automatic import of python-safety-road-mappingopeneuler20.03

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+/safety-road-mapping-0.1.7.tar.gz
diff --git a/python-safety-road-mapping.spec b/python-safety-road-mapping.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-safety-road-mapping
+Version:	0.1.7
+Release:	1
+Summary:	Module to generate a safety score for brazilian roads.
+License:	MIT
+URL:		https://github.com/cervejaria-ambev/safety_road_mapping
+Source0:	https://mirrors.aliyun.com/pypi/web/packages/4d/59/11cf4ea0c70519086a6d80b719dd6c8ac9137bdb03fa5b85a55fc2049df5/safety-road-mapping-0.1.7.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-folium
+Requires:	python3-openrouteservice
+Requires:	python3-pandas
+Requires:	python3-geopy
+Requires:	python3-dotenv
+Requires:	python3-patool
+Requires:	python3-plotly
+Requires:	python3-Unidecode
+Requires:	python3-colour
+Requires:	python3-typeguard
+Requires:	python3-typing-extensions
+
+%description
+# General Instructions
+
+## Generating API token
+
+This project uses [openrouteservice API](https://openrouteservice.org) to plot maps and routes.
+So the following steps are necessary at first:
+
+1. Sign up on [openrouteservice.org](https://openrouteservice.org/dev/#/signup) to generate an API token;
+2. Create a `.env` file with the following content: `TOKEN=XXXXXXXXXXXXXXX`, where `XXXXXXXXXXXXXXX` is the token generated in the step before;
+3. Install the lib: `pip install safety-road-mapping`
+4. Get the road accidents according the instructions bellow: [Getting accident road data](#getting-accident-road-data)
+5. See the documentation on: [safety documentation](docs/safety_road_mapping/safety.md)
+6. See the examples on how to use the lib on: [how-to-use.ipynb](./safety_road_mapping/examples/how-to-use.ipynb)
+
+## Getting accident road data
+
+- The accidents data used were extracted from the [Polícia Rodoviária Federal website](https://www.gov.br/prf/pt-br).
+- The notebook [get_data.ipynb](./safety_road_mapping/extract_data/get_data.ipynb) is responsible to download and extract the data used.
+- If you want to directly download the files you can [click here](https://www.gov.br/prf/pt-br/acesso-a-informacao/dados-abertos/dados-abertos-acidentes).
+- To consolidate all the accidents by year on an unique `.csv` file use the notebook [consolidate_data.ipynb](./safety_road_mapping/extract_data/consolidate_data.ipynb).
+- For a simple explore data analysis from the data look at [eda_accidents.ipynb](./safety_road_mapping/extract_data/eda_accidents.ipynb)
+
+### Adding São Paulo data
+
+- Access the [infosiga website](http://www.respeitoavida.sp.gov.br/relatorios/)
+- Download the xlsx file with fatal accidents: [Fatal accidents](http://painelderesultados.infosiga.sp.gov.br/bases/acidentes_fatais.xlsx)
+- Download the csv file with non fatal accidents: [Non-fatal accidents](http://painelderesultados.infosiga.sp.gov.br/bases/acidentes_naofatais.csv)
+- Use the notebook [treat_data_from_SP.ipynb](./safety_road_mapping/extract_data/treat_data_from_SP.ipynb) to transform and concatenate the data generating a final file that will be used as input for the safety map code.
+
+## Other possible steps on the project
+
+- The accidents data used comes just from road federal police source, so there are some routes that don't receive score because they are state highways.
+- Create some unit tests.
+- Use [Renaest](https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-denatran/docs/renaest) data (currently only [SP has geolocation data](http://www.infosiga.sp.gov.br)).
+- Include other variables in the score calculation.
+- Include driver behaviors data.
+- Implement an algorithm to predict accidents.
+- The routes subsections are not connected, once they are plotted individually in the map. Visually it can be interesting to connect them. (Is it possible or necessary?).
+
+
+%package -n python3-safety-road-mapping
+Summary:	Module to generate a safety score for brazilian roads.
+Provides:	python-safety-road-mapping
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-safety-road-mapping
+# General Instructions
+
+## Generating API token
+
+This project uses [openrouteservice API](https://openrouteservice.org) to plot maps and routes.
+So the following steps are necessary at first:
+
+1. Sign up on [openrouteservice.org](https://openrouteservice.org/dev/#/signup) to generate an API token;
+2. Create a `.env` file with the following content: `TOKEN=XXXXXXXXXXXXXXX`, where `XXXXXXXXXXXXXXX` is the token generated in the step before;
+3. Install the lib: `pip install safety-road-mapping`
+4. Get the road accidents according the instructions bellow: [Getting accident road data](#getting-accident-road-data)
+5. See the documentation on: [safety documentation](docs/safety_road_mapping/safety.md)
+6. See the examples on how to use the lib on: [how-to-use.ipynb](./safety_road_mapping/examples/how-to-use.ipynb)
+
+## Getting accident road data
+
+- The accidents data used were extracted from the [Polícia Rodoviária Federal website](https://www.gov.br/prf/pt-br).
+- The notebook [get_data.ipynb](./safety_road_mapping/extract_data/get_data.ipynb) is responsible to download and extract the data used.
+- If you want to directly download the files you can [click here](https://www.gov.br/prf/pt-br/acesso-a-informacao/dados-abertos/dados-abertos-acidentes).
+- To consolidate all the accidents by year on an unique `.csv` file use the notebook [consolidate_data.ipynb](./safety_road_mapping/extract_data/consolidate_data.ipynb).
+- For a simple explore data analysis from the data look at [eda_accidents.ipynb](./safety_road_mapping/extract_data/eda_accidents.ipynb)
+
+### Adding São Paulo data
+
+- Access the [infosiga website](http://www.respeitoavida.sp.gov.br/relatorios/)
+- Download the xlsx file with fatal accidents: [Fatal accidents](http://painelderesultados.infosiga.sp.gov.br/bases/acidentes_fatais.xlsx)
+- Download the csv file with non fatal accidents: [Non-fatal accidents](http://painelderesultados.infosiga.sp.gov.br/bases/acidentes_naofatais.csv)
+- Use the notebook [treat_data_from_SP.ipynb](./safety_road_mapping/extract_data/treat_data_from_SP.ipynb) to transform and concatenate the data generating a final file that will be used as input for the safety map code.
+
+## Other possible steps on the project
+
+- The accidents data used comes just from road federal police source, so there are some routes that don't receive score because they are state highways.
+- Create some unit tests.
+- Use [Renaest](https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-denatran/docs/renaest) data (currently only [SP has geolocation data](http://www.infosiga.sp.gov.br)).
+- Include other variables in the score calculation.
+- Include driver behaviors data.
+- Implement an algorithm to predict accidents.
+- The routes subsections are not connected, once they are plotted individually in the map. Visually it can be interesting to connect them. (Is it possible or necessary?).
+
+
+%package help
+Summary:	Development documents and examples for safety-road-mapping
+Provides:	python3-safety-road-mapping-doc
+%description help
+# General Instructions
+
+## Generating API token
+
+This project uses [openrouteservice API](https://openrouteservice.org) to plot maps and routes.
+So the following steps are necessary at first:
+
+1. Sign up on [openrouteservice.org](https://openrouteservice.org/dev/#/signup) to generate an API token;
+2. Create a `.env` file with the following content: `TOKEN=XXXXXXXXXXXXXXX`, where `XXXXXXXXXXXXXXX` is the token generated in the step before;
+3. Install the lib: `pip install safety-road-mapping`
+4. Get the road accidents according the instructions bellow: [Getting accident road data](#getting-accident-road-data)
+5. See the documentation on: [safety documentation](docs/safety_road_mapping/safety.md)
+6. See the examples on how to use the lib on: [how-to-use.ipynb](./safety_road_mapping/examples/how-to-use.ipynb)
+
+## Getting accident road data
+
+- The accidents data used were extracted from the [Polícia Rodoviária Federal website](https://www.gov.br/prf/pt-br).
+- The notebook [get_data.ipynb](./safety_road_mapping/extract_data/get_data.ipynb) is responsible to download and extract the data used.
+- If you want to directly download the files you can [click here](https://www.gov.br/prf/pt-br/acesso-a-informacao/dados-abertos/dados-abertos-acidentes).
+- To consolidate all the accidents by year on an unique `.csv` file use the notebook [consolidate_data.ipynb](./safety_road_mapping/extract_data/consolidate_data.ipynb).
+- For a simple explore data analysis from the data look at [eda_accidents.ipynb](./safety_road_mapping/extract_data/eda_accidents.ipynb)
+
+### Adding São Paulo data
+
+- Access the [infosiga website](http://www.respeitoavida.sp.gov.br/relatorios/)
+- Download the xlsx file with fatal accidents: [Fatal accidents](http://painelderesultados.infosiga.sp.gov.br/bases/acidentes_fatais.xlsx)
+- Download the csv file with non fatal accidents: [Non-fatal accidents](http://painelderesultados.infosiga.sp.gov.br/bases/acidentes_naofatais.csv)
+- Use the notebook [treat_data_from_SP.ipynb](./safety_road_mapping/extract_data/treat_data_from_SP.ipynb) to transform and concatenate the data generating a final file that will be used as input for the safety map code.
+
+## Other possible steps on the project
+
+- The accidents data used comes just from road federal police source, so there are some routes that don't receive score because they are state highways.
+- Create some unit tests.
+- Use [Renaest](https://www.gov.br/infraestrutura/pt-br/assuntos/transito/arquivos-denatran/docs/renaest) data (currently only [SP has geolocation data](http://www.infosiga.sp.gov.br)).
+- Include other variables in the score calculation.
+- Include driver behaviors data.
+- Implement an algorithm to predict accidents.
+- The routes subsections are not connected, once they are plotted individually in the map. Visually it can be interesting to connect them. (Is it possible or necessary?).
+
+
+%prep
+%autosetup -n safety-road-mapping-0.1.7
+
+%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-safety-road-mapping -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 0.1.7-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
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+++ b/sources
@@ -0,0 +1 @@
+4e7deb8d5c323f4dc44734e3d6dd608f  safety-road-mapping-0.1.7.tar.gz