Metadata-Version: 2.1
Name: pandas-aws
Version: 0.1.2
Summary: 
Home-page: https://github.com/FlorentPajot/pandas-aws
License: MIT
Keywords: pandas,aws,python,dataengineering
Author: FlorentPajot
Author-email: pro.florent.pajot@gmail.com
Requires-Python: >=3.7,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Dist: boto3 (>=1.12.26,<2.0.0)
Requires-Dist: fastparquet (>=0.3.3,<0.4.0)
Requires-Dist: pandas (>=1.0.3,<2.0.0)
Requires-Dist: pyarrow (>=0.16.0,<0.17.0)
Requires-Dist: xlrd (>=1.2.0,<2.0.0)
Requires-Dist: xlsxwriter (>=1.2.8,<2.0.0)
Project-URL: Repository, https://github.com/FlorentPajot/pandas-aws
Description-Content-Type: text/markdown

[![Build Status](https://travis-ci.com/FlorentPajot/pandas-aws.svg?branch=master)](https://travis-ci.com/FlorentPajot/pandas-aws) [![codecov](https://codecov.io/gh/FlorentPajot/pandas-aws/branch/master/graph/badge.svg)](https://codecov.io/gh/FlorentPajot/pandas-aws)

# Pandas AWS - AWS use made easy for data scientists

Pandas AWS makes it super easy to use a pandas.DataFrame along with AWS services.

```
# Example : get a DataFrame from multiple CSV files in S3

from pandas_aws import get_client, get_df_from_keys

MY_BUCKET= 'pandas-aws-bucket'

s3 = get_client('s3')

df = get_df_from_keys(s3, MY_BUCKET, prefix='my-folder', suffix='.csv')
```

# Installing pandas-aws

## Pip installation

You can use pip to download the package

`pip install pandas-aws`

# Contributing to pandas-aws

## Git clone

We use the `develop` brand as the release branch, thus `git clone` the repository and `git checkout develop` in order to get the latest version in development.

```
git clone git@github.com:FlorentPajot/pandas-aws.git
```

## Preparing your environment

Pandas AWS uses `poetry` to manage dependencies. Thus, `poetry` is required:

`curl -SSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python`

Create a separate Python environment, for example using `pyenv`:

```
pyenv virtualenv pandas-aws
pyenv activate pandas-aws
```
Then install dependencies with poetry after your `git clone` from the project repository:

`poetry install`

## Guidelines

Todo

