c4v-py 0.1.0.dev20211026

Code for Venezuela python library.

c4v-py

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.

• Installation
• Development
• Pending

Installation

Use pip to install the package:

pip install c4v-py

Usage

TODO

Can you help us? Open a new issue in minutes!

Contributing

The following tools are used in this project:

• Poetry is used as package manager.
• Nox is used as automation tool, mainly for testing.
• Black is the mandatory formatter tool.
• PyEnv 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. 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!

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 for details.
• Understand what is in the following folders and decide what to do with them.
  • brat-v1.3_Crunchy_Frog
  • creating_models
  • 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