| Name | geoparquet-pydantic JSON |
| Version |
0.0.1
JSON |
| download |
| home_page | |
| Summary | Read/write geoparquet with the geojson-pydanic models. |
| upload_time | 2024-02-21 02:50:25 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.11 |
| license | MIT |
| keywords |
geoparquet
pydantic
geospatial
|
| VCS |
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| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
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# GeoParquet-Pydantic
**Motivation:** This project started at the 2024 San Fransisco GeoParquet Community hackathon, and arose out of a simple observation:
why must Python users install the *massive* GDAL dependency (typically via GeoPandas) to do simple GeoJSON<>GeoParquet conversions.
**Is this library the right choice for you?:**
* Do you need to use a wide variety of Geospatial functions? If so, you will likely have to add GDAL/GeoPandas as a dependency anyways,
making this ibrary's conversion functions *probably* redundant.
* Is your workflow command line centric? If so you may want to consider Planet Lab's simular CLI tool [`gpq`](https://github.com/planetlabs/gpq),
which is written in Go and substantially faster.
* Otherwise, if you are using Python and want to avoid unnecessary bulky dependencies, this library will be a great choice!
**Note:** All user-exposed functions and schema classes are available at the top level (i.e., `geoparquet_pydantic.validate_geoparquet_table(...)`) of this library.
# Documentation is on GitHub [here](https://github.com/xaviernogueira/geoparquet-pydantic/blob/main/README.md)
# Getting Started
Install from [PyPi](https://pypi.org/project/geoparquet-pydantic):
```bash
pip install geoparquet-pydantic
```
Or from source:
```bash
$ git clone https://github.com/xaviernogueira/geoparquet-pydantic.git
$ cd geoparquet-pydantic
$ pip install .
```
Then import with an underscore:
```python
import geoparquet_pydantic
```
Or just import the functions/classes you need from the top-level:
```python
from geoparquet_pydantic import GeometryColumnMetadata
from geoparquet_pydantic import GeoParquetMetadata
from geoparquet_pydantic import validate_geoparquet_table
from geoparquet_pydantic import validate_geoparquet_file
from geoparquet_pydantic import geojson_to_geoparquet
from geoparquet_pydantic import geoparquet_to_geojson
```
# Roadmap
- [ ] Make CLI file<>file functions w/ `click`.
- [ ] Add parrallelized Parquet read for `geoparquet_pydantic.geoparquet_to_geojson()`.
# Contribute
We encourage contributions, feature requests, and bug reports!
Here is our recomended workflow:
* Use `dev-requirements.txt` to install our development dependencies.
* Make your edits using `pyright` as a linter.
* Use `pre-commit run --all-file` before commiting your work.
* If you add a new feature, we request that you add test coverage for it.
Happy coding!
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"description": "# GeoParquet-Pydantic\n\n**Motivation:** This project started at the 2024 San Fransisco GeoParquet Community hackathon, and arose out of a simple observation:\nwhy must Python users install the *massive* GDAL dependency (typically via GeoPandas) to do simple GeoJSON<>GeoParquet conversions.\n\n**Is this library the right choice for you?:**\n* Do you need to use a wide variety of Geospatial functions? If so, you will likely have to add GDAL/GeoPandas as a dependency anyways,\nmaking this ibrary's conversion functions *probably* redundant.\n* Is your workflow command line centric? If so you may want to consider Planet Lab's simular CLI tool [`gpq`](https://github.com/planetlabs/gpq),\nwhich is written in Go and substantially faster.\n* Otherwise, if you are using Python and want to avoid unnecessary bulky dependencies, this library will be a great choice!\n\n**Note:** All user-exposed functions and schema classes are available at the top level (i.e., `geoparquet_pydantic.validate_geoparquet_table(...)`) of this library.\n\n# Documentation is on GitHub [here](https://github.com/xaviernogueira/geoparquet-pydantic/blob/main/README.md)\n\n# Getting Started\n\nInstall from [PyPi](https://pypi.org/project/geoparquet-pydantic):\n```bash\npip install geoparquet-pydantic\n```\n\nOr from source:\n```bash\n$ git clone https://github.com/xaviernogueira/geoparquet-pydantic.git\n$ cd geoparquet-pydantic\n$ pip install .\n```\n\nThen import with an underscore:\n```python\nimport geoparquet_pydantic\n```\n\nOr just import the functions/classes you need from the top-level:\n```python\nfrom geoparquet_pydantic import GeometryColumnMetadata\nfrom geoparquet_pydantic import GeoParquetMetadata\nfrom geoparquet_pydantic import validate_geoparquet_table\nfrom geoparquet_pydantic import validate_geoparquet_file\nfrom geoparquet_pydantic import geojson_to_geoparquet\nfrom geoparquet_pydantic import geoparquet_to_geojson\n```\n\n# Roadmap\n\n- [ ] Make CLI file<>file functions w/ `click`.\n- [ ] Add parrallelized Parquet read for `geoparquet_pydantic.geoparquet_to_geojson()`.\n\n# Contribute\n\nWe encourage contributions, feature requests, and bug reports!\n\nHere is our recomended workflow:\n\n* Use `dev-requirements.txt` to install our development dependencies.\n* Make your edits using `pyright` as a linter.\n* Use `pre-commit run --all-file` before commiting your work.\n* If you add a new feature, we request that you add test coverage for it.\n\nHappy coding!\n",
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