| Name | osm-flex JSON |
| Version |
1.1.0
JSON |
| download |
| home_page | |
| Summary | Python package for flexible data extraction from OpenStreetMap |
| upload_time | 2023-11-21 14:22:11 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.9 |
| license | GPL-3.0 |
| keywords |
openstreetmap
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# osm-flex
<img align="right" width="200" alt="Logo" src="https://raw.githubusercontent.com/osm-flex/osm-flex/develop/doc/logo_osm-flex.png">
[](https://github.com/osm-flex/osm-flex)
[](https://github.com/osm-flex/osm-flex)
[](https://badge.fury.io/py/osm-flex)
[](https://pypistats.org/packages/osm-flex)
[](https://osm-flex.readthedocs.io/en/latest/?badge=latest)
[](https://fair-software.eu)
[](https://doi.org/10.5281/zenodo.8082963)
Python package for flexible data extraction from OpenStreetMap. This packages allows to
1. download OSM data dumps
2. [optional] clip to desired shape
2. extract specific features to geodataframes
## Documentation
Please refer to the [ReadTheDocs](https://osm-flex.readthedocs.io/en/latest/?badge=latest) of this project for the full documentation of all functions.
## Installation
```
conda create -n osm-flex cartopy geopandas
conda activate osm-flex
pip install osm-flex
```
---
NOTE
This package requires shapely v2.0 or later. Installing this package in an existing environment might overwrite older versions.
The (optional) clipping functionalities require manual installation of osmconvert or osmosis. See tutorial 1 for details.
---
## Example
Download osm data for Switzerland from geofabrik.
```python
import osm_flex.download as dl
iso3 = 'CHE'
dl.get_country_geofabrik(iso3)
```
Extract all buildings related to education and extract all polygons with forests.
```python
import osm_flex.extract as ex
from osm_flex.config import OSM_DATA_DIR
path_che_dump = OSM_DATA_DIR.joinpath('switzerland-latest.osm.pbf')
```
```python
gdf_ch_education = ex.extract_cis(path_che_dump, 'education')
```
<img title="Education" alt="Education GeodataFrame" src="./doc/education_ch.png">
```python
gdf_ch_forest = ex.extract(
path_che_dump, 'multipolygons', ['landuse', 'name'], "landuse='forest'"
)
```
<img title="Forests" alt="Forest map " src="./doc/forest_ch.png">
## Running Tests
Follow installation instructions. Then,
```
python -m pip install -e "./[tests]"
pytest
```
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