ohsome 0.1.0b2

A Python client for the ohsome API

ohsome-py: A Python client for the ohsome API

The ohsome-py package helps you extract and analyse OpenStreetMap history data using the ohsome API and Python. It handles queries to the ohsome API and converts its responses to Pandas and GeoPandas data frames to facilitate easy data handling and analysis.

The ohsome API provides various endpoints for data aggregation, data extraction and contributions to analyse the history of OSM data. Take a look at the documentation of the ohsome API or go through the Tutorial to get started on how to use ohsome-py.

Installation

ohsome-py requires Python >= 3.6. The easiest way to install ohsome-py is using pip:

$ pip install ohsome

If you want to run the Juypter Notebook Tutorial you also need to install jupyter and matplotlib:

$ pip install jupyter matplotlib

Usage

All queries are handled by an OhsomeClient object, which also provides information about the current ohsome API instance, e.g. start_timestamp and end_timestamp indicate the earliest and the latest possible dates for a query.

from ohsome import OhsomeClient
client = OhsomeClient()
client.start_timestamp # --> '2007-10-08T00:00:00Z'
client.end_timestamp # --> '2021-01-23T03:00Z'

1. Data Aggregation

Example: The Number of OSM ways tagged as landuse=farmland using the /elements/count endpoint:

response = client.elements.count.post(bboxes=[8.625,49.3711,8.7334,49.4397],
				      time="2014-01-01",
				      filter="landuse=farmland and type:way")

The single components of the endpoint URL are appended as method calls to the OhsomeClient object. Use automatic code completion to find valid endpoints. Alternatively, you can define the endpoint as argument in the .post() method.

response = client.post(endpoint="elements/count",
		       bboxes=[8.625,49.3711,8.7334,49.4397],
		       time="2020-01-01",
		       filter="landuse=farmland and type:way")

Responses from the data aggregation endpoints can be converted to a pandas.DataFrame object using the OhsomeResponse.as_dataframe() method.

response_df = response.as_dataframe()

2. Data Extraction

Example: OSM ways tagged as landuse=farmland including their geometry and tags using the /elements/geometry endpoint:

client = OhsomeClient()
response = client.elements.geometry.post(bboxes=[8.625,49.3711,8.7334,49.4397],
					 time="2020-01-01",
					 filter="landuse=farmland and type:way",
					 properties="tags")
response_gdf = response.as_dataframe()

Responses from the data extraction endpoint can be converted to a geopandas.GeoDataFrame using the OhsomeResponse.as_dataframe() method, since the data contains geometries.

Query Parameters

All query parameters are described in the ohsome API documentation and can be passed as string objects to the post() method. Other Python data types are accepted as well.

Boundary

The boundary of the query can be defined using the bpolys, bboxes and bcircles parameters. The coordinates have to be given in WGS 84 (EPSG:4326).

bpolys

The bpolys parameter can be passed as a geopandas.GeoDataFrame containing the polygon features.

bpolys = gpd.read_file("./data/polygons.geojson")
client.elements.count.groupByBoundary.post(bpolys=bpolys, filter="amenity=restaurant")

bboxes

The bboxes parameter contains the coordinates of one or several bounding boxes.

bboxes = [8.7137,49.4096,8.717,49.4119] # one bounding box
bboxes = [[8.7137,49.4096,8.717,49.4119], [8.7137,49.4096,8.717,49.4119]]
bboxes = {"A": [8.67066, 49.41423, 8.68177, 49.4204],
	  "B": [8.67066, 49.41423, 8.68177, 49.4204]}

bcircles

The bcircles parameter contains one or several circles defined through the coordinates of the centroids and the radius in meters.

bcircles = [8.7137,49.4096, 100]
bcircles = [[8.7137,49.4096, 100], [8.7137,49.4096, 300]]
bcircles = {"Circle1": [8.695, 49.41, 200],
	    "Circle2": [8.696, 49.41, 200]}

Time

The time parameter must be ISO-8601 conform can be passed in several ways

time = '2018-01-01/2018-03-01/P1M'
time = ['2018-01-01', '2018-02-01', '2018-03-01']
time = datetime.datetime(year=2018, month=3, day=1)
time = pandas.date_range("2018-01-01", periods=3, freq="M")

Contribution Guidelines

If you want to contribute to this project, please fork the repository or create a new branch containing your changes.

Install the pre-commit hooks in our local git repo before commiting to ensure homogenous code style.

$ pre-commit install

Run the tests inside the repo using pytest (and poetry if you like) to make sure everything works.

$ poetry run pytest

Running the tests in a docker container containing an ohsome API instance is faster, but not mandatory. To set up and start such a docker container run the following command before running the tests.

$ docker run -dt --name ohsome-api -p 8080:8080 julianpsotta/ohsome-api:1.3.2

Create a pull request to the development branch once it is ready to be merged.

References

The design of this package was inspired by the blog post Using Python to Implement a Fluent Interface to Any REST API by Elmer Thomas.