Type Infer
- Release:
0.0.20
- Date:
Apr 22, 2024
Welcome to the type_infer
documentation. type_infer
is a Python package aimed at automatically inferring the data type for each column in a tabular dataset.
Quick Guide
Installation
You can install type_infer
as follows:
pip install type_infer
We recommend doing the above inside a newly-created python virtual environment.
Setting up a dev environment
Clone the repository
Run
cd type_infer && pip install --editable .
Add it to your python path (e.g. by adding
export PYTHONPATH='/where/you/cloned/repo':$PYTHONPATH
as a newline at the end of your~/.bashrc
file)Check that the unit-tests are passing by going into the directory where you cloned and running:
python -m unittest discover tests
Warning
If python
default to python2.x on your environment use python3
and pip3
instead
Quick start
type_infer
works with pandas.DataFrames
.
import type_infer
Contributions
We love to receive contributions from the community and hear your opinions! We want to make contributing as easy as it can be.
Please continue reading this guide if you are interested.
How can you help us?
Report a bug
Improve documentation
Solve an issue
Propose new features
Discuss feature implementations
Submit a bug fix
Test with your own data and let us know how it went!
Code contributions
In general, we follow the fork-and-pull git workflow. Here are the steps:
Fork the repository
Checkout the
staging
branch, which is the development version that gets released intostable
(there can be exceptions, but make sure to ask and confirm with us).Make changes and commit them
Make sure that the CI tests pass. You can run the test suite locally with
flake8 .
to check style andpython -m unittest discover tests
to run the automated tests. This doesn’t guarantee it will pass remotely since we run on multiple envs, but should work in most cases.Push your local branch to your fork
Submit a pull request from your repo to the
staging
branch ofmindsdb/type_infer
so that we can review your changes. Be sure to merge the latest from staging before making a pull request!
Note
You will need to sign a CLI agreement for the code since the repository is under a GPL license.
Feature and Bug reports
We use GitHub issues to track bugs and features. Report them by opening a new issue and fill out all of the required inputs.
Code review process
Pull request (PR) reviews are done on a regular basis. If your PR does not address a previous issue, please make an issue first.
If your change can affect performance, we will run our private benchmark suite to validate it.
Please, make sure you respond to our feedback/questions.
Community
If you have additional questions or you want to chat with MindsDB core team, you can join our community:
To get updates on MindsDB’s latest announcements, releases, and events, sign up for our Monthly Community Newsletter.
Join our mission of democratizing machine learning and allowing developers to become data scientists!
Contributor Code of Conduct
Please note that this project is released with a Contributor Code of Conduct. By participating in this project, you agree to abide by its terms.