path: root/python-c4v-py.spec

%global _empty_manifest_terminate_build 0
Name:		python-c4v-py
Version:	0.1.0.dev202201291921
Release:	1
Summary:	Code for Venezuela python library.
License:	Apache-2.0
URL:		https://www.codeforvenezuela.org/
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/6a/d8/ffc6e5a5f276c7ee1e615bff2f5bf97169f720e84bfea5e209e00868bd5e/c4v-py-0.1.0.dev202201291921.tar.gz
BuildArch:	noarch

Requires:	python3-pip
Requires:	python3-tensorflow
Requires:	python3-tensorflow_hub[make_image_classifier]
Requires:	python3-tensorflow-probability
Requires:	python3-scikit-learn
Requires:	python3-scikit-multilearn
Requires:	python3-pandas
Requires:	python3-nltk
Requires:	python3-google-cloud-bigquery
Requires:	python3-google-cloud-logging
Requires:	python3-Scrapy
Requires:	python3-beautifulsoup4
Requires:	python3-tabulate
Requires:	python3-click
Requires:	python3-scipy
Requires:	python3-nbconvert
Requires:	python3-traitlets
Requires:	python3-ipykernel
Requires:	python3-ipython
Requires:	python3-zipp
Requires:	python3-importlib-metadata
Requires:	python3-importlib-resources
Requires:	python3-dataclasses
Requires:	python3-transformers
Requires:	python3-datasets
Requires:	python3-torch
Requires:	python3-dynaconf
Requires:	python3-transformers-interpret
Requires:	python3-streamlit
Requires:	python3-Flask
Requires:	python3-pytz
Requires:	python3-google-cloud-storage
Requires:	python3-google-cloud-functions
Requires:	python3-firebase-admin
Requires:	python3-scrapydo

%description
# c4v-py

<p align="center">
  <img width="125" src="assets/logo.png">
</p>

> Solving Venezuela pressing matters one commmit at a time

`c4v-py` is a library used to address Venezuela's pressing issues
using computer and data science. Check the [online documentation](https://code-for-venezuela.github.io/c4v-py/)

- [Installation](#installation)
- [Development](#development)
- [Pending](#pending)

## Installation

Use pip to install the package:

```python3
pip install c4v-py
```

## Usage

_TODO_

[Can you help us? Open a new issue in
minutes!](https://github.com/code-for-venezuela/c4v-py/issues/new/choose)

## Contributing

The following tools are used in this project:

- [Poetry](https://python-poetry.org/) is used as package manager.
- [Nox](https://nox.thea.codes/) is used as automation tool, mainly for testing.
- [Black](https://black.readthedocs.io/) is the mandatory formatter tool.
- [PyEnv](https://github.com/pyenv/pyenv/wiki) is recommended as a tool to handle multiple python versions in your machine.

The library is intended to be compatible with python ~3.6.9, ~3.7.4 and ~3.8.2. But the primary version to support is ~3.8.2.

The general structure of the project is trying to follow the recommendations
in [Cookiecutter Data Science](https://drivendata.github.io/cookiecutter-data-science/).
The main difference lies in the source code itself which is not constraint to data science code.

### Setup

1. Install pyenv and select a version, ie: 3.8.2. Once installed run `pyenv install 3.8.2`
2. Install poetry in your system
3. Clone this repo in a desired location `git clone https://github.com/code-for-venezuela/c4v-py.git`
4. Navigate to the folder `cd c4v-py`
5. Make sure your poetry picks up the right version of python by running `pyenv local 3.8.2`, if 3.8.2 is your right version.
6. Since our toml file is already created, we need to get all dependencies by running `poetry install`. This step might take a few minutes to complete.
7. Install nox
8. From `c4v-py` directory, on your terminal, run the command `nox -s tests` to make sure all the tests run.

If you were able to follow every step with no error, you are ready to start contributing. Otherwise, [open a new issue](https://github.com/code-for-venezuela/c4v-py/issues/new/choose)!

## Roadmap

- [ ] Add CONTRIBUTING guidelines
- [ ] Add issue templates
- [ ] Document where to find things (datasets, more info, etc.)
  - This might be done (in conjunction) with Github Projects. Managing tasks there might be a good idea.
- [ ] Add LICENSE
- [ ] Change the authors field in pyproject.toml
- [ ] Change the repository field in pyproject.toml
- [ ] Move the content below to a place near to the data in the data folder or use the reference folder.
      Check [Cookiecutter Data Science](https://drivendata.github.io/cookiecutter-data-science/) for details.
- [ ] Understand what is in the following folders and decide what to do with them.
  - [ ] brat-v1.3_Crunchy_Frog
  - [ ] creating_models
  - [x] data/data_to_annotate
  - [ ] data_analysis
- [ ] Set symbolic links between `brat-v1.3_Crunchy_Frog/data` and `data/data_to_annotate`. `data_sampler` extracts to `data/data_to_annotate`. Files placed here are read by Brat.
  - [ ] Download Brat - `wget https://brat.nlplab.org/index.html`
  - [ ] untar brat - `tar -xzvf brat-v1.3_Crunchy_Frog.tar.gz`
  - [ ] install brat - `cd brat-v1.3_Crunchy_Frog && ./install.sh`
  - [ ] replace default annotation conf for current configuration - `wget https://raw.githubusercontent.com/dieko95/c4v-py/master/brat-v1.3_Crunchy_Frog/annotation.conf -O annotation.conf`
  - [ ] replace default config.py for current configuration - `wget https://raw.githubusercontent.com/dieko95/c4v-py/master/brat-v1.3_Crunchy_Frog/config.py -O config.py`


%package -n python3-c4v-py
Summary:	Code for Venezuela python library.
Provides:	python-c4v-py
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-c4v-py
# c4v-py

<p align="center">
  <img width="125" src="assets/logo.png">
</p>

> Solving Venezuela pressing matters one commmit at a time

`c4v-py` is a library used to address Venezuela's pressing issues
using computer and data science. Check the [online documentation](https://code-for-venezuela.github.io/c4v-py/)

- [Installation](#installation)
- [Development](#development)
- [Pending](#pending)

## Installation

Use pip to install the package:

```python3
pip install c4v-py
```

## Usage

_TODO_

[Can you help us? Open a new issue in
minutes!](https://github.com/code-for-venezuela/c4v-py/issues/new/choose)

## Contributing

The following tools are used in this project:

- [Poetry](https://python-poetry.org/) is used as package manager.
- [Nox](https://nox.thea.codes/) is used as automation tool, mainly for testing.
- [Black](https://black.readthedocs.io/) is the mandatory formatter tool.
- [PyEnv](https://github.com/pyenv/pyenv/wiki) is recommended as a tool to handle multiple python versions in your machine.

The library is intended to be compatible with python ~3.6.9, ~3.7.4 and ~3.8.2. But the primary version to support is ~3.8.2.

The general structure of the project is trying to follow the recommendations
in [Cookiecutter Data Science](https://drivendata.github.io/cookiecutter-data-science/).
The main difference lies in the source code itself which is not constraint to data science code.

### Setup

1. Install pyenv and select a version, ie: 3.8.2. Once installed run `pyenv install 3.8.2`
2. Install poetry in your system
3. Clone this repo in a desired location `git clone https://github.com/code-for-venezuela/c4v-py.git`
4. Navigate to the folder `cd c4v-py`
5. Make sure your poetry picks up the right version of python by running `pyenv local 3.8.2`, if 3.8.2 is your right version.
6. Since our toml file is already created, we need to get all dependencies by running `poetry install`. This step might take a few minutes to complete.
7. Install nox
8. From `c4v-py` directory, on your terminal, run the command `nox -s tests` to make sure all the tests run.

If you were able to follow every step with no error, you are ready to start contributing. Otherwise, [open a new issue](https://github.com/code-for-venezuela/c4v-py/issues/new/choose)!

## Roadmap

- [ ] Add CONTRIBUTING guidelines
- [ ] Add issue templates
- [ ] Document where to find things (datasets, more info, etc.)
  - This might be done (in conjunction) with Github Projects. Managing tasks there might be a good idea.
- [ ] Add LICENSE
- [ ] Change the authors field in pyproject.toml
- [ ] Change the repository field in pyproject.toml
- [ ] Move the content below to a place near to the data in the data folder or use the reference folder.
      Check [Cookiecutter Data Science](https://drivendata.github.io/cookiecutter-data-science/) for details.
- [ ] Understand what is in the following folders and decide what to do with them.
  - [ ] brat-v1.3_Crunchy_Frog
  - [ ] creating_models
  - [x] data/data_to_annotate
  - [ ] data_analysis
- [ ] Set symbolic links between `brat-v1.3_Crunchy_Frog/data` and `data/data_to_annotate`. `data_sampler` extracts to `data/data_to_annotate`. Files placed here are read by Brat.
  - [ ] Download Brat - `wget https://brat.nlplab.org/index.html`
  - [ ] untar brat - `tar -xzvf brat-v1.3_Crunchy_Frog.tar.gz`
  - [ ] install brat - `cd brat-v1.3_Crunchy_Frog && ./install.sh`
  - [ ] replace default annotation conf for current configuration - `wget https://raw.githubusercontent.com/dieko95/c4v-py/master/brat-v1.3_Crunchy_Frog/annotation.conf -O annotation.conf`
  - [ ] replace default config.py for current configuration - `wget https://raw.githubusercontent.com/dieko95/c4v-py/master/brat-v1.3_Crunchy_Frog/config.py -O config.py`


%package help
Summary:	Development documents and examples for c4v-py
Provides:	python3-c4v-py-doc
%description help
# c4v-py

<p align="center">
  <img width="125" src="assets/logo.png">
</p>

> Solving Venezuela pressing matters one commmit at a time

`c4v-py` is a library used to address Venezuela's pressing issues
using computer and data science. Check the [online documentation](https://code-for-venezuela.github.io/c4v-py/)

- [Installation](#installation)
- [Development](#development)
- [Pending](#pending)

## Installation

Use pip to install the package:

```python3
pip install c4v-py
```

## Usage

_TODO_

[Can you help us? Open a new issue in
minutes!](https://github.com/code-for-venezuela/c4v-py/issues/new/choose)

## Contributing

The following tools are used in this project:

- [Poetry](https://python-poetry.org/) is used as package manager.
- [Nox](https://nox.thea.codes/) is used as automation tool, mainly for testing.
- [Black](https://black.readthedocs.io/) is the mandatory formatter tool.
- [PyEnv](https://github.com/pyenv/pyenv/wiki) is recommended as a tool to handle multiple python versions in your machine.

The library is intended to be compatible with python ~3.6.9, ~3.7.4 and ~3.8.2. But the primary version to support is ~3.8.2.

The general structure of the project is trying to follow the recommendations
in [Cookiecutter Data Science](https://drivendata.github.io/cookiecutter-data-science/).
The main difference lies in the source code itself which is not constraint to data science code.

### Setup

1. Install pyenv and select a version, ie: 3.8.2. Once installed run `pyenv install 3.8.2`
2. Install poetry in your system
3. Clone this repo in a desired location `git clone https://github.com/code-for-venezuela/c4v-py.git`
4. Navigate to the folder `cd c4v-py`
5. Make sure your poetry picks up the right version of python by running `pyenv local 3.8.2`, if 3.8.2 is your right version.
6. Since our toml file is already created, we need to get all dependencies by running `poetry install`. This step might take a few minutes to complete.
7. Install nox
8. From `c4v-py` directory, on your terminal, run the command `nox -s tests` to make sure all the tests run.

If you were able to follow every step with no error, you are ready to start contributing. Otherwise, [open a new issue](https://github.com/code-for-venezuela/c4v-py/issues/new/choose)!

## Roadmap

- [ ] Add CONTRIBUTING guidelines
- [ ] Add issue templates
- [ ] Document where to find things (datasets, more info, etc.)
  - This might be done (in conjunction) with Github Projects. Managing tasks there might be a good idea.
- [ ] Add LICENSE
- [ ] Change the authors field in pyproject.toml
- [ ] Change the repository field in pyproject.toml
- [ ] Move the content below to a place near to the data in the data folder or use the reference folder.
      Check [Cookiecutter Data Science](https://drivendata.github.io/cookiecutter-data-science/) for details.
- [ ] Understand what is in the following folders and decide what to do with them.
  - [ ] brat-v1.3_Crunchy_Frog
  - [ ] creating_models
  - [x] data/data_to_annotate
  - [ ] data_analysis
- [ ] Set symbolic links between `brat-v1.3_Crunchy_Frog/data` and `data/data_to_annotate`. `data_sampler` extracts to `data/data_to_annotate`. Files placed here are read by Brat.
  - [ ] Download Brat - `wget https://brat.nlplab.org/index.html`
  - [ ] untar brat - `tar -xzvf brat-v1.3_Crunchy_Frog.tar.gz`
  - [ ] install brat - `cd brat-v1.3_Crunchy_Frog && ./install.sh`
  - [ ] replace default annotation conf for current configuration - `wget https://raw.githubusercontent.com/dieko95/c4v-py/master/brat-v1.3_Crunchy_Frog/annotation.conf -O annotation.conf`
  - [ ] replace default config.py for current configuration - `wget https://raw.githubusercontent.com/dieko95/c4v-py/master/brat-v1.3_Crunchy_Frog/config.py -O config.py`


%prep
%autosetup -n c4v-py-0.1.0.dev202201291921

%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-c4v-py -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.1.0.dev202201291921-1
- Package Spec generated