renamed the features module and features_from_X functions. Use these instead. The geometries module and functions are deprecated and will be removed in the v2.0.0 release.

Parameters:

address (string) – Do not use: deprecated.
tags (dict) – Do not use: deprecated.
dist (numeric) – Do not use: deprecated.

Returns:

gdf

Return type:

geopandas.GeoDataFrame

osmnx.geometries.geometries_from_bbox(north, south, east, west, tags)

Do not use: deprecated.

Parameters:

north (float) – Do not use: deprecated.
south (float) – Do not use: deprecated.
east (float) – Do not use: deprecated.
west (float) – Do not use: deprecated.
tags (dict) – Do not use: deprecated.

Returns:

gdf

Return type:

geopandas.GeoDataFrame

osmnx.geometries.geometries_from_place(query, tags, which_result=None, buffer_dist=None)

Do not use: deprecated.

Parameters:

query (string or dict or list) – Do not use: deprecated.
tags (dict) – Do not use: deprecated.
which_result (int) – Do not use: deprecated.
buffer_dist (float) – Do not use: deprecated.

Returns:

gdf

Return type:

geopandas.GeoDataFrame

osmnx.geometries.geometries_from_point(center_point, tags, dist=1000)

Do not use: deprecated.

Parameters:

center_point (tuple) – Do not use: deprecated.
tags (dict) – Do not use: deprecated.
dist (numeric) – Do not use: deprecated.

Returns:

gdf

Return type:

geopandas.GeoDataFrame

osmnx.geometries.geometries_from_polygon(polygon, tags)

Do not use: deprecated.

Parameters:

polygon (shapely.geometry.Polygon or shapely.geometry.MultiPolygon) – Do not use: deprecated.
tags (dict) – Do not use: deprecated.

Returns:

gdf

Return type:

geopandas.GeoDataFrame

osmnx.geometries.geometries_from_xml(filepath, polygon=None, tags=None)

Do not use: deprecated.

Parameters:

filepath (string or pathlib.Path) – Do not use: deprecated.
polygon (shapely.geometry.Polygon) – Do not use: deprecated.
tags (dict) – Do not use: deprecated.

Returns:

gdf

Return type:

geopandas.GeoDataFrame

osmnx.graph module#

Download and create graphs from OpenStreetMap data.

This module uses filters to query the Overpass API: you can either specify a built-in network type or provide your own custom filter with Overpass QL.

Refer to the Getting Started guide for usage limitations.

osmnx.graph._add_paths(G, paths, bidirectional=False)

Add a list of paths to the graph as edges.

Parameters:

G (networkx.MultiDiGraph) – graph to add paths to
paths (list) – list of paths’ tag:value attribute data dicts
bidirectional (bool) – if True, create bi-directional edges for one-way streets

Return type:

None

osmnx.graph._convert_node(element)

Convert an OSM node element into the format for a networkx node.

Parameters:: element (dict) – an OSM node element
Returns:: node
Return type:: dict

osmnx.graph._convert_path(element)

Convert an OSM way element into the format for a networkx path.

Parameters:: element (dict) – an OSM way element
Returns:: path
Return type:: dict

osmnx.graph._create_graph(response_jsons, retain_all=False, bidirectional=False)

Create a networkx MultiDiGraph from Overpass API responses.

Adds length attributes in meters (great-circle distance between endpoints) to all of the graph’s (pre-simplified, straight-line) edges via the distance.add_edge_lengths function.

Parameters:

response_jsons (iterable) – iterable of dicts of JSON responses from from the Overpass API
retain_all (bool) – if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component.
bidirectional (bool) – if True, create bi-directional edges for one-way streets

Returns:

Return type:

networkx.MultiDiGraph

osmnx.graph._is_path_one_way(path, bidirectional, oneway_values)

Determine if a path of nodes allows travel in only one direction.

Parameters:

path (dict) – a path’s tag:value attribute data
bidirectional (bool) – whether this is a bi-directional network type
oneway_values (set) – the values OSM uses in its ‘oneway’ tag to denote True

Return type:

bool

osmnx.graph._is_path_reversed(path, reversed_values)

Determine if the order of nodes in a path should be reversed.

Parameters:

path (dict) – a path’s tag:value attribute data
reversed_values (set) – the values OSM uses in its ‘oneway’ tag to denote travel can only occur in the opposite direction of the node order

Return type:

bool

osmnx.graph._parse_nodes_paths(response_json)

Construct dicts of nodes and paths from an Overpass response.

Parameters:: response_json (dict) – JSON response from the Overpass API
Returns:: nodes, paths – dicts’ keys = osmid and values = dict of attributes
Return type:: tuple of dicts

osmnx.graph.graph_from_address(address, dist=1000, dist_type='bbox', network_type='all_private', simplify=True, retain_all=False, truncate_by_edge=False, return_coords=None, clean_periphery=None, custom_filter=None)

Download and create a graph within some distance of an address.

You can use the settings module to retrieve a snapshot of historical OSM data as of a certain date, or to configure the Overpass server timeout, memory allocation, and other custom settings.

Parameters:

address (string) – the address to geocode and use as the central point around which to construct the graph
dist (int) – retain only those nodes within this many meters of the center of the graph
dist_type (string {"network", "bbox"}) – if “bbox”, retain only those nodes within a bounding box of the distance parameter. if “network”, retain only those nodes within some network distance from the center-most node.
network_type (string {"all_private", "all", "bike", "drive", "drive_service", "walk"}) – what type of street network to get if custom_filter is None
simplify (bool) – if True, simplify graph topology with the simplify_graph function
retain_all (bool) – if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component.
truncate_by_edge (bool) – if True, retain nodes outside bounding box if at least one of node’s neighbors is within the bounding box
return_coords (bool) – deprecated, do not use
clean_periphery (bool) – deprecated, do not use
custom_filter (string) – a custom ways filter to be used instead of the network_type presets e.g., ‘[“power”~”line”]’ or ‘[“highway”~”motorway|trunk”]’. Also pass in a network_type that is in settings.bidirectional_network_types if you want graph to be fully bi-directional.

Return type:

networkx.MultiDiGraph or optionally (networkx.MultiDiGraph, (lat, lon))

Notes

Very large query areas use the utils_geo._consolidate_subdivide_geometry function to automatically make multiple requests: see that function’s documentation for caveats.

osmnx.graph.graph_from_bbox(north=None, south=None, east=None, west=None, bbox=None, network_type='all_private', simplify=True, retain_all=False, truncate_by_edge=False, clean_periphery=None, custom_filter=None)

Download and create a graph within some bounding box.

You can use the settings module to retrieve a snapshot of historical OSM data as of a certain date, or to configure the Overpass server timeout, memory allocation, and other custom settings.

Parameters:

north (float) – deprecated, do not use
south (float) – deprecated, do not use
east (float) – deprecated, do not use
west (float) – deprecated, do not use
bbox (tuple of floats) – bounding box as (north, south, east, west)
network_type (string {"all_private", "all", "bike", "drive", "drive_service", "walk"}) – what type of street network to get if custom_filter is None
simplify (bool) – if True, simplify graph topology with the simplify_graph function
retain_all (bool) – if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component.
truncate_by_edge (bool) – if True, retain nodes outside bounding box if at least one of node’s neighbors is within the bounding box
clean_periphery (bool) – deprecated, do not use
custom_filter (string) – a custom ways filter to be used instead of the network_type presets e.g., ‘[“power”~”line”]’ or ‘[“highway”~”motorway|trunk”]’. Also pass in a network_type that is in settings.bidirectional_network_types if you want graph to be fully bi-directional.

Returns:

Return type:

networkx.MultiDiGraph

Notes

Very large query areas use the utils_geo._consolidate_subdivide_geometry function to automatically make multiple requests: see that function’s documentation for caveats.

osmnx.graph.graph_from_place(query, network_type='all_private', simplify=True, retain_all=False, truncate_by_edge=False, which_result=None, buffer_dist=None, clean_periphery=None, custom_filter=None)

Download and create a graph within the boundaries of some place(s).

The query must be geocodable and OSM must have polygon boundaries for the geocode result. If OSM does not have a polygon for this place, you can instead get its street network using the graph_from_address function, which geocodes the place name to a point and gets the network within some distance of that point.

You can use the settings module to retrieve a snapshot of historical OSM data as of a certain date, or to configure the Overpass server timeout, memory allocation, and other custom settings.

Parameters:

query (string or dict or list) – the query or queries to geocode to get place boundary polygon(s)
network_type (string {"all_private", "all", "bike", "drive", "drive_service", "walk"}) – what type of street network to get if custom_filter is None
simplify (bool) – if True, simplify graph topology with the simplify_graph function
retain_all (bool) – if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component.
truncate_by_edge (bool) – if True, retain nodes outside boundary polygon if at least one of node’s neighbors is within the polygon
which_result (int) – which geocoding result to use. if None, auto-select the first (Multi)Polygon or raise an error if OSM doesn’t return one.
buffer_dist (float) – deprecated, do not use
clean_periphery (bool) – deprecated, do not use
custom_filter (string) – a custom ways filter to be used instead of the network_type presets e.g., ‘[“power”~”line”]’ or ‘[“highway”~”motorway|trunk”]’. Also pass in a network_type that is in settings.bidirectional_network_types if you want graph to be fully bi-directional.

Returns:

Return type:

networkx.MultiDiGraph

Notes

Very large query areas use the utils_geo._consolidate_subdivide_geometry function to automatically make multiple requests: see that function’s documentation for caveats.

osmnx.graph.graph_from_point(center_point, dist=1000, dist_type='bbox', network_type='all_private', simplify=True, retain_all=False, truncate_by_edge=False, clean_periphery=None, custom_filter=None)

Download and create a graph within some distance of a (lat, lon) point.

You can use the settings module to retrieve a snapshot of historical OSM data as of a certain date, or to configure the Overpass server timeout, memory allocation, and other custom settings.

Parameters:

center_point (tuple) – the (lat, lon) center point around which to construct the graph
dist (int) – retain only those nodes within this many meters of the center of the graph, with distance determined according to dist_type argument
dist_type (string {"network", "bbox"}) – if “bbox”, retain only those nodes within a bounding box of the distance parameter. if “network”, retain only those nodes within some network distance from the center-most node.
network_type (string, {"all_private", "all", "bike", "drive", "drive_service", "walk"}) – what type of street network to get if custom_filter is None
simplify (bool) – if True, simplify graph topology with the simplify_graph function
retain_all (bool) – if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component.
truncate_by_edge (bool) – if True, retain nodes outside bounding box if at least one of node’s neighbors is within the bounding box
clean_periphery (bool,) – deprecated, do not use
custom_filter (string) – a custom ways filter to be used instead of the network_type presets e.g., ‘[“power”~”line”]’ or ‘[“highway”~”motorway|trunk”]’. Also pass in a network_type that is in settings.bidirectional_network_types if you want graph to be fully bi-directional.

Returns:

Return type:

networkx.MultiDiGraph

Notes

Very large query areas use the utils_geo._consolidate_subdivide_geometry function to automatically make multiple requests: see that function’s documentation for caveats.

osmnx.graph.graph_from_polygon(polygon, network_type='all_private', simplify=True, retain_all=False, truncate_by_edge=False, clean_periphery=None, custom_filter=None)

Download and create a graph within the boundaries of a (multi)polygon.

You can use the settings module to retrieve a snapshot of historical OSM data as of a certain date, or to configure the Overpass server timeout, memory allocation, and other custom settings.

Parameters:

polygon (shapely.geometry.Polygon or shapely.geometry.MultiPolygon) – the shape to get network data within. coordinates should be in unprojected latitude-longitude degrees (EPSG:4326).
network_type (string {"all_private", "all", "bike", "drive", "drive_service", "walk"}) – what type of street network to get if custom_filter is None
simplify (bool) – if True, simplify graph topology with the simplify_graph function
retain_all (bool) – if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component.
truncate_by_edge (bool) – if True, retain nodes outside boundary polygon if at least one of node’s neighbors is within the polygon
clean_periphery (bool) – deprecated, do not use
custom_filter (string) – a custom ways filter to be used instead of the network_type presets e.g., ‘[“power”~”line”]’ or ‘[“highway”~”motorway|trunk”]’. Also pass in a network_type that is in settings.bidirectional_network_types if you want graph to be fully bi-directional.

Returns:

Return type:

networkx.MultiDiGraph

Notes

Very large query areas use the utils_geo._consolidate_subdivide_geometry function to automatically make multiple requests: see that function’s documentation for caveats.

osmnx.graph.graph_from_xml(filepath, bidirectional=False, simplify=True, retain_all=False, encoding='utf-8')

Create a graph from data in a .osm formatted XML file.

Do not load an XML file generated by OSMnx: this use case is not supported and may not behave as expected. To save/load graphs to/from disk for later use in OSMnx, use the io.save_graphml and io.load_graphml functions instead.

Parameters:

filepath (string or pathlib.Path) – path to file containing OSM XML data
bidirectional (bool) – if True, create bi-directional edges for one-way streets
simplify (bool) – if True, simplify graph topology with the simplify_graph function
retain_all (bool) – if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component.
encoding (string) – the XML file’s character encoding

Returns:

Return type:

networkx.MultiDiGraph

osmnx.io module#

Serialize graphs to/from files on disk.

osmnx.io._convert_bool_string(value)

Convert a “True” or “False” string literal to corresponding boolean type.

This is necessary because Python will otherwise parse the string “False” to the boolean value True, that is, bool(“False”) == True. This function raises a ValueError if a value other than “True” or “False” is passed.

If the value is already a boolean, this function just returns it, to accommodate usage when the value was originally inside a stringified list.

Parameters:: value (string {"True", "False"}) – the value to convert
Return type:: bool

osmnx.io._convert_edge_attr_types(G, dtypes=None)

Convert graph edges’ attributes using a dict of data types.

Parameters:

G (networkx.MultiDiGraph) – input graph
dtypes (dict) – dict of edge attribute names:types

Returns:

Return type:

networkx.MultiDiGraph

osmnx.io._convert_graph_attr_types(G, dtypes=None)

Convert graph-level attributes using a dict of data types.

Parameters:

G (networkx.MultiDiGraph) – input graph
dtypes (dict) – dict of graph-level attribute names:types

Returns:

Return type:

networkx.MultiDiGraph

osmnx.io._convert_node_attr_types(G, dtypes=None)

Convert graph nodes’ attributes using a dict of data types.

Parameters:

G (networkx.MultiDiGraph) – input graph
dtypes (dict) – dict of node attribute names:types

Returns:

Return type:

networkx.MultiDiGraph

osmnx.io._stringify_nonnumeric_cols(gdf)

Make every non-numeric GeoDataFrame column (besides geometry) a string.

This allows proper serializing via Fiona of GeoDataFrames with mixed types such as strings and ints in the same column.

Parameters:: gdf (geopandas.GeoDataFrame) – gdf to stringify non-numeric columns of
Returns:: gdf – gdf with non-numeric columns stringified
Return type:: geopandas.GeoDataFrame

osmnx.io.load_graphml(filepath=None, graphml_str=None, node_dtypes=None, edge_dtypes=None, graph_dtypes=None)

Load an OSMnx-saved GraphML file from disk or GraphML string.

This function converts node, edge, and graph-level attributes (serialized as strings) to their appropriate data types. These can be customized as needed by passing in dtypes arguments providing types or custom converter functions. For example, if you want to convert some attribute’s values to bool, consider using the built-in ox.io._convert_bool_string function to properly handle “True”/”False” string literals as True/False booleans: ox.load_graphml(fp, node_dtypes={my_attr: ox.io._convert_bool_string}).

If you manually configured the all_oneway=True setting, you may need to manually specify here that edge oneway attributes should be type str.

Note that you must pass one and only one of filepath or graphml_str. If passing graphml_str, you may need to decode the bytes read from your file before converting to string to pass to this function.

Parameters:

filepath (string or pathlib.Path) – path to the GraphML file
graphml_str (string) – a valid and decoded string representation of a GraphML file’s contents
node_dtypes (dict) – dict of node attribute names:types to convert values’ data types. the type can be a python type or a custom string converter function.
edge_dtypes (dict) – dict of edge attribute names:types to convert values’ data types. the type can be a python type or a custom string converter function.
graph_dtypes (dict) – dict of graph-level attribute names:types to convert values’ data types. the type can be a python type or a custom string converter function.

Returns:

Return type:

networkx.MultiDiGraph

osmnx.io.save_graph_geopackage(G, filepath=None, encoding='utf-8', directed=False)

Save graph nodes and edges to disk as layers in a GeoPackage file.

Parameters:

G (networkx.MultiDiGraph) – input graph
filepath (string or pathlib.Path) – path to the GeoPackage file including extension. if None, use default data folder + graph.gpkg
encoding (string) – the character encoding for the saved file
directed (bool) – if False, save one edge for each undirected edge in the graph but retain original oneway and to/from information as edge attributes; if True, save one edge for each directed edge in the graph

Return type:

None

osmnx.io.save_graph_shapefile(G, filepath=None, encoding='utf-8', directed=False)

Do not use: deprecated. Use the save_graph_geopackage function instead.

The Shapefile format is proprietary and outdated. Instead, use the superior GeoPackage file format via the save_graph_geopackage function. See http://switchfromshapefile.org/ for more information.

Parameters:

G (networkx.MultiDiGraph) – input graph
filepath (string or pathlib.Path) – path to the shapefiles folder (no file extension). if None, use default data folder + graph_shapefile
encoding (string) – the character encoding for the saved files
directed (bool) – if False, save one edge for each undirected edge in the graph but retain original oneway and to/from information as edge attributes; if True, save one edge for each directed edge in the graph

Return type:

None

osmnx.io.save_graph_xml(data, filepath=None, node_tags=None, node_attrs=None, edge_tags=None, edge_attrs=None, oneway=None, merge_edges=None, edge_tag_aggs=None, api_version=None, precision=None, way_tag_aggs=None)

Save graph to disk as an OSM-formatted XML .osm file.

This function exists only to allow serialization to the .osm file format for applications that require it, and has constraints to conform to that. As such, this function has a limited use case which does not include saving/loading graphs for subsequent OSMnx analysis. To save/load graphs to/from disk for later use in OSMnx, use the io.save_graphml and io.load_graphml functions instead. To load a graph from a .osm file that you have downloaded or generated elsewhere, use the graph.graph_from_xml function.

Parameters:

data (networkx.MultiDiGraph) – the input graph
filepath (string or pathlib.Path) – do not use, deprecated
node_tags (list) – do not use, deprecated
node_attrs (list) – do not use, deprecated
edge_tags (list) – do not use, deprecated
edge_attrs (list) – do not use, deprecated
oneway (bool) – do not use, deprecated
merge_edges (bool) – do not use, deprecated
edge_tag_aggs (tuple) – do not use, deprecated
api_version (float) – do not use, deprecated
precision (int) – do not use, deprecated
way_tag_aggs (dict) – Keys are OSM way tag keys and values are aggregation functions (anything accepted as an argument by pandas.agg). Allows user to aggregate graph edge attribute values into single OSM way values. If None, or if some tag’s key does not exist in the dict, the way attribute will be assigned the value of the first edge of the way.

Return type:

None

osmnx.io.save_graphml(G, filepath=None, gephi=False, encoding='utf-8')

Save graph to disk as GraphML file.

Parameters:

G (networkx.MultiDiGraph) – input graph
filepath (string or pathlib.Path) – path to the GraphML file including extension. if None, use default data folder + graph.graphml
gephi (bool) – if True, give each edge a unique key/id to work around Gephi’s interpretation of the GraphML specification
encoding (string) – the character encoding for the saved file

Return type:

None

osmnx._nominatim module#

Tools to work with the Nominatim API.

osmnx._nominatim._download_nominatim_element(query, by_osmid=False, limit=1, polygon_geojson=1)

Retrieve an OSM element from the Nominatim API.

Parameters:

query (string or dict) – query string or structured query dict
by_osmid (bool) – if True, treat query as an OSM ID lookup rather than text search
limit (int) – max number of results to return
polygon_geojson (int) – retrieve the place’s geometry from the API, 0=no, 1=yes

Returns:

response_json – JSON response from the Nominatim server

Return type:

dict

osmnx._nominatim._nominatim_request(params, request_type='search', pause=1, error_pause=60)

Send a HTTP GET request to the Nominatim API and return response.

Parameters:

params (OrderedDict) – key-value pairs of parameters
request_type (string {"search", "reverse", "lookup"}) – which Nominatim API endpoint to query
pause (float) – how long to pause before request, in seconds. per the nominatim usage policy: “an absolute maximum of 1 request per second” is allowed
error_pause (float) – how long to pause in seconds before re-trying request if error

Returns:

response_json

Return type:

dict

osmnx.osm_xml module#

Read/write .osm formatted XML files.

class osmnx.osm_xml._OSMContentHandler

SAX content handler for OSM XML.

Used to build an Overpass-like response JSON object in self.object. For format notes, see https://wiki.openstreetmap.org/wiki/OSM_XML and https://overpass-api.de

endElement(name)

Signals the end of an element in non-namespace mode.

The name parameter contains the name of the element type, just as with the startElement event.

startElement(name, attrs)

Signals the start of an element in non-namespace mode.

The name parameter contains the raw XML 1.0 name of the element type as a string and the attrs parameter holds an instance of the Attributes class containing the attributes of the element.

osmnx.osm_xml._append_edges_xml_tree(root, gdf_edges, edge_attrs, edge_tags, edge_tag_aggs, merge_edges)

Append edges to an XML tree.

Parameters:

root (ElementTree.Element) – xml tree
gdf_edges (geopandas.GeoDataFrame) – GeoDataFrame of graph edges
edge_attrs (list) – osm way attributes to include in output OSM XML
edge_tags (list) – osm way tags to include in output OSM XML
edge_tag_aggs (list of length-2 string tuples) – useful only if merge_edges is True, this argument allows the user to specify edge attributes to aggregate such that the merged OSM way entry tags accurately represent the sum total of their component edge attributes. For example, if the user wants the OSM way to have a “length” attribute, the user must specify edge_tag_aggs=[(‘length’, ‘sum’)] in order to tell this method to aggregate the lengths of the individual component edges. Otherwise, the length attribute will simply reflect the length of the first edge associated with the way.
merge_edges (bool) – if True merges graph edges such that each OSM way has one entry and one entry only in the OSM XML. Otherwise, every OSM way will have a separate entry for each node pair it contains.

Returns:

root – XML tree with edges appended

Return type:

ElementTree.Element

osmnx.osm_xml._append_merged_edge_attrs(xml_edge, sample_edge, all_edges_df, edge_tags, edge_tag_aggs)

Extract edge attributes and append to XML edge.

Parameters:

xml_edge (ElementTree.SubElement) – XML representation of an output graph edge
sample_edge (pandas.Series) – sample row from the the dataframe of way edges
all_edges_df (pandas.DataFrame) – a dataframe with one row for each edge in an OSM way
edge_tags (list) – osm way tags to include in output OSM XML
edge_tag_aggs (list of length-2 string tuples) – useful only if merge_edges is True, this argument allows the user to specify edge attributes to aggregate such that the merged OSM way entry tags accurately represent the sum total of their component edge attributes. For example if the user wants the OSM way to have a length attribute, the user must specify edge_tag_aggs=[(‘length’, ‘sum’)] to tell this method to aggregate the lengths of the individual component edges. Otherwise, the length attribute will simply reflect the length of the first edge associated with the way.

osmnx.osm_xml._append_nodes_as_edge_attrs(xml_edge, sample_edge, all_edges_df)

Extract list of ordered nodes and append as attributes of XML edge.

Parameters:

xml_edge (ElementTree.SubElement) – XML representation of an output graph edge
sample_edge (pandas.Series) – sample row from the the dataframe of way edges
all_edges_df (pandas.DataFrame) – a dataframe with one row for each edge in an OSM way

osmnx.osm_xml._append_nodes_xml_tree(root, gdf_nodes, node_attrs, node_tags)

Append nodes to an XML tree.

Parameters:

root (ElementTree.Element) – xml tree
gdf_nodes (geopandas.GeoDataFrame) – GeoDataFrame of graph nodes
node_attrs (list) – osm way attributes to include in output OSM XML
node_tags (list) – osm way tags to include in output OSM XML

Returns:

root – xml tree with nodes appended

Return type:

ElementTree.Element

osmnx.osm_xml._create_way_for_each_edge(root, gdf_edges, edge_attrs, edge_tags)

Append a new way to an empty XML tree graph for each edge in way.

This will generate separate OSM ways for each network edge, even if the edges are all part of the same original OSM way. As such, each way will be composed of two nodes, and there will be many ways with the same OSM ID. This does not conform to the OSM XML schema standard, but the data will still comprise a valid network and will be readable by most OSM tools.

Parameters:

root (ElementTree.Element) – an empty XML tree
gdf_edges (geopandas.GeoDataFrame) – GeoDataFrame of graph edges
edge_attrs (list) – osm way attributes to include in output OSM XML
edge_tags (list) – osm way tags to include in output OSM XML

osmnx.osm_xml._get_unique_nodes_ordered_from_way(df_way_edges)

Recover original node order from edges associated with a single OSM way.

Parameters:: df_way_edges (pandas.DataFrame) – Dataframe containing columns ‘u’ and ‘v’ corresponding to origin/destination nodes.
Returns:: unique_ordered_nodes – An ordered list of unique node IDs. If the edges do not all connect (e.g. [(1, 2), (2,3), (10, 11), (11, 12), (12, 13)]), then this method will return only those nodes associated with the largest component of connected edges, even if subsequent connected chunks are contain more total nodes. This ensures a proper topological representation of nodes in the XML way records because if there are unconnected components, the sorting algorithm cannot recover their original order. We would not likely ever encounter this kind of disconnected structure of nodes within a given way, but it is not explicitly forbidden in the OSM XML design schema.
Return type:: list

osmnx.osm_xml._overpass_json_from_file(filepath, encoding)

Read OSM XML from file and return Overpass-like JSON.

Parameters:

filepath (string or pathlib.Path) – path to file containing OSM XML data
encoding (string) – the XML file’s character encoding

Return type:

OSMContentHandler object

osmnx.osm_xml._save_graph_xml(data, filepath, node_tags, node_attrs, edge_tags, edge_attrs, oneway, merge_edges, edge_tag_aggs, api_version, precision, way_tag_aggs)

Save graph to disk as an OSM-formatted UTF-8 encoded XML .osm file.

Parameters:

data (networkx.MultiDiGraph) – the input graph
filepath (string or pathlib.Path) – do not use, deprecated
node_tags (list) – do not use, deprecated
node_attrs (list) – do not use, deprecated
edge_tags (list) – do not use, deprecated
edge_attrs (list) – do not use, deprecated
oneway (bool) – do not use, deprecated
merge_edges (bool) – do not use, deprecated
edge_tag_aggs (tuple) – do not use, deprecated
api_version (float) – do not use, deprecated
precision (int) – do not use, deprecated
way_tag_aggs (dict) – Keys are OSM way tag keys and values are aggregation functions (anything accepted as an argument by pandas.agg). Allows user to aggregate graph edge attribute values into single OSM way values. If None, or if some tag’s key does not exist in the dict, the way attribute will be assigned the value of the first edge of the way.

Return type:

None

osmnx.osm_xml.save_graph_xml(data, filepath=None, node_tags=None, node_attrs=None, edge_tags=None, edge_attrs=None, oneway=None, merge_edges=None, edge_tag_aggs=None, api_version=None, precision=None, way_tag_aggs=None)

Do not use: deprecated.

The save_graph_xml has moved from the osm_xml module to the io module. osm_xml.save_graph_xml has been deprecated and will be removed in the v2.0.0 release. Access the function via the io module instead.

Parameters:

data (networkx.MultiDiGraph) – do not use, deprecated
filepath (string or pathlib.Path) – do not use, deprecated
node_tags (list) – do not use, deprecated
node_attrs (list) – do not use, deprecated
edge_tags (list) – do not use, deprecated
edge_attrs (list) – do not use, deprecated
oneway (bool) – do not use, deprecated
merge_edges (bool) – do not use, deprecated
edge_tag_aggs (tuple) – do not use, deprecated
api_version (float) – do not use, deprecated
precision (int) – do not use, deprecated
way_tag_aggs (dict) – do not use, deprecated

Return type:

None

osmnx._overpass module#

Tools to work with the Overpass API.

osmnx._overpass._create_overpass_query(polygon_coord_str, tags)

Create an Overpass features query string based on passed tags.

Parameters:

polygon_coord_str (list) – list of lat lon coordinates
tags (dict) – dict of tags used for finding elements in the search area

Returns:

query

Return type:

string

osmnx._overpass._download_overpass_features(polygon, tags)

Retrieve OSM features within boundary from the Overpass API.

Parameters:

polygon (shapely.geometry.Polygon) – boundaries to fetch elements within
tags (dict) – dict of tags used for finding elements in the selected area

Yields:

response_json (dict) – a generator of JSON responses from the Overpass server

osmnx._overpass._download_overpass_network(polygon, network_type, custom_filter)

Retrieve networked ways and nodes within boundary from the Overpass API.

Parameters:

polygon (shapely.geometry.Polygon or shapely.geometry.MultiPolygon) – boundary to fetch the network ways/nodes within
network_type (string) – what type of street network to get if custom_filter is None
custom_filter (string) – a custom “ways” filter to be used instead of the network_type presets

Yields:

response_json (dict) – a generator of JSON responses from the Overpass server

osmnx._overpass._get_osm_filter(network_type)

Create a filter to query OSM for the specified network type.

Parameters:: network_type (string {"all_private", "all", "bike", "drive", "drive_service", "walk"}) – what type of street network to get
Return type:: string

osmnx._overpass._get_overpass_pause(base_endpoint, recursive_delay=5, default_duration=60)

Retrieve a pause duration from the Overpass API status endpoint.

Check the Overpass API status endpoint to determine how long to wait until the next slot is available. You can disable this via the settings module’s overpass_rate_limit setting.

Parameters:

base_endpoint (string) – base Overpass API url (without “/status” at the end)
recursive_delay (int) – how long to wait between recursive calls if the server is currently running a query
default_duration (int) – if fatal error, fall back on returning this value

Returns:

pause

Return type:

int

osmnx._overpass._make_overpass_polygon_coord_strs(polygon)

Subdivide query polygon and return list of coordinate strings.

Project to utm, divide polygon up into sub-polygons if area exceeds a max size (in meters), project back to lat-lon, then get a list of polygon(s) exterior coordinates. Ignore interior (“holes”) coordinates.

Parameters:: polygon (shapely.geometry.Polygon or shapely.geometry.MultiPolygon) – polygon to convert to exterior coordinate strings
Returns:: coord_strs – list of strings of exterior coordinates of polygon(s)
Return type:: list

osmnx._overpass._make_overpass_settings()

Make settings string to send in Overpass query.

Return type:: string

osmnx._overpass._overpass_request(data, pause=None, error_pause=60)

Send a HTTP POST request to the Overpass API and return response.

Parameters:

data (OrderedDict) – key-value pairs of parameters
pause (float) – how long to pause in seconds before request, if None, will query API status endpoint to find when next slot is available
error_pause (float) – how long to pause in seconds (in addition to pause) before re-trying request if error

Returns:

response_json

Return type:

dict

osmnx.plot module#

Visualize street networks, routes, orientations, and geospatial features.

osmnx.plot._config_ax(ax, crs, bbox, padding)

Configure axis for display.

Parameters:

ax (matplotlib axis) – the axis containing the plot
crs (dict or string or pyproj.CRS) – the CRS of the plotted geometries
bbox (tuple) – bounding box as (north, south, east, west)
padding (float) – relative padding to add around the plot’s bbox

Returns:

ax – the configured/styled axis

Return type:

matplotlib axis

osmnx.plot._get_colors_by_value(vals, num_bins, cmap, start, stop, na_color, equal_size)

Map colors to the values in a series.

Parameters:

vals (pandas.Series) – series labels are node/edge IDs and values are attribute values
num_bins (int) – if None, linearly map a color to each value. otherwise, assign values to this many bins then assign a color to each bin.
cmap (string) – name of a matplotlib colormap
start (float) – where to start in the colorspace
stop (float) – where to end in the colorspace
na_color (string) – what color to assign to missing values
equal_size (bool) – ignored if num_bins is None. if True, bin into equal-sized quantiles (requires unique bin edges). if False, bin into equal-spaced bins.

Returns:

color_series – series labels are node/edge IDs and values are colors

Return type:

pandas.Series

osmnx.plot._save_and_show(fig, ax, save=False, show=True, close=True, filepath=None, dpi=300)

Save a figure to disk and/or show it, as specified by args.

Parameters:

fig (figure) – matplotlib figure
ax (axis) – matplotlib axis
save (bool) – if True, save the figure to disk at filepath
show (bool) – if True, call pyplot.show() to show the figure
close (bool) – if True, call pyplot.close() to close the figure
filepath (string) – if save is True, the path to the file. file format determined from extension. if None, use settings.imgs_folder/image.png
dpi (int) – if save is True, the resolution of saved file

Returns:

fig, ax – matplotlib figure, axis

Return type:

tuple

osmnx.plot._verify_mpl()

Verify that matplotlib is installed and successfully imported.

Return type:: None

osmnx.plot.get_colors(n, cmap='viridis', start=0.0, stop=1.0, alpha=1.0, return_hex=None)

Get n evenly-spaced colors from a matplotlib colormap.

Parameters:

n (int) – number of colors
cmap (string) – name of a matplotlib colormap
start (float) – where to start in the colorspace
stop (float) – where to end in the colorspace
alpha (float) – If None, return colors as HTML-like hex triplet “#rrggbb” RGB strings. If float, return as “#rrggbbaa” RGBa strings.
return_hex (bool) – deprecated, do not use

Returns:

color_list

Return type:

list

osmnx.plot.get_edge_colors_by_attr(G, attr, num_bins=None, cmap='viridis', start=0, stop=1, na_color='none', equal_size=False)

Get colors based on edge attribute values.

Parameters:

G (networkx.MultiDiGraph) – input graph
attr (string) – name of a numerical edge attribute
num_bins (int) – if None, linearly map a color to each value. otherwise, assign values to this many bins then assign a color to each bin.
cmap (string) – name of a matplotlib colormap
start (float) – where to start in the colorspace
stop (float) – where to end in the colorspace
na_color (string) – what color to assign edges with missing attr values
equal_size (bool) – ignored if num_bins is None. if True, bin into equal-sized quantiles (requires unique bin edges). if False, bin into equal-spaced bins.

Returns:

edge_colors – series labels are edge IDs (u, v, key) and values are colors

Return type:

pandas.Series

osmnx.plot.get_node_colors_by_attr(G, attr, num_bins=None, cmap='viridis', start=0, stop=1, na_color='none', equal_size=False)

Get colors based on node attribute values.

Parameters:

G (networkx.MultiDiGraph) – input graph
attr (string) – name of a numerical node attribute
num_bins (int) – if None, linearly map a color to each value. otherwise, assign values to this many bins then assign a color to each bin.
cmap (string) – name of a matplotlib colormap
start (float) – where to start in the colorspace
stop (float) – where to end in the colorspace
na_color (string) – what color to assign nodes with missing attr values
equal_size (bool) – ignored if num_bins is None. if True, bin into equal-sized quantiles (requires unique bin edges). if False, bin into equal-spaced bins.

Returns:

node_colors – series labels are node IDs and values are colors

Return type:

pandas.Series

osmnx.plot.plot_figure_ground(G=None, address=None, point=None, dist=805, network_type='drive_service', street_widths=None, default_width=4, color='w', edge_color=None, smooth_joints=None, **pg_kwargs)

Plot a figure-ground diagram of a street network.

Parameters:

G (networkx.MultiDiGraph) – input graph, must be unprojected
address (string) – deprecated, do not use
point (tuple) – deprecated, do not use
dist (numeric) – how many meters to extend north, south, east, west from center point
network_type (string) – deprecated, do not use
street_widths (dict) – dict keys are street types and values are widths to plot in pixels
default_width (numeric) – fallback width in pixels for any street type not in street_widths
color (string) – color of the streets
edge_color (string) – deprecated, do not use
smooth_joints (bool) – deprecated, do not use
pg_kwargs – keyword arguments to pass to plot_graph

Returns:

fig, ax – matplotlib figure, axis

Return type:

tuple

osmnx.plot.plot_footprints(gdf, ax=None, figsize=(8, 8), color='orange', edge_color='none', edge_linewidth=0, alpha=None, bgcolor='#111111', bbox=None, save=False, show=True, close=False, filepath=None, dpi=600)

Visualize a GeoDataFrame of geospatial features’ footprints.

Parameters:

gdf (geopandas.GeoDataFrame) – GeoDataFrame of footprints (shapely Polygons and MultiPolygons)
ax (axis) – if not None, plot on this preexisting axis
figsize (tuple) – if ax is None, create new figure with size (width, height)
color (string) – color of the footprints
edge_color (string) – color of the edge of the footprints
edge_linewidth (float) – width of the edge of the footprints
alpha (float) – opacity of the footprints
bgcolor (string) – background color of the plot
bbox (tuple) – bounding box as (north, south, east, west). if None, will calculate from the spatial extents of the geometries in gdf
save (bool) – if True, save the figure to disk at filepath
show (bool) – if True, call pyplot.show() to show the figure
close (bool) – if True, call pyplot.close() to close the figure
filepath (string) – if save is True, the path to the file. file format determined from extension. if None, use settings.imgs_folder/image.png
dpi (int) – if save is True, the resolution of saved file

Returns:

fig, ax – matplotlib figure, axis

Return type:

tuple

osmnx.plot.plot_graph(G, ax=None, figsize=(8, 8), bgcolor='#111111', node_color='w', node_size=15, node_alpha=None, node_edgecolor='none', node_zorder=1, edge_color='#999999', edge_linewidth=1, edge_alpha=None, show=True, close=False, save=False, filepath=None, dpi=300, bbox=None)

Visualize a graph.

Parameters:

G (networkx.MultiDiGraph) – input graph
ax (matplotlib axis) – if not None, plot on this preexisting axis
figsize (tuple) – if ax is None, create new figure with size (width, height)
bgcolor (string) – background color of plot
node_color (string or list) – color(s) of the nodes
node_size (int) – size of the nodes: if 0, then skip plotting the nodes
node_alpha (float) – opacity of the nodes, note: if you passed RGBA values to node_color, set node_alpha=None to use the alpha channel in node_color
node_edgecolor (string) – color of the nodes’ markers’ borders
node_zorder (int) – zorder to plot nodes: edges are always 1, so set node_zorder=0 to plot nodes below edges
edge_color (string or list) – color(s) of the edges’ lines
edge_linewidth (float) – width of the edges’ lines: if 0, then skip plotting the edges
edge_alpha (float) – opacity of the edges, note: if you passed RGBA values to edge_color, set edge_alpha=None to use the alpha channel in edge_color
show (bool) – if True, call pyplot.show() to show the figure
close (bool) – if True, call pyplot.close() to close the figure
save (bool) – if True, save the figure to disk at filepath
filepath (string) – if save is True, the path to the file. file format determined from extension. if None, use settings.imgs_folder/image.png
dpi (int) – if save is True, the resolution of saved file
bbox (tuple) – bounding box as (north, south, east, west). if None, will calculate from spatial extents of plotted geometries.

Returns:

fig, ax – matplotlib figure, axis

Return type:

tuple

osmnx.plot.plot_graph_route(G, route, route_color='r', route_linewidth=4, route_alpha=0.5, orig_dest_size=100, ax=None, **pg_kwargs)

Visualize a route along a graph.

Parameters:

G (networkx.MultiDiGraph) – input graph
route (list) – route as a list of node IDs
route_color (string) – color of the route
route_linewidth (int) – width of the route line
route_alpha (float) – opacity of the route line
orig_dest_size (int) – size of the origin and destination nodes
ax (matplotlib axis) – if not None, plot route on this preexisting axis instead of creating a new fig, ax and drawing the underlying graph
pg_kwargs – keyword arguments to pass to plot_graph

Returns:

fig, ax – matplotlib figure, axis

Return type:

tuple

osmnx.plot.plot_graph_routes(G, routes, route_colors='r', route_linewidths=4, **pgr_kwargs)

Visualize several routes along a graph.

Parameters:

G (networkx.MultiDiGraph) – input graph
routes (list) – routes as a list of lists of node IDs
route_colors (string or list) – if string, 1 color for all routes. if list, the colors for each route.
route_linewidths (int or list) – if int, 1 linewidth for all routes. if list, the linewidth for each route.
pgr_kwargs – keyword arguments to pass to plot_graph_route

Returns:

fig, ax – matplotlib figure, axis

Return type:

tuple

osmnx.plot.plot_orientation(Gu, num_bins=36, min_length=0, weight=None, ax=None, figsize=(5, 5), area=True, color='#003366', edgecolor='k', linewidth=0.5, alpha=0.7, title=None, title_y=1.05, title_font=None, xtick_font=None)

Plot a polar histogram of a spatial network’s bidirectional edge bearings.

Ignores self-loop edges as their bearings are undefined.

For more info see: Boeing, G. 2019. “Urban Spatial Order: Street Network Orientation, Configuration, and Entropy.” Applied Network Science, 4 (1), 67. https://doi.org/10.1007/s41109-019-0189-1

Parameters:

Gu (networkx.MultiGraph) – undirected, unprojected graph with bearing attributes on each edge
num_bins (int) – number of bins; for example, if num_bins=36 is provided, then each bin will represent 10 degrees around the compass
min_length (float) – ignore edges with length attributes less than min_length
weight (string) – if not None, weight edges’ bearings by this (non-null) edge attribute
ax (matplotlib.axes.PolarAxesSubplot) – if not None, plot on this preexisting axis; must have projection=polar
figsize (tuple) – if ax is None, create new figure with size (width, height)
area (bool) – if True, set bar length so area is proportional to frequency, otherwise set bar length so height is proportional to frequency
color (string) – color of histogram bars
edgecolor (string) – color of histogram bar edges
linewidth (float) – width of histogram bar edges
alpha (float) – opacity of histogram bars
title (string) – title for plot
title_y (float) – y position to place title
title_font (dict) – the title’s fontdict to pass to matplotlib
xtick_font (dict) – the xtick labels’ fontdict to pass to matplotlib

Returns:

fig, ax – matplotlib figure, axis

Return type:

tuple

osmnx.projection module#

Project a graph, GeoDataFrame, or geometry to a different CRS.

osmnx.projection.is_projected(crs)

Determine if a coordinate reference system is projected or not.

Parameters:: crs (string or pyproj.CRS) – the identifier of the coordinate reference system, which can be anything accepted by pyproj.CRS.from_user_input() such as an authority string or a WKT string
Returns:: projected – True if crs is projected, otherwise False
Return type:: bool

osmnx.projection.project_gdf(gdf, to_crs=None, to_latlong=False)

Project a GeoDataFrame from its current CRS to another.

If to_latlong is True, this projects the GeoDataFrame to the CRS defined by settings.default_crs, otherwise it projects it to the CRS defined by to_crs. If to_crs is None, it projects it to the CRS of an appropriate UTM zone given gdf’s bounds.

Parameters:

gdf (geopandas.GeoDataFrame) – the GeoDataFrame to be projected
to_crs (string or pyproj.CRS) – if None, project to an appropriate UTM zone, otherwise project to this CRS
to_latlong (bool) – if True, project to settings.default_crs and ignore to_crs

Returns:

gdf_proj – the projected GeoDataFrame

Return type:

geopandas.GeoDataFrame

osmnx.projection.project_geometry(geometry, crs=None, to_crs=None, to_latlong=False)

Project a Shapely geometry from its current CRS to another.

Parameters:

geometry (shapely geometry) – the geometry to be projected
crs (string or pyproj.CRS) – the initial CRS of geometry. if None, it will be set to settings.default_crs
to_crs (string or pyproj.CRS) – if None, project to an appropriate UTM zone, otherwise project to this CRS
to_latlong (bool) – if True, project to settings.default_crs and ignore to_crs

Returns:

geometry_proj, crs – the projected geometry and its new CRS

Return type:

tuple

osmnx.projection.project_graph(G, to_crs=None, to_latlong=False)

Project a graph from its current CRS to another.

Parameters:

G (networkx.MultiDiGraph) – the graph to be projected
to_crs (string or pyproj.CRS) – if None, project to an appropriate UTM zone, otherwise project to this CRS
to_latlong (bool) – if True, project to settings.default_crs and ignore to_crs

Returns:

G_proj – the projected graph

Return type:

networkx.MultiDiGraph

osmnx.routing module#

Calculate weighted shortest paths between graph nodes.

osmnx.routing._clean_maxspeed(maxspeed, agg=numpy.mean, convert_mph=True)

Clean a maxspeed string and convert mph to kph if necessary.

If present, splits maxspeed on “|” (which denotes that the value contains different speeds per lane) then aggregates the resulting values. Invalid inputs return None. See https://wiki.openstreetmap.org/wiki/Key:maxspeed for details on values and formats.

Parameters:

maxspeed (string) – a valid OpenStreetMap way maxspeed value
agg (function) – aggregation function if maxspeed contains multiple values (default is numpy.mean)
convert_mph (bool) – if True, convert miles per hour to km per hour

Returns:

clean_value

Return type:

string

osmnx.routing._collapse_multiple_maxspeed_values(value, agg)

Collapse a list of maxspeed values to a single value.

Parameters:

value (list or string) – an OSM way maxspeed value, or a list of them
agg (function) – the aggregation function to reduce the list to a single value

Returns:

agg_value – an integer representation of the aggregated value in the list, converted to kph if original value was in mph.

Return type:

int

osmnx.routing._single_shortest_path(G, orig, dest, weight)

Solve the shortest path from an origin node to a destination node.

This function is a convenience wrapper around networkx.shortest_path, with exception handling for unsolvable paths. It uses Dijkstra’s algorithm.

Parameters:

G (networkx.MultiDiGraph) – input graph
orig (int) – origin node ID
dest (int) – destination node ID
weight (string) – edge attribute to minimize when solving shortest path

Returns:

path – list of node IDs constituting the shortest path

Return type:

list

osmnx.routing._verify_edge_attribute(G, attr)

Verify attribute values are numeric and non-null across graph edges.

Raises a ValueError if attribute contains non-numeric values and raises a warning if attribute is missing or null on any edges.

Parameters:

G (networkx.MultiDiGraph) – input graph
attr (string) – edge attribute to verify

Return type:

None

osmnx.routing.add_edge_speeds(G, hwy_speeds=None, fallback=None, precision=None, agg=numpy.mean)

Add edge speeds (km per hour) to graph as new speed_kph edge attributes.

By default, this imputes free-flow travel speeds for all edges via the mean maxspeed value of the edges of each highway type. For highway types in the graph that have no maxspeed value on any edge, it assigns the mean of all maxspeed values in graph.

This default mean-imputation can obviously be imprecise, and the user can override it by passing in hwy_speeds and/or fallback arguments that correspond to local speed limit standards. The user can also specify a different aggregation function (such as the median) to impute missing values from the observed values.

If edge maxspeed attribute has “mph” in it, value will automatically be converted from miles per hour to km per hour. Any other speed units should be manually converted to km per hour prior to running this function, otherwise there could be unexpected results. If “mph” does not appear in the edge’s maxspeed attribute string, then function assumes kph, per OSM guidelines: https://wiki.openstreetmap.org/wiki/Map_Features/Units

Parameters:

G (networkx.MultiDiGraph) – input graph
hwy_speeds (dict) – dict keys = OSM highway types and values = typical speeds (km per hour) to assign to edges of that highway type for any edges missing speed data. Any edges with highway type not in hwy_speeds will be assigned the mean preexisting speed value of all edges of that highway type.
fallback (numeric) – default speed value (km per hour) to assign to edges whose highway type did not appear in hwy_speeds and had no preexisting speed values on any edge
precision (int) – deprecated, do not use
agg (function) – aggregation function to impute missing values from observed values. the default is numpy.mean, but you might also consider for example numpy.median, numpy.nanmedian, or your own custom function

Returns:

G – graph with speed_kph attributes on all edges

Return type:

networkx.MultiDiGraph

osmnx.routing.add_edge_travel_times(G, precision=None)

Add edge travel time (seconds) to graph as new travel_time edge attributes.

Calculates free-flow travel time along each edge, based on length and speed_kph attributes. Note: run add_edge_speeds first to generate the speed_kph attribute. All edges must have length and speed_kph attributes and all their values must be non-null.

Parameters:

G (networkx.MultiDiGraph) – input graph
precision (int) – deprecated, do not use

Returns:

G – graph with travel_time attributes on all edges

Return type:

networkx.MultiDiGraph

osmnx.routing.k_shortest_paths(G, orig, dest, k, weight='length')

Solve k shortest paths from an origin node to a destination node.

Uses Yen’s algorithm. See also shortest_path to solve just the one shortest path.

Parameters:

G (networkx.MultiDiGraph) – input graph
orig (int) – origin node ID
dest (int) – destination node ID
k (int) – number of shortest paths to solve
weight (string) – edge attribute to minimize when solving shortest paths. default is edge length in meters.

Yields:

path (list) – a generator of k shortest paths ordered by total weight. each path is a list of node IDs.

osmnx.routing.route_to_gdf(G, route, weight='length')

Return a GeoDataFrame of the edges in a path, in order.

Parameters:

G (networkx.MultiDiGraph) – input graph
route (list) – list of node IDs constituting the path
weight (string) – if there are parallel edges between two nodes, choose lowest weight

Returns:

gdf_edges – GeoDataFrame of the edges

Return type:

geopandas.GeoDataFrame

osmnx.routing.shortest_path(G, orig, dest, weight='length', cpus=1)

Solve shortest path from origin node(s) to destination node(s).

Uses Dijkstra’s algorithm. If orig and dest are single node IDs, this will return a list of the nodes constituting the shortest path between them. If orig and dest are lists of node IDs, this will return a list of lists of the nodes constituting the shortest path between each origin-destination pair. If a path cannot be solved, this will return None for that path. You can parallelize solving multiple paths with the cpus parameter, but be careful to not exceed your available RAM.

See also k_shortest_paths to solve multiple shortest paths between a single origin and destination. For additional functionality or different solver algorithms, use NetworkX directly.

Parameters:

G (networkx.MultiDiGraph) – input graph
orig (int or list) – origin node ID, or a list of origin node IDs
dest (int or list) – destination node ID, or a list of destination node IDs
weight (string) – edge attribute to minimize when solving shortest path
cpus (int) – how many CPU cores to use; if None, use all available

Returns:

path – list of node IDs constituting the shortest path, or, if orig and dest are lists, then a list of path lists

Return type:

list

osmnx.settings module#

Global settings that can be configured by the user.

all_onewaybool: Only use if specifically saving to .osm XML file with the save_graph_xml function. If True, forces all ways to be loaded as oneway ways, preserving the original order of nodes stored in the OSM way XML. This also retains original OSM string values for oneway attribute values, rather than converting them to a True/False bool. Default is False.
bidirectional_network_typeslist: Network types for which a fully bidirectional graph will be created. Default is [“walk”].
cache_folderstr or pathlib.Path: Path to folder in which to save/load HTTP response cache, if the use_cache setting equals True. Default is “./cache”.
cache_only_modebool: If True, download network data from Overpass then raise a CacheOnlyModeInterrupt error for user to catch. This prevents graph building from taking place and instead just saves OSM response data to cache. Useful for sequentially caching lots of raw data (as you can only query Overpass one request at a time) then using the local cache to quickly build many graphs simultaneously with multiprocessing. Default is False.
data_folderstr or pathlib.Path: Path to folder in which to save/load graph files by default. Default is “./data”.
default_accept_languagestr: Do not use, deprecated. Use http_accept_language instead.
default_accessstr: Default filter for OSM “access” key. Default is ‘[“access”!~”private”]’. Note that also filtering out “access=no” ways prevents including transit-only bridges (e.g., Tilikum Crossing) from appearing in drivable road network (e.g., ‘[“access”!~”private|no”]’). However, some drivable tollroads have “access=no” plus a “access:conditional” key to clarify when it is accessible, so we can’t filter out all “access=no” ways by default. Best to be permissive here then remove complicated combinations of tags programatically after the full graph is downloaded and constructed.
default_crsstr: Default coordinate reference system to set when creating graphs. Default is “epsg:4326”.
default_refererstr: Do not use, deprecated. Use http_referer instead.
default_user_agentstr: Do not use, deprecated. Use http_user_agent instead.
doh_url_templatestr: Endpoint to resolve DNS-over-HTTPS if local DNS resolution fails. Set to None to disable DoH, but see downloader._config_dns documentation for caveats. Default is: “https://8.8.8.8/resolve?name={hostname}”
elevation_url_templatestr: Endpoint of the Google Maps Elevation API (or equivalent), containing exactly two parameters: locations and key. Default is: “https://maps.googleapis.com/maps/api/elevation/json?locations={locations}&key={key}” One example of an alternative equivalent would be Open Topo Data: “https://api.opentopodata.org/v1/aster30m?locations={locations}&key={key}”
http_accept_languagestr: HTTP header accept-language. Default is “en”. Note that Nominatim’s default language is “en” and it can sort result importance scores differently if a different language is specified.
http_refererstr: HTTP header referer. Default is “OSMnx Python package (https://github.com/gboeing/osmnx)”.
http_user_agentstr: HTTP header user-agent. Default is “OSMnx Python package (https://github.com/gboeing/osmnx)”.
imgs_folderstr or pathlib.Path: Path to folder in which to save plotted images by default. Default is “./images”.
log_filebool: If True, save log output to a file in logs_folder. Default is False.
log_filenamestr: Name of the log file, without file extension. Default is “osmnx”.
log_consolebool: If True, print log output to the console (terminal window). Default is False.
log_levelint: One of Python’s logger.level constants. Default is logging.INFO.
log_namestr: Name of the logger. Default is “OSMnx”.
logs_folderstr or pathlib.Path: Path to folder in which to save log files. Default is “./logs”.
max_query_area_sizeint: Maximum area for any part of the geometry in meters: any polygon bigger than this will get divided up for multiple queries to the API. Default is 2500000000.
memoryint: Do not use, deprecated. Use overpass_memory instead.
nominatim_endpointstr: Do not use, deprecated. Use nominatim_url instead.
nominatim_keystr: Your Nominatim API key, if you are using an API instance that requires one. Default is None.
nominatim_urlstr: The base API url to use for Nominatim queries. Default is “https://nominatim.openstreetmap.org/”.
osm_xml_node_attrslist: Do not use, deprecated.
osm_xml_node_tagslist: Do not use, deprecated.
osm_xml_way_attrslist: Do not use, deprecated.
osm_xml_way_tagslist: Do not use, deprecated.
overpass_endpointstr: Do not use, deprecated. Use overpass_url instead.
overpass_memoryint | None: Overpass server memory allocation size for the query, in bytes. If None, server will choose its default allocation size. Use with caution. Default is None.
overpass_rate_limitbool: If True, check the Overpass server status endpoint for how long to pause before making request. Necessary if server uses slot management, but can be set to False if you are running your own overpass instance without rate limiting. Default is True.
overpass_settingsstr: Settings string for Overpass queries. Default is “[out:json][timeout:{timeout}]{maxsize}”. By default, the {timeout} and {maxsize} values are set dynamically by OSMnx when used. To query, for example, historical OSM data as of a certain date: ‘[out:json][timeout:90][date:”2019-10-28T19:20:00Z”]’. Use with caution.
overpass_urlstr: The base API url to use for Overpass queries. Default is “https://overpass-api.de/api”.
requests_kwargsdict: Optional keyword args to pass to the requests package when connecting to APIs, for example to configure authentication or provide a path to a local certificate file. More info on options such as auth, cert, verify, and proxies can be found in the requests package advanced docs. Default is {}.
requests_timeoutint: The timeout interval in seconds for HTTP requests, and (when applicable) for Overpass server to use for executing the query. Default is 180.
timeoutint: Do not use, deprecated. Use requests_timeout instead.
use_cachebool: If True, cache HTTP responses locally instead of calling API repeatedly for the same request. Default is True.
useful_tags_nodelist: OSM “node” tags to add as graph node attributes, when present in the data retrieved from OSM. Default is [“ref”, “highway”].
useful_tags_waylist: OSM “way” tags to add as graph edge attributes, when present in the data retrieved from OSM. Default is [“bridge”, “tunnel”, “oneway”, “lanes”, “ref”, “name”, “highway”, “maxspeed”, “service”, “access”, “area”, “landuse”, “width”, “est_width”, “junction”].

osmnx.simplification module#

Simplify, correct, and consolidate network topology.

osmnx.simplification._build_path(G, endpoint, endpoint_successor, endpoints)

Build a path of nodes from one endpoint node to next endpoint node.

Parameters:

G (networkx.MultiDiGraph) – input graph
endpoint (int) – the endpoint node from which to start the path
endpoint_successor (int) – the successor of endpoint through which the path to the next endpoint will be built
endpoints (set) – the set of all nodes in the graph that are endpoints

Returns:

path – the first and last items in the resulting path list are endpoint nodes, and all other items are interstitial nodes that can be removed subsequently

Return type:

list

osmnx.simplification._consolidate_intersections_rebuild_graph(G, tolerance=10, reconnect_edges=True)

Consolidate intersections comprising clusters of nearby nodes.

Merge nodes and return a rebuilt graph with consolidated intersections and reconnected edge geometries.

The tolerance argument should be adjusted to approximately match street design standards in the specific street network, and you should always use a projected graph to work in meaningful and consistent units like meters.

Returned graph’s node IDs represent clusters rather than osmids. Refer to nodes’ osmid_original attributes for original osmids. If multiple nodes were merged together, the osmid_original attribute is a list of merged nodes’ osmids.

Parameters:

G (networkx.MultiDiGraph) – a projected graph
tolerance (float) – nodes are buffered to this distance (in graph’s geometry’s units) and subsequent overlaps are dissolved into a single node
reconnect_edges (bool) – ignored if rebuild_graph is not True. if True, reconnect edges and their geometries in rebuilt graph to the consolidated nodes and update edge length attributes; if False, returned graph has no edges (which is faster if you just need topologically consolidated intersection counts).

Returns:

H – a rebuilt graph with consolidated intersections and reconnected edge geometries

Return type:

networkx.MultiDiGraph

osmnx.simplification._get_paths_to_simplify(G, endpoint_attrs)

Generate all the paths to be simplified between endpoint nodes.

The path is ordered from the first endpoint, through the interstitial nodes, to the second endpoint.

Parameters:

G (networkx.MultiDiGraph) – input graph
endpoint_attrs (iterable) – An iterable of edge attribute names for relaxing the strictness of endpoint determination. If not None, a node is an endpoint if its incident edges have different values then each other for any of the edge attributes in endpoint_attrs.

Yields:

path_to_simplify (list) – a generator of paths to simplify

osmnx.simplification._is_endpoint(G, node, endpoint_attrs)

Determine if a node is a true endpoint of an edge.

Return True if the node is a “true” endpoint of an edge in the network, otherwise False. OpenStreetMap data includes many nodes that exist only as geometric vertices to allow ways to curve. A true edge endpoint is a node that satisfies at least 1 of the following 4 rules:

It is its own neighbor (ie, it self-loops).

2) Or, it has no incoming edges or no outgoing edges (ie, all its incident edges are inbound or all its incident edges are outbound).

Or, it does not have exactly two neighbors and degree of 2 or 4.

4) Or, if endpoint_attrs is not None, and its incident edges have different values than each other for any of the edge attributes in endpoint_attrs.

Parameters:

G (networkx.MultiDiGraph) – input graph
node (int) – the node to examine
endpoint_attrs (iterable) – An iterable of edge attribute names for relaxing the strictness of endpoint determination. If not None, a node is an endpoint if its incident edges have different values then each other for any of the edge attributes in endpoint_attrs.

Return type:

bool

osmnx.simplification._merge_nodes_geometric(G, tolerance)

Geometrically merge nodes within some distance of each other.

Parameters:

G (networkx.MultiDiGraph) – a projected graph
tolerance (float) – buffer nodes to this distance (in graph’s geometry’s units) then merge overlapping polygons into a single polygon via a unary union operation

Returns:

merged – the merged overlapping polygons of the buffered nodes

Return type:

GeoSeries

osmnx.simplification._remove_rings(G, endpoint_attrs)

Remove all self-contained rings from a graph.

This identifies any connected components that form a self-contained ring without any endpoints, and removes them from the graph.

Parameters:

G (networkx.MultiDiGraph) – input graph
endpoint_attrs (iterable) – An iterable of edge attribute names for relaxing the strictness of endpoint determination. If not None, a node is an endpoint if its incident edges have different values then each other for any of the edge attributes in endpoint_attrs.

Returns:

G – graph with self-contained rings removed

Return type:

networkx.MultiDiGraph

osmnx.simplification.consolidate_intersections(G, tolerance=10, rebuild_graph=True, dead_ends=False, reconnect_edges=True)

Consolidate intersections comprising clusters of nearby nodes.

Merges nearby nodes and returns either their centroids or a rebuilt graph with consolidated intersections and reconnected edge geometries. The tolerance argument should be adjusted to approximately match street design standards in the specific street network, and you should always use a projected graph to work in meaningful and consistent units like meters. Note the tolerance represents a per-node buffering radius: for example, to consolidate nodes within 10 meters of each other, use tolerance=5.

When rebuild_graph=False, it uses a purely geometrical (and relatively fast) algorithm to identify “geometrically close” nodes, merge them, and return just the merged intersections’ centroids. When rebuild_graph=True, it uses a topological (and slower but more accurate) algorithm to identify “topologically close” nodes, merge them, then rebuild/return the graph. Returned graph’s node IDs represent clusters rather than osmids. Refer to nodes’ osmid_original attributes for original osmids. If multiple nodes were merged together, the osmid_original attribute is a list of merged nodes’ osmids.

Divided roads are often represented by separate centerline edges. The intersection of two divided roads thus creates 4 nodes, representing where each edge intersects a perpendicular edge. These 4 nodes represent a single intersection in the real world. A similar situation occurs with roundabouts and traffic circles. This function consolidates nearby nodes by buffering them to an arbitrary distance, merging overlapping buffers, and taking their centroid.

Parameters:

G (networkx.MultiDiGraph) – a projected graph
tolerance (float) – nodes are buffered to this distance (in graph’s geometry’s units) and subsequent overlaps are dissolved into a single node
rebuild_graph (bool) – if True, consolidate the nodes topologically, rebuild the graph, and return as networkx.MultiDiGraph. if False, consolidate the nodes geometrically and return the consolidated node points as geopandas.GeoSeries
dead_ends (bool) – if False, discard dead-end nodes to return only street-intersection points
reconnect_edges (bool) – ignored if rebuild_graph is not True. if True, reconnect edges and their geometries in rebuilt graph to the consolidated nodes and update edge length attributes; if False, returned graph has no edges (which is faster if you just need topologically consolidated intersection counts).

Returns:

if rebuild_graph=True, returns MultiDiGraph with consolidated intersections and reconnected edge geometries. if rebuild_graph=False, returns GeoSeries of shapely Points representing the centroids of street intersections

Return type:

networkx.MultiDiGraph or geopandas.GeoSeries

osmnx.simplification.simplify_graph(G, strict=None, edge_attrs_differ=None, endpoint_attrs=None, remove_rings=True, track_merged=False)

Simplify a graph’s topology by removing interstitial nodes.

This simplifies graph topology by removing all nodes that are not intersections or dead-ends, by creating an edge directly between the end points that encapsulate them while retaining the full geometry of the original edges, saved as a new geometry attribute on the new edge.

Note that only simplified edges receive a geometry attribute. Some of the resulting consolidated edges may comprise multiple OSM ways, and if so, their multiple attribute values are stored as a list. Optionally, the simplified edges can receive a merged_edges attribute that contains a list of all the (u, v) node pairs that were merged together.

Use the edge_attrs_differ parameter to relax simplification strictness. For example, edge_attrs_differ=[‘osmid’] will retain every node whose incident edges have different OSM IDs. This lets you keep nodes at elbow two-way intersections (but be aware that sometimes individual blocks have multiple OSM IDs within them too). You could also use this parameter to retain nodes where sidewalks or bike lanes begin/end in the middle of a block.

Parameters:

G (networkx.MultiDiGraph) – input graph
strict (bool) – deprecated, do not use
edge_attrs_differ (iterable) – An iterable of edge attribute names for relaxing the strictness of endpoint determination. If not None, a node is an endpoint if its incident edges have different values then each other for any of the edge attributes in edge_attrs_differ.
endpoint_attrs (iterable) – deprecated, do not use
remove_rings (bool) – if True, remove isolated self-contained rings that have no endpoints
track_merged (bool) – if True, add merged_edges attribute on simplified edges, containing a list of all the (u, v) node pairs that were merged together

Returns:

G – topologically simplified graph, with a new geometry attribute on each simplified edge

Return type:

networkx.MultiDiGraph

osmnx.speed module#

Calculate graph edge speeds and travel times.

osmnx.speed.add_edge_speeds(G, hwy_speeds=None, fallback=None, precision=None, agg=numpy.mean)

Do not use: deprecated.

Use the routing.add_edge_speeds function instead.

Parameters:

G (networkx.MultiDiGraph) – deprecated, do not use
hwy_speeds (dict) – deprecated, do not use
fallback (numeric) – deprecated, do not use
precision (int) – deprecated, do not use
agg (function) – deprecated, do not use

Returns:

Return type:

networkx.MultiDiGraph

osmnx.speed.add_edge_travel_times(G, precision=None)

Do not use: deprecated.

Use the routing.add_edge_travel_times function instead.

Parameters:

G (networkx.MultiDiGraph) – deprecated, do not use
precision (int) – deprecated, do not use

Returns:

Return type:

networkx.MultiDiGraph

osmnx.stats module#

Calculate geometric and topological network measures.

This module defines streets as the edges in an undirected representation of the graph. Using undirected graph edges prevents double-counting bidirectional edges of a two-way street, but may double-count a divided road’s separate centerlines with different end point nodes. If clean_periphery=True when the graph was created (which is the default parameterization), then you will get accurate node degrees (and in turn streets-per-node counts) even at the periphery of the graph.

You can use NetworkX directly for additional topological network measures.

osmnx.stats.basic_stats(G, area=None, clean_int_tol=None)

Calculate basic descriptive geometric and topological measures of a graph.

Density measures are only calculated if area is provided and clean intersection measures are only calculated if clean_int_tol is provided.

Parameters:

G (networkx.MultiDiGraph) – input graph
area (float) – if not None, calculate density measures and use this value (in square meters) as the denominator
clean_int_tol (float) – if not None, calculate consolidated intersections count (and density, if area is also provided) and use this tolerance value; refer to the simplification.consolidate_intersections function documentation for details

Returns:

stats –

dictionary containing the following keys

circuity_avg - see circuity_avg function documentation
clean_intersection_count - see clean_intersection_count function documentation
clean_intersection_density_km - clean_intersection_count per sq km
edge_density_km - edge_length_total per sq km
edge_length_avg - edge_length_total / m
edge_length_total - see edge_length_total function documentation
intersection_count - see intersection_count function documentation
intersection_density_km - intersection_count per sq km
k_avg - graph’s average node degree (in-degree and out-degree)
m - count of edges in graph
n - count of nodes in graph
node_density_km - n per sq km
self_loop_proportion - see self_loop_proportion function documentation
street_density_km - street_length_total per sq km
street_length_avg - street_length_total / street_segment_count
street_length_total - see street_length_total function documentation
street_segment_count - see street_segment_count function documentation
streets_per_node_avg - see streets_per_node_avg function documentation
streets_per_node_counts - see streets_per_node_counts function documentation
streets_per_node_proportions - see streets_per_node_proportions function documentation

Return type:

dict

osmnx.stats.circuity_avg(Gu)

Calculate average street circuity using edges of undirected graph.

Circuity is the sum of edge lengths divided by the sum of straight-line distances between edge endpoints. Calculates straight-line distance as euclidean distance if projected or great-circle distance if unprojected.

Parameters:: Gu (networkx.MultiGraph) – undirected input graph
Returns:: circuity_avg – the graph’s average undirected edge circuity
Return type:: float

osmnx.stats.count_streets_per_node(G, nodes=None)

Count how many physical street segments connect to each node in a graph.

This function uses an undirected representation of the graph and special handling of self-loops to accurately count physical streets rather than directed edges. Note: this function is automatically run by all the graph.graph_from_x functions prior to truncating the graph to the requested boundaries, to add accurate street_count attributes to each node even if some of its neighbors are outside the requested graph boundaries.

Parameters:

G (networkx.MultiDiGraph) – input graph
nodes (list) – which node IDs to get counts for. if None, use all graph nodes, otherwise calculate counts only for these node IDs

Returns:

streets_per_node – counts of how many physical streets connect to each node, with keys = node ids and values = counts

Return type:

dict

osmnx.stats.edge_length_total(G)

Calculate graph’s total edge length.

Parameters:: G (networkx.MultiDiGraph) – input graph
Returns:: length – total length (meters) of edges in graph
Return type:: float

osmnx.stats.intersection_count(G=None, min_streets=2)

Count the intersections in a graph.

Intersections are defined as nodes with at least min_streets number of streets incident on them.

Parameters:

G (networkx.MultiDiGraph) – input graph
min_streets (int) – a node must have at least min_streets incident on them to count as an intersection

Returns:

count – count of intersections in graph

Return type:

int

osmnx.stats.self_loop_proportion(Gu)

Calculate percent of edges that are self-loops in a graph.

A self-loop is defined as an edge from node u to node v where u==v.

Parameters:: Gu (networkx.MultiGraph) – undirected input graph
Returns:: proportion – proportion of graph edges that are self-loops
Return type:: float

osmnx.stats.street_length_total(Gu)

Calculate graph’s total street segment length.

Parameters:: Gu (networkx.MultiGraph) – undirected input graph
Returns:: length – total length (meters) of streets in graph
Return type:: float

osmnx.stats.street_segment_count(Gu)

Count the street segments in a graph.

Parameters:: Gu (networkx.MultiGraph) – undirected input graph
Returns:: count – count of street segments in graph
Return type:: int

osmnx.stats.streets_per_node(G)

Count streets (undirected edges) incident on each node.

Parameters:: G (networkx.MultiDiGraph) – input graph
Returns:: spn – dictionary with node ID keys and street count values
Return type:: dict

osmnx.stats.streets_per_node_avg(G)

Calculate graph’s average count of streets per node.

Parameters:: G (networkx.MultiDiGraph) – input graph
Returns:: spna – average count of streets per node
Return type:: float

osmnx.stats.streets_per_node_counts(G)

Calculate streets-per-node counts.

Parameters:: G (networkx.MultiDiGraph) – input graph
Returns:: spnc – dictionary keyed by count of streets incident on each node, and with values of how many nodes in the graph have this count
Return type:: dict

osmnx.stats.streets_per_node_proportions(G)

Calculate streets-per-node proportions.

Parameters:: G (networkx.MultiDiGraph) – input graph
Returns:: spnp – dictionary keyed by count of streets incident on each node, and with values of what proportion of nodes in the graph have this count
Return type:: dict

osmnx.truncate module#

Truncate graph by distance, bounding box, or polygon.

osmnx.truncate.largest_component(G, strongly=False)

Get subgraph of G’s largest weakly/strongly connected component.

Parameters:

G (networkx.MultiDiGraph) – input graph
strongly (bool) – if True, return the largest strongly instead of weakly connected component

Returns:

G – the largest connected component subgraph of the original graph

Return type:

networkx.MultiDiGraph

osmnx.truncate.truncate_graph_bbox(G, north=None, south=None, east=None, west=None, bbox=None, truncate_by_edge=False, retain_all=False, quadrat_width=None, min_num=None)

Remove every node in graph that falls outside a bounding box.

Parameters:

G (networkx.MultiDiGraph) – input graph
north (float) – deprecated, do not use
south (float) – deprecated, do not use
east (float) – deprecated, do not use
west (float) – deprecated, do not use
bbox (tuple of floats) – bounding box as (north, south, east, west)
truncate_by_edge (bool) – if True, retain nodes outside bounding box if at least one of node’s neighbors is within the bounding box
retain_all (bool) – if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component.
quadrat_width (float) – deprecated, do not use
min_num (int) – deprecated, do not use

Returns:

G – the truncated graph

Return type:

networkx.MultiDiGraph

osmnx.truncate.truncate_graph_dist(G, source_node, max_dist=1000, weight='length', retain_all=False)

Remove every node farther than some network distance from source_node.

This function can be slow for large graphs, as it must calculate shortest path distances between source_node and every other graph node.

Parameters:

G (networkx.MultiDiGraph) – input graph
source_node (int) – node in graph from which to measure network distances to other nodes
max_dist (float) – remove every node in the graph that is greater than this distance (in same units as weight attribute) along the network from source_node
weight (string) – graph edge attribute to use to measure distance
retain_all (bool) – if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component.

Returns:

G – the truncated graph

Return type:

networkx.MultiDiGraph

osmnx.truncate.truncate_graph_polygon(G, polygon, retain_all=False, truncate_by_edge=False, quadrat_width=None, min_num=None)

Remove every node in graph that falls outside a (Multi)Polygon.

Parameters:

G (networkx.MultiDiGraph) – input graph
polygon (shapely.geometry.Polygon or shapely.geometry.MultiPolygon) – only retain nodes in graph that lie within this geometry
retain_all (bool) – if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component.
truncate_by_edge (bool) – if True, retain nodes outside boundary polygon if at least one of node’s neighbors is within the polygon
quadrat_width (float) – deprecated, do not use
min_num (int) – deprecated, do not use

Returns:

G – the truncated graph

Return type:

networkx.MultiDiGraph

osmnx.utils module#

General utility functions.

osmnx.utils._get_logger(level, name, filename)

Create a logger or return the current one if already instantiated.

Parameters:

level (int) – one of Python’s logger.level constants
name (string) – name of the logger
filename (string) – name of the log file, without file extension

Returns:

logger

Return type:

logging.logger

osmnx.utils.citation(style='bibtex')

Print the OSMnx package’s citation information.

Boeing, G. (2017). OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks. Computers, Environment and Urban Systems, 65, 126-139. https://doi.org/10.1016/j.compenvurbsys.2017.05.004

Parameters:: style (string {"apa", "bibtex", "ieee"}) – citation format, either APA or BibTeX or IEEE
Return type:: None

osmnx.utils.config(all_oneway=False, bidirectional_network_types=['walk'], cache_folder='./cache', cache_only_mode=False, data_folder='./data', default_accept_language=None, default_access='["access"!~"private"]', default_crs='epsg:4326', default_referer=None, default_user_agent=None, imgs_folder='./images', log_console=False, log_file=False, log_filename='osmnx', log_level=20, log_name='OSMnx', logs_folder='./logs', max_query_area_size=2500000000, memory=None, nominatim_endpoint=None, nominatim_key=None, osm_xml_node_attrs=None, osm_xml_node_tags=None, osm_xml_way_attrs=None, osm_xml_way_tags=None, overpass_endpoint=None, overpass_rate_limit=True, overpass_settings='[out:json][timeout:{timeout}]{maxsize}', requests_kwargs={}, timeout=None, use_cache=True, useful_tags_node=['ref', 'highway'], useful_tags_way=['bridge', 'tunnel', 'oneway', 'lanes', 'ref', 'name', 'highway', 'maxspeed', 'service', 'access', 'area', 'landuse', 'width', 'est_width', 'junction'])

Do not use: deprecated. Use the settings module directly.

Parameters:

all_oneway (bool) – deprecated
bidirectional_network_types (list) – deprecated
cache_folder (string or pathlib.Path) – deprecated
data_folder (string or pathlib.Path) – deprecated
cache_only_mode (bool) – deprecated
default_accept_language (string) – deprecated
default_access (string) – deprecated
default_crs (string) – deprecated
default_referer (string) – deprecated
default_user_agent (string) – deprecated
imgs_folder (string or pathlib.Path) – deprecated
log_file (bool) – deprecated
log_filename (string) – deprecated
log_console (bool) – deprecated
log_level (int) – deprecated
log_name (string) – deprecated
logs_folder (string or pathlib.Path) – deprecated
max_query_area_size (int) – deprecated
memory (int) – deprecated
nominatim_endpoint (string) – deprecated
nominatim_key (string) – deprecated
osm_xml_node_attrs (list) – deprecated
osm_xml_node_tags (list) – deprecated
osm_xml_way_attrs (list) – deprecated
osm_xml_way_tags (list) – deprecated
overpass_endpoint (string) – deprecated
overpass_rate_limit (bool) – deprecated
overpass_settings (string) – deprecated
requests_kwargs (dict) – deprecated
timeout (int) – deprecated
use_cache (bool) – deprecated
useful_tags_node (list) – deprecated
useful_tags_way (list) – deprecated

Return type:

None

osmnx.utils.log(message, level=None, name=None, filename=None)

Write a message to the logger.

This logs to file and/or prints to the console (terminal), depending on the current configuration of settings.log_file and settings.log_console.

Parameters:

message (string) – the message to log
level (int) – one of Python’s logger.level constants
name (string) – name of the logger
filename (string) – name of the log file, without file extension

Return type:

None

osmnx.utils.ts(style='datetime', template=None)

Return current local timestamp as a string.

Parameters:

style (string {"datetime", "date", "time"}) – format the timestamp with this built-in style
template (string) – if not None, format the timestamp with this format string instead of one of the built-in styles

Returns:

ts – local timestamp string

Return type:

string

osmnx.utils_geo module#

Geospatial utility functions.

osmnx.utils_geo._consolidate_subdivide_geometry(geometry)

Consolidate and subdivide some geometry.

Consolidate a geometry into a convex hull, then subdivide it into smaller sub-polygons if its area exceeds max size (in geometry’s units). Configure the max size via max_query_area_size in the settings module.

When the geometry has a very large area relative to its vertex count, the resulting MultiPolygon’s boundary may differ somewhat from the input, due to the way long straight lines are projected. You can interpolate additional vertices along your input geometry’s exterior to mitigate this.

Parameters:: geometry (shapely.geometry.Polygon or shapely.geometry.MultiPolygon) – the projected (in meter units) geometry to consolidate and subdivide
Returns:: geometry
Return type:: shapely.geometry.MultiPolygon

osmnx.utils_geo._intersect_index_quadrats(geometries, polygon)

Identify geometries that intersect a (Multi)Polygon.

Uses an r-tree spatial index and cuts polygon up into smaller sub-polygons for r-tree acceleration. Ensure that geometries and polygon are in the same coordinate reference system.

Parameters:

geometries (geopandas.GeoSeries) – the geometries to intersect with the polygon
polygon (shapely.geometry.Polygon or shapely.geometry.MultiPolygon) – the polygon to intersect with the geometries

Returns:

geoms_in_poly – set of the index labels of the geometries that intersected the polygon

Return type:

set

osmnx.utils_geo._quadrat_cut_geometry(geometry, quadrat_width)

Split a Polygon or MultiPolygon up into sub-polygons of a specified size.

Parameters:

geometry (shapely.geometry.Polygon or shapely.geometry.MultiPolygon) – the geometry to split up into smaller sub-polygons
quadrat_width (float) – width (in geometry’s units) of quadrat squares with which to split up the geometry

Returns:

geometry

Return type:

shapely.geometry.MultiPolygon

osmnx.utils_geo._round_linestring_coords(ls, precision)

Round the coordinates of a shapely LineString to some decimal precision.

Parameters:

ls (shapely.geometry.LineString) – the LineString to round the coordinates of
precision (int) – decimal precision to round coordinates to

Return type:

shapely.geometry.LineString

osmnx.utils_geo._round_multilinestring_coords(mls, precision)

Round the coordinates of a shapely MultiLineString to some decimal precision.

Parameters:

mls (shapely.geometry.MultiLineString) – the MultiLineString to round the coordinates of
precision (int) – decimal precision to round coordinates to

Return type:

shapely.geometry.MultiLineString

osmnx.utils_geo._round_multipoint_coords(mpt, precision)

Round the coordinates of a shapely MultiPoint to some decimal precision.

Parameters:

mpt (shapely.geometry.MultiPoint) – the MultiPoint to round the coordinates of
precision (int) – decimal precision to round coordinates to

Return type:

shapely.geometry.MultiPoint

osmnx.utils_geo._round_multipolygon_coords(mp, precision)

Round the coordinates of a shapely MultiPolygon to some decimal precision.

Parameters:

mp (shapely.geometry.MultiPolygon) – the MultiPolygon to round the coordinates of
precision (int) – decimal precision to round coordinates to

Return type:

shapely.geometry.MultiPolygon

osmnx.utils_geo._round_point_coords(pt, precision)

Round the coordinates of a shapely Point to some decimal precision.

Parameters:

pt (shapely.geometry.Point) – the Point to round the coordinates of
precision (int) – decimal precision to round coordinates to

Return type:

shapely.geometry.Point

osmnx.utils_geo._round_polygon_coords(p, precision)

Round the coordinates of a shapely Polygon to some decimal precision.

Parameters:

p (shapely.geometry.Polygon) – the polygon to round the coordinates of
precision (int) – decimal precision to round coordinates to

Return type:

shapely.geometry.Polygon

osmnx.utils_geo.bbox_from_point(point, dist=1000, project_utm=False, return_crs=False)

Create a bounding box around a (lat, lon) point.

Create a bounding box some distance (in meters) in each direction (north, south, east, and west) from the center point and optionally project it.

Parameters:

point (tuple) – the (lat, lon) center point to create the bounding box around
dist (int) – bounding box distance in meters from the center point
project_utm (bool) – if True, return bounding box as UTM-projected coordinates
return_crs (bool) – if True, and project_utm=True, return the projected CRS too

Returns:

bbox or bbox, crs – (north, south, east, west) or ((north, south, east, west), crs)

Return type:

tuple or tuple, crs

osmnx.utils_geo.bbox_to_poly(north=None, south=None, east=None, west=None, bbox=None)

Convert bounding box coordinates to shapely Polygon.

Parameters:

north (float) – deprecated, do not use
south (float) – deprecated, do not use
east (float) – deprecated, do not use
west (float) – deprecated, do not use
bbox (tuple of floats) – bounding box as (north, south, east, west)

Return type:

shapely.geometry.Polygon

osmnx.utils_geo.interpolate_points(geom, dist)

Interpolate evenly spaced points along a LineString.

The spacing is approximate because the LineString’s length may not be evenly divisible by it.

Parameters:

geom (shapely.geometry.LineString) – a LineString geometry
dist (float) – spacing distance between interpolated points, in same units as geom. smaller values accordingly generate more points.

Yields:

points (generator) – tuples of (x, y) floats of the interpolated points’ coordinates

osmnx.utils_geo.round_geometry_coords(geom, precision)

Do not use: deprecated.

Parameters:

geom (shapely.geometry.geometry {Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon}) – deprecated, do not use
precision (int) – deprecated, do not use

Return type:

shapely.geometry.geometry

osmnx.utils_geo.sample_points(G, n)

Randomly sample points constrained to a spatial graph.

This generates a graph-constrained uniform random sample of points. Unlike typical spatially uniform random sampling, this method accounts for the graph’s geometry. And unlike equal-length edge segmenting, this method guarantees uniform randomness.

Parameters:

G (networkx.MultiGraph) – graph from which to sample points. should be undirected (to avoid oversampling bidirectional edges) and projected (for accurate point interpolation)
n (int) – how many points to sample

Returns:

points – the sampled points, multi-indexed by (u, v, key) of the edge from which each point was drawn

Return type:

geopandas.GeoSeries

osmnx.utils_graph module#

Graph utility functions.

osmnx.utils_graph.get_digraph(G, weight='length')

Do not use: deprecated.

Use the convert.to_digraph function instead.

Parameters:

G (networkx.MultiDiGraph) – deprecated, do not use
weight (string) – deprecated, do not use

Return type:

networkx.DiGraph

osmnx.utils_graph.get_largest_component(G, strongly=False)

Do not use: deprecated.

Use the truncate.largest_component function instead.

Parameters:

G (networkx.MultiDiGraph) – deprecated, do not use
strongly (bool) – deprecated, do not use

Returns:

Return type:

networkx.MultiDiGraph

osmnx.utils_graph.get_route_edge_attributes(G, route, attribute=None, minimize_key='length', retrieve_default=None)

Do not use: deprecated.

Use the routing.route_to_gdf function instead.

Parameters:

G (networkx.MultiDiGraph) – deprecated, do not use
route (list) – deprecated, do not use
attribute (string) – deprecated, do not use
minimize_key (string) – deprecated, do not use
retrieve_default (Callable[Tuple[Any, Any], Any]) – deprecated, do not use

Returns:

attribute_values

Return type:

list

osmnx.utils_graph.get_undirected(G)

Do not use: deprecated.

Use the convert.to_undirected function instead.

Parameters:: G (networkx.MultiDiGraph) – deprecated, do not use
Return type:: networkx.MultiGraph

osmnx.utils_graph.graph_from_gdfs(gdf_nodes, gdf_edges, graph_attrs=None)

Do not use: deprecated.

Use the convert.graph_from_gdfs function instead.

Parameters:

gdf_nodes (geopandas.GeoDataFrame) – deprecated, do not use
gdf_edges (geopandas.GeoDataFrame) – deprecated, do not use
graph_attrs (dict) – deprecated, do not use

Returns:

Return type:

networkx.MultiDiGraph

osmnx.utils_graph.graph_to_gdfs(G, nodes=True, edges=True, node_geometry=True, fill_edge_geometry=True)

Do not use: deprecated.

Use the convert.graph_to_gdfs function instead.

Parameters:

G (networkx.MultiDiGraph) – deprecated, do not use
nodes (bool) – deprecated, do not use
edges (bool) – deprecated, do not use
node_geometry (bool) – deprecated, do not use
fill_edge_geometry (bool) – deprecated, do not use

Return type:

geopandas.GeoDataFrame or tuple

osmnx.utils_graph.remove_isolated_nodes(G, warn=True)

Do not use: deprecated.

Parameters:

G (networkx.MultiDiGraph) – deprecated, do not use
warn (bool) – deprecated, do not use

Returns:

Return type:

networkx.MultiDiGraph

osmnx.utils_graph.route_to_gdf(G, route, weight='length')

Do not use: deprecated.

Use the routing.route_to_gdf function instead.

Parameters:

G (networkx.MultiDiGraph) – deprecated, do not use
route (list) – deprecated, do not use
weight (string) – deprecated, do not use

Returns:

gdf_edges

Return type:

geopandas.GeoDataFrame

osmnx._version module#

OSMnx package version information.