semvec/pypi-packages huggingface dataset:
amazonian 2022.5.27
Python library for working with Amazon Web Services such as Redshift and S3
License: MIT
Requires Python: ~=3.6

# Amazonian

*Amazonian* is a *Python* library for interacting easily with Amazon S3 and Redshift.

# Installation
`pip install amazonian`

# Usage

## `S3`

```python
from amazonian import S3

s3 = S3(key=None, secret=None, iam_role=None, root='s3://', spark=spark)

# get list of files:
s3.ls(path='s3://bucket/directory/subdirectory')

# get a tree representation of folder structure
s3.tree(path='s3://bucket/directory/subdirectory')

# get file size:
s3.get_size(path='some_file')

# save a Spark DataFrame as a Parquet
s3.save_parquet(data=my_data, path='s3://bucket/directory/subdirectory/name.parquet')

# load a Parquet into a Spark DataFrame
my_data = s3.load_parquet(path='s3://bucket/directory/subdirectory/name.parquet')
```
django-model-auditmatic 0.2.0
Audit support for Django models using PostgreSQL triggers and stored procedures.
License: MIT

Work in progress
================
- this probably doesn't work well yet.


Usage
-----
- Add django_auditmatic to INSTALLED_APPS.

Example::

    INSTALLED_APPS.append("django_auditmatic")


- Configure which models you want to audit in settings.py

Example::

    AUDITMATIC = {
        "apps": {
            "auth": {
                "User": {"m2m": any},
            }
        }
    }


In this example will only include the User model from the auth app, along with any many-to-many relationships.

- Then run::

    python manage.py install_audit