semvec/pypi-packages huggingface dataset:
django-commflex 1.0.1
Provides flexibility of sending messages across multiple channels
License: MIT

Django Commflex Library
------------------------

A flexible and reliable Django library for sending SMS messages through multiple providers with built-in retry capabilities.

Key Features
------------

- Multiple SMS provider support (AWS SNS and AIT)
- Automatic phone number validation
- Configurable retry mechanism with exponential backoff

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

1. Install the package:

   .. code-block:: bash

       pip install django-commflex


2. Add "django-double-commflex" to your ``INSTALLED_APPS`` setting:

   .. code-block:: python

      INSTALLED_APPS = [
          ...
          'commflex',
      ]

3. Add SMS settings to your Django settings:

   .. code-block:: python

       SMS_SETTINGS = {
           'aws': {
               'access_key': 'your-access-key',
               'secret_access_key': 'your-secret-key',
               'region': 'aws-region',
               'enabled': True,
               'timeout': 30,
           },
           'ait': {
            'username': 'your-username',
            'api_key': 'your-api-key',
            'sms_url': 'https://api.ait-provider.com/sms',
            'sender_id': 'YOUR_SENDER_ID',
            'enabled': False,
            'timeout': 30,  # Optional, defaults to 30 seconds
            }
       }

3. Send an SMS:

   .. code-block:: python

      from commflex.sms import send_sms
      send_sms(phone_number, message)

Supported Providers
-------------------

AWS SNS
~~~~~~~
Amazon Simple Notification Service integration with support for all regions.

AIT SMS
~~~~~~~
Africa's Talking SMS service integration with custom sender ID support.


Testing
-------

Run the test suite:

.. code-block:: bash

    python -m pytest

For development, install test dependencies:

.. code-block:: bash

    pip install -e ".[test]"


Documentation
-------------

https://django-commflex.readthedocs.io/en/latest/index.html
krakenohlcvt 0.1.17
Extract symbol data as pandas data frames from the Kraken_OHLCVT.zip file of the Kraken exchange
License: MIT
Requires Python: <4.0,>=3.6

# krakenohlcvt

A python package to handle Kraken exchange historial OHLCVT data without needing to unzip the Kraken_OHLCVT.zip file.

# Installation

```bash
pip install krakenohlcvt
```

or

```bash
potry add krakenohlcvt
```

# Usage

```python

from krakenohlcvt import KrakenDataHandler


# Enter path to the Kraken zip file:

import os

DATA_PATH = os.path.expanduser("~/Downloads/Kraken_OHLCVT.zip")

# or simpler:

DATA_PATH = "path/to/Kraken_OHLCVT.zip"


# load it

kd = KrakenDataHandler(DATA_PATH)


# you can inspect which symbols it contains:
kd.list_symbols()

# when searching for a specific symbol, search with either "starts_with=" or "contains="
kd.list_symbols(starts_with="ETH")

# then get the timeframe from the specific symbol
df = kd.load_symbol_data("ETHUSDT", "15m")
# if timeframe not in ["1m", "15m", "1h", "1d"], then the '1m' data gets loaded and the timeframe
# inferred from the 1m data!


# save a timeframe of a specific symbol as df pickle:
kd.save_to_df_pickle(symbol="ETHUSDT", timeframe="15m", outpath=os.path.expanduser("~/projects/python/LotusBot/src/backtester/ETHUSDT_15m.csv"), dropna_rows=True)

# convert unix time in the index to human-readable datetime object
[kd.unix_to_datetime(x) for x in df.index] # very slow! a lot faster:
kd.unix_to_datetime(df.index)
# also possible
[datetime.datetime.fromtimestamp(x) for x in df.index]

```
tinydataflow 0.0.8
biblioteca Python simples e extensível que facilita a criação e execução de pipelines de transformação de dados e automação de processos
License: MIT
Requires Python: >=3.8
Keywords: data flow transformation pipeline

TinyDataFlow Ã© uma biblioteca Python simples e extensÃ­vel que facilita a criaÃ§Ã£o e execuÃ§Ã£o de pipelines de transformaÃ§Ã£o de dados e automaÃ§Ã£o de processos. Com suporte para conectores de dados e transformadores que vÃ£o desde a leitura de arquivos, processamento de linhas, gravaÃ§Ã£o de arquivos CSV atÃ© envio de e-mails. O TinyFlow Ã© projetado para ser flexÃ­vel e modular, permitindo que vocÃª defina e execute fluxos de dados personalizados de maneira eficiente.

Recursos:

Conectores de dados : Integre vÃ¡rias fontes de dados, como arquivos TXT, CSV, bancos de dados, XML, e mais.
Transformadores de dados : Crie transformaÃ§Ãµes personalizadas para processar seus dados.
ExtensÃ­vel : Adicione seus prÃ³prios conectores e transformadores de maneira simples.

InstalaÃ§Ã£o:

VocÃª pode instalar o TinyDataFlow diretamente do repositÃ³rio ou clonar o projeto para desenvolvimento local:

# Clonando o repositÃ³rio
git clone https://github.com/ismaelnjr/tinydataflow_project.git
cd tinydataflow

# Instalando dependÃªncias
pip install tinydataflow -r requirements.txt

DependÃªncias

O TinyDataFlow utiliza as seguintes bibliotecas:

Python 3.8+
smtplib- Envio de e-mails via SMTP.
cryptography- Para criptografia de credenciais (opcional).
python-dotenv- Para carregar variÃ¡veis â€‹â€‹de ambiente de arquivos .env.
csv- Para leitura e manipulaÃ§Ã£o de arquivos CSV.

Uso:

Em test_case_email_sender.py Ã© um exemplo de como usar o TinyFlow para processar um arquivo CSV e enviar e-mails com templates.