semvec/pypi-packages huggingface dataset:
pytechfin 1.0.1
Techfin Python API and Tools
License: MIT
Keywords: TOTVS Techfin,Carol.ai,TOTVS

.. note::
   For the latest source, discussion, etc, please visit the
   `GitHub repository <https://github.com/jnefoussi/pytechfin>`_


.. image:: https://raw.githubusercontent.com/jnefoussi/pytechfin/main/logos/pytechfin_logo.png

============
pytechfin
============

Initializing 
------------

.. code:: python

    from pytechfin import Techfin, TOTVSRacAuth

    cred = {
        "client_id": "123",
        "client_secret": "123",  }

    auth = TOTVSRacAuth(**cred)
    tf = Techfin(auth)


Good practice using token
-------------------------

Never write in plain text your credentials. One can use 
the environment variables

 1. ``TECHFINCLIENTID`` for the client ID
 2. ``TECHFINCLIENTSECRET`` for the client secret
 3. ``CAROLUSER`` Carol User with tenant access
 4. ``CAROLPWD`` Carol User Password
 
 e.g., one can create a ``.env`` file like this:

.. code:: python

    TECHFINCLIENTID=123
    TECHFINCLIENTSECRET=1234
    CAROLUSER=mycaroluser@mail.com
    CAROLUSER=My@Pwd

and then

.. code:: python

    from pytechfin import Techfin
    from dotenv import load_dotenv
    load_dotenv(".env") #this will import these env variables to your execution.
    tf = Techfin()
probabilistic-models 0.1.0
An interface to facilitate rapid development and deployment of probabilistic models
License: MIT
Requires Python: >=3.6

# [Probabilistic Models](http://github.com/wesselb/probabilistic-models)

[![CI](https://github.com/wesselb/probabilistic-models/workflows/CI/badge.svg)](https://github.com/wesselb/probabilistic-models/actions?query=workflow%3ACI)
[![Coverage Status](https://coveralls.io/repos/github/wesselb/probabilistic-models/badge.svg?branch=main)](https://coveralls.io/github/wesselb/probabilistic-models?branch=main)
[![Latest Docs](https://img.shields.io/badge/docs-latest-blue.svg)](https://wesselb.github.io/probabilistic-models)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

An interface to facilitate rapid development and deployment of probabilistic models

## Installation

See [the instructions here](https://gist.github.com/wesselb/4b44bf87f3789425f96e26c4308d0adc).
Then simply

```
pip install probabilistic-models
```

## Basic Usage

Like so:

```python
>>> print('Hello, world!')
Hello, world!
```