Measurement Unit Converter

📜 Summary

This repository is dedicated to the corverter

🛠️ Fixes and improvements

The project is being developed, and the next necessary updates are:

• Add first features;
• Test the features;
• Docstring everything that had been created;
  • Track the features;
  • Docstring them;
• Add new buches product's references
• Add new currencies

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💻 Prerequisites

Before starting, make sure you have the following prerequisites:

• Install the Anaconda distribution from this link;
• Install all requirements listed in environment.yml in a virtual or conda environment as follows: conda env create -f environment.yml

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📫 Contributing to the project

To contribute, follow these steps:

1. Clone this repository and create a new branch;
2. Make your changes to the project;
3. Commit your updates to your new branch;
4. Upload your changes to github;
5. Open a Pull Request pointing to the base used branch.

obs1: If you want to contribute or test a specific commit, you can do the following:

git clone https://<user>:<pwd>@https://github.ibm.com/Agro-Insights-AA/exploratory_analysis.git@<commit-hash>

obs2: Commit messages must obey semantic git, as described in the example:

<type>[optional scope]: <description>

[optional body]

[optional footer]

Other semantic git examples can be found at the link: semantic git examples;

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📁 Folder structure

The project is structured as described below:

├───data -> Store the data to be analyzed
│ ├───External      -> Data from 3rd party sources
│ ├───interim       -> Interim data that has been transformed
│ ├───processed     -> The final canonical datasets for modeling
│ └───raw           -> The original and immutable data dump
├───notebooks       -> Experiments and analysis are here
└───src             -> Successful experiments modularized in .py files
    ├───data        -> Used to do the ETL
    ├───features    -> Responsible for the main functionality of the repo
    ├───test        -> Test Cases created to verify functionality
    ├───models      -> Related to training, testing and creating ML models
    ├───utils       -> Useful features for other modules
    └───preview     -> Used for dataviz

obs: All data stored in the /data/ folder is included in .gitignore;