semvec/pypi-packages huggingface dataset:
SQython 0.0.5
A SQL wrapper for python.

# SQython
 A wrapper for SQL and python.
 
 Checkout functions.MD for a list of the available use cases so far!

 # requirments
 - psycopg2
 - os (comes with python install)
 - numpy
 - io / StringIO (comes with python install)
 - pandas


# This was made to create an easier access to SQL through python

# instalation

### NOTE TO MAKE SURE THE SQ IS CAPITALIZED WHEN INSTALLING AND IMPORTING !!!!!!!!!!!!!!!
```
pip install SQython
```

# example use cases

```

import SQython as sq

# creating a connection to my DB and creating a new database

conn = sq.create_connection("postgres", "postgres", "3301", 'localhost', 5432)
sq.execute_query(conn,sq.create_database('maxtest'))

# after creating we need to connect to our new database

conn = sq.create_connection("maxtest", "postgres", "3301", 'localhost', 5432)


# creating a table based on column names and datatypes to each of their respective columns

sq.execute_query(conn,sq.make_table('testtable',['test1','test2','test3'],['serial','char(50)','char(50)'],'test1'))


# sample DataFrame that we will insert

data = {'test1':[1,2,3],
       'test2':['max','luke','aids'],
       'test3':['a','B','c']}
data = pd.DataFrame(data)

# pushing the data to DB
sq.execute_many(conn,data,'testtable')


# example of deleting new table

sq.execute_query(conn,sq.delete_table('testtable'))

# if we want to delete the current database we must connect to a different one before deletion

conn = sq.create_connection("postgres", "postgres", "3301", 'localhost', 5432)
sq.execute_query(conn,sq.delete_database('maxtest'))


# example of altering a column name
sq.execute_query(conn,sq.alter_column_name(testtable,'test2','names'))

# example of changing an existing columns datatype
# changing column 'names' to varchar
sq.execute_query(conn,sq.alter_datatype(testtable,'names','VARCHAR'))

# to write your own query!

query = 'select * from table'

sq.execute_query(conn,query)

# Currently working on a more efficient and easy querying method

```
# FREE SOFTWARE HELL YEAH
pytest-aws-config 0.1.0
Protect your AWS credentials in unit tests
Requires Python: >=3.6

# pytest_aws_config

Tiny [Pytest](https://pytest.org) plugin that mocks your AWS configuration in tests, making your tests independent of the configuration on the developer machine. In particular, it prevents your tests from accessing your AWS credentials.

## Why is this useful?

Developers often use AWS configuration files to store (temporary) credentials to IAM users/roles. This is very useful to access the AWS account from the command line. But it also means that tests will run with these credentials.

```
> export AWS_PROFILE=production
> aws logs describe-log-groups  # analyze some issue on production
> ... time passes ...
> ... write some code ...
> pytest tests  # execute tests
```
Whoops! These tests just ran with access to your production account. Hopefully everything was correctly mocked or patched.

## Installation

Just install this plugin with `pip install pytest_aws_config`. No configuration necessary.

## What about functional tests?

Of course, some of your tests may actually need AWS credentials. You have two options:

- Disable the plugin when running functional tests: `pytest -p no:pytest_aws_config`
- Keep the plugin and use some other mechanism (e.g. a pytest fixture) to set the configuration in the test. Then your tests remain independent of the configuration on the developer machine.

## Links

AWS documentation on [configuration files](https://docs.aws.amazon.com/cli/latest/userguide/cli-configure-files.html) and [environment variables](https://docs.aws.amazon.com/cli/latest/userguide/cli-configure-envvars.html).