semvec/pypi-packages huggingface dataset:
the-trial 2.0.0
A Python microframework for easy communication with Kafka.
Requires Python: >=3.8
Keywords: consumer, kafka, microframework, producer, python

========
theTrial
========

.. DYNAMIC

.. image:: https://img.shields.io/pypi/v/TODO
   :target: https://pypi.org/project/TODO
   :alt: pypi

.. image:: https://github.com/donMichaelL/test_package/actions/workflows/main.yaml/badge.svg?branch=main
    :target: https://github.com/donMichaelL/test_package/actions/workflows/main.yaml
    :alt: Main Workflow Status

.. image:: https://img.shields.io/github/actions/workflow/status/donMichaelL/test_package/main.yaml.svg?branch=main&style=for-the-badge
    :target: https://github.com/donMichaelL/test_package/actions/workflows/main.yaml
    :alt: Main Workflow Status

.. STATIC

.. image:: https://img.shields.io/badge/pre--commit-enabled-%2300A36C%09
   :target: https://github.com/pre-commit/pre-commit
   :alt: pre-commit

.. image:: https://img.shields.io/badge/Code_Style-black-black?color=black
   :target: https://github.com/psf/black
   :alt: black

.. image:: https://img.shields.io/badge/License-MIT-blue
   :target: https://github.com/donMichaelL/theTrial/blob/master/LICENSE
   :alt: license

``theTrial`` is a microframework designed to provide a simple interface for interacting with Kafka.
It simplifies the process of setting up consumers and producers for Kafka topics using Pythonic decorators.
Under the hood, it uses `confluent-kafka <https://github.com/confluentinc/confluent-kafka-python>`_ to communicate synchronously with Kafka clusters.

Installation
------------

Install from pip:

.. code-block:: bash

   python -m pip install theTrial

Quick Start
-----------

Here's a simple example to get you started:

.. code-block:: python

   from theTrial import TheTrial

   app = TheTrial()


Settings Configuration
----------------------

For a detailed explanation and additional configuration options, refer to the official Confluent documentation: `Confluent Kafka Python Documentation <https://docs.confluent.io/platform/current/clients/confluent-kafka-python/html/index.html>`_.

User-Defined Settings
^^^^^^^^^^^^^^^^^^^^^


Logging Configuration
---------------------

``theTrial`` employs and extends Python's built-in logging module for system logging.

CLI Commands
------------

`theTrial` includes a set of CLI commands to set up and manage your projects.

Start Command
^^^^^^^^^^^^^

To initialize a new project structure, use the `start` command:

.. code-block:: bash

   theTrial start --name [YOUR_APP_NAME]

By default, the main app file will be named `app.py`. You can specify a different name using the ``--name`` option.

This command will:

- Create the main app file (`[YOUR_APP_NAME].py`).
joft 0.1.1
CLI tool for automation of user actions on a JIRA instance
Requires Python: >=3.11

# Jira Off-load Tool - JOFT

## What is this?

JOFT is a CLI tool for automation of user actions on a [JIRA](https://www.atlassian.com/software/jira) instance. This was created because the build-in automation in JIRA is not sufficient when you want to do complex actions without having the admin rights on the instance.

## How does it work?

To do automation with JOFT you first need to write a yaml template file which will actually hold your actions that you want execute. You can execute actions per issue from a JQL trigger query or without it.

If you provide a specific trigger JQL query in the yaml file, all the described actions defined in a yaml template file will execute once per issue found by the trigger JQL query. A yaml template file can have only JQL trigger query. If you need more create another yaml template file with a different query.

If you don't provide the trigger JQL query, the defined actions will execute once.

## Installation

Clone the repo. Create a virtualenv with the tool of your liking just make sure the Python version is 3.11 and higher.

To install the tool go to the root dir of the project, activate your venv, and run `pip install .`. For development, run `pip install -e .` instead.

To run all tests and type-checker run `tox`.

## Usage

First you need to have a jira instance and an account on that instance. Then you need get personal access token your [PAT token](https://confluence.atlassian.com/enterprise/using-personal-access-tokens-1026032365.html). To be able to work with JOFT create a config for your JIRA instance in the root of the project folder. There is an default config example you can use in the project folder `joft.config.toml.default`. Just remove the `.default` from the end of the file and add your credentials and you are good to go.

To get help run the tool in CLI withou any options: 

`joft`.

To validate your yaml template file run: 

`joft validate --template ./<path to your yaml template>`

To run the actions from your yaml template file run: 

`joft run --template ./<path to your yaml template>`

If you need more verbose output for debugging, define `JOFT_DEBUG=1` environment variable.

## Docs

Documentation can be found [here](docs/introduction.md).
mfa-authenticator 1.0.4.11
This helps you setup MFA with 3rd Party Authenticator (Google Authenticator, Microsoft Authenticator, etc)
Requires Python: >=3.10

# MFA SETUP AND VERIFICATION PACKAGE



## This is a python package for MFA setup and verification using 3rd Party 
## Authenticating Applications (like Google Authenticator, Microsoft Authenticator,Sale Force, etc)


### Setup MFA: Onboard on a 3rd Party Authenticator Application:
    1. Generate the MFA URL AND SECRET KEY
    2. Generate the QR Code version of the MFA URL
    3. Integrate with the 3rd party Authenticator :
            a. Scan the QR code generated
            b. Enter the Secret Key



### MFA Verification: 
    -   Insert the code and verify it


#### Sample Code:
    from mfa import MFA


    1. Generate the MFA URL AND SECRET KEY
        m = MFA(service_name, user_details)
            => service_name is the name of the service (eg: company name) : STRING
            => user_detail is the user details (eg: email address, phone number, etc):  STRING
        
        Example: 
            service_name = 'Sunny Inc'
            user_details = 'sunday@test.com'
            m = MFA(service_name, user_details) 
            mfa_url,secret_key = m.generate_mfa_code()
            print(mfa_url)
            print(secret_key)

    2. Generate the QR Code version of the MFA URL
        m.generate_qr_code(mfa_url)   
       
        ##### NOTE: This is optional because the mfa_url should be converted to a qr code on the 
                    client side ( Fromtend application : Web or Mobile App)
      


    3. Verify the Generated Code
        generated_code = '123456' # generated by the user via the 
                                    # 3rd party authenticator app (Google Authenticator, Microsoft Authenticator, etc)
        
        status = m.verify_code(generated_code)
        print(status)




### NOTE: 

    1 -> Developer will be expected to save the secret Key for each user 
        (it should be unique for each user)
            
    2 -> End User should be asked to save the secret key or I will suggest 
        you save it in a db with a key value pair or a field where the key 
        is the recovery code (unique) and value is the secret key. So you share 
        the recovery code with the user

    3 -> When they can't recover the qr or lost the mobile device, 
        you can ask them for the recovery code then use it to get the secret key 
        from the db and then use it to setup on the 3rd party authenticator app.