%global _empty_manifest_terminate_build 0 Name: python-geobr Version: 0.2.0 Release: 1 Summary: geobr: Download Official Spatial Data Sets of Brazil License: MIT URL: https://github.com/ipeaGIT/geobr Source0: https://mirrors.nju.edu.cn/pypi/web/packages/bb/00/a020d07504d58c26e4b443ddec09b7514d38ee01b23f9c7622977d397aa2/geobr-0.2.0.tar.gz BuildArch: noarch Requires: python3-geopandas Requires: python3-shapely %description # geobr: Download Official Spatial Data Sets of Brazil logo logo

geobr is a computational package to download official spatial data sets of Brazil. The package includes a wide range of geospatial data in geopackage format (like shapefiles but better), available at various geographic scales and for various years with harmonized attributes, projection and topology (see detailed list of available data sets below).

## [READ FULL DOCS](https://github.com/ipeaGIT/geobr) ## Contribute To start the development environment run ```sh make . .venv/bin/activate ``` Test with `python -m pytest` You can use a helper to translate a function from R. If you want to add `read_biomes`, just run `python helpers/translate_from_R.py read_biomes` It will scrape the original R function to get documentation and metadata. It adds: - default year - function name - documentation one liner - larger documentation - very basic tests ! Be aware that if the function that you are adding is more complicated than the template. So, double always double check ! Before pushing, run `make prepare-push` #### For Windows We recommend using conda and creating an environment that includes all libraries simultaneously. First create an environment and install Shapely and GDAL as such: `conda create --name geobr_env python=3.7` Activate the environmnet `conda activate geobr_env` Then add Shapely from conda-forge channel `conda install shapely gdal -c conda-forge` Then the other packages `conda install fiona pandas geopandas requests -c conda-forge` **Alternatively**, type on a terminal `conda create --name --file conda_requirements.txt` Finally, if **not** using conda, try: `pip install -r pip_requirements.txt` ## Translation Status | Function | Translated? | Easy? | | ------------------------- | ----------- | ----- | | read_amazon | Yes | Super | | read_biomes | Yes | Super | | read_census_tract | Yes | No | | read_comparable_areas | No | Yes | | read_conservation_units | Yes | Super | | read_country | Yes | Super | | read_disaster_risk_area | Yes | Super | | read_health_facilities | Yes | Super | | read_health_region | Yes | Super | | read_immediate_region | Yes | Yes | | read_indigenous_land | Yes | Super | | read_intermediate_region | Yes | Yes | | read_meso_region | Yes | No | | read_metro_area | Yes | Super | | read_micro_region | Yes | No | | read_municipal_seat | Yes | Super | | read_municipality | Yes | No | | read_region | Yes | Super | | read_semiarid | Yes | Super | | read_state | Yes | Super | | read_statistical_grid | No | No | | read_urban_area | Yes | Super | | read_urban_concentrations | No | Super | | read_weighting_area | Yes | No | | list_geobr | Yes | Yes | | lookup_muni | Yes | No | | read_neighborhood | Yes | Yes | # Release new version ``` poetry version [patch|minor|major] poetry publish --build ``` %package -n python3-geobr Summary: geobr: Download Official Spatial Data Sets of Brazil Provides: python-geobr BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-geobr # geobr: Download Official Spatial Data Sets of Brazil logo logo

geobr is a computational package to download official spatial data sets of Brazil. The package includes a wide range of geospatial data in geopackage format (like shapefiles but better), available at various geographic scales and for various years with harmonized attributes, projection and topology (see detailed list of available data sets below).

## [READ FULL DOCS](https://github.com/ipeaGIT/geobr) ## Contribute To start the development environment run ```sh make . .venv/bin/activate ``` Test with `python -m pytest` You can use a helper to translate a function from R. If you want to add `read_biomes`, just run `python helpers/translate_from_R.py read_biomes` It will scrape the original R function to get documentation and metadata. It adds: - default year - function name - documentation one liner - larger documentation - very basic tests ! Be aware that if the function that you are adding is more complicated than the template. So, double always double check ! Before pushing, run `make prepare-push` #### For Windows We recommend using conda and creating an environment that includes all libraries simultaneously. First create an environment and install Shapely and GDAL as such: `conda create --name geobr_env python=3.7` Activate the environmnet `conda activate geobr_env` Then add Shapely from conda-forge channel `conda install shapely gdal -c conda-forge` Then the other packages `conda install fiona pandas geopandas requests -c conda-forge` **Alternatively**, type on a terminal `conda create --name --file conda_requirements.txt` Finally, if **not** using conda, try: `pip install -r pip_requirements.txt` ## Translation Status | Function | Translated? | Easy? | | ------------------------- | ----------- | ----- | | read_amazon | Yes | Super | | read_biomes | Yes | Super | | read_census_tract | Yes | No | | read_comparable_areas | No | Yes | | read_conservation_units | Yes | Super | | read_country | Yes | Super | | read_disaster_risk_area | Yes | Super | | read_health_facilities | Yes | Super | | read_health_region | Yes | Super | | read_immediate_region | Yes | Yes | | read_indigenous_land | Yes | Super | | read_intermediate_region | Yes | Yes | | read_meso_region | Yes | No | | read_metro_area | Yes | Super | | read_micro_region | Yes | No | | read_municipal_seat | Yes | Super | | read_municipality | Yes | No | | read_region | Yes | Super | | read_semiarid | Yes | Super | | read_state | Yes | Super | | read_statistical_grid | No | No | | read_urban_area | Yes | Super | | read_urban_concentrations | No | Super | | read_weighting_area | Yes | No | | list_geobr | Yes | Yes | | lookup_muni | Yes | No | | read_neighborhood | Yes | Yes | # Release new version ``` poetry version [patch|minor|major] poetry publish --build ``` %package help Summary: Development documents and examples for geobr Provides: python3-geobr-doc %description help # geobr: Download Official Spatial Data Sets of Brazil logo logo

geobr is a computational package to download official spatial data sets of Brazil. The package includes a wide range of geospatial data in geopackage format (like shapefiles but better), available at various geographic scales and for various years with harmonized attributes, projection and topology (see detailed list of available data sets below).

## [READ FULL DOCS](https://github.com/ipeaGIT/geobr) ## Contribute To start the development environment run ```sh make . .venv/bin/activate ``` Test with `python -m pytest` You can use a helper to translate a function from R. If you want to add `read_biomes`, just run `python helpers/translate_from_R.py read_biomes` It will scrape the original R function to get documentation and metadata. It adds: - default year - function name - documentation one liner - larger documentation - very basic tests ! Be aware that if the function that you are adding is more complicated than the template. So, double always double check ! Before pushing, run `make prepare-push` #### For Windows We recommend using conda and creating an environment that includes all libraries simultaneously. First create an environment and install Shapely and GDAL as such: `conda create --name geobr_env python=3.7` Activate the environmnet `conda activate geobr_env` Then add Shapely from conda-forge channel `conda install shapely gdal -c conda-forge` Then the other packages `conda install fiona pandas geopandas requests -c conda-forge` **Alternatively**, type on a terminal `conda create --name --file conda_requirements.txt` Finally, if **not** using conda, try: `pip install -r pip_requirements.txt` ## Translation Status | Function | Translated? | Easy? | | ------------------------- | ----------- | ----- | | read_amazon | Yes | Super | | read_biomes | Yes | Super | | read_census_tract | Yes | No | | read_comparable_areas | No | Yes | | read_conservation_units | Yes | Super | | read_country | Yes | Super | | read_disaster_risk_area | Yes | Super | | read_health_facilities | Yes | Super | | read_health_region | Yes | Super | | read_immediate_region | Yes | Yes | | read_indigenous_land | Yes | Super | | read_intermediate_region | Yes | Yes | | read_meso_region | Yes | No | | read_metro_area | Yes | Super | | read_micro_region | Yes | No | | read_municipal_seat | Yes | Super | | read_municipality | Yes | No | | read_region | Yes | Super | | read_semiarid | Yes | Super | | read_state | Yes | Super | | read_statistical_grid | No | No | | read_urban_area | Yes | Super | | read_urban_concentrations | No | Super | | read_weighting_area | Yes | No | | list_geobr | Yes | Yes | | lookup_muni | Yes | No | | read_neighborhood | Yes | Yes | # Release new version ``` poetry version [patch|minor|major] poetry publish --build ``` %prep %autosetup -n geobr-0.2.0 %build %py3_build %install %py3_install install -d -m755 %{buildroot}/%{_pkgdocdir} if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi pushd %{buildroot} if [ -d usr/lib ]; then find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/lib64 ]; then find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/bin ]; then find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/sbin ]; then find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst fi touch doclist.lst if [ -d usr/share/man ]; then find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst fi popd mv %{buildroot}/filelist.lst . mv %{buildroot}/doclist.lst . %files -n python3-geobr -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Tue May 30 2023 Python_Bot - 0.2.0-1 - Package Spec generated