semvec/pypi-packages huggingface dataset:
fluxo 0.14.2
Simple data flow with execution in separate threads and easy scheduling configuration.
License: MIT
Requires Python: >=3.11
Keywords: fluxo, data, scheduler

# Fluxo

![Logo Fluxo](https://firebasestorage.googleapis.com/v0/b/teste-nascin-cripto.appspot.com/o/icon-192.png?alt=media&token=ab503840-b47d-4555-8bf4-16347df27d55)

### Simple data flow with execution in separate threads and easy scheduling configuration.

# Installation

To use the `fluxo` library, you can install it using the pip command. Make sure you have Python and pip installed before proceeding.

```
pip install fluxo
```

# How to Use

### 1 - Create a folder in the project root:

First, create a folder named `python_files` at the root of your project. This folder will contain your Python files.

### 2 - Create a Python file within the python_files folder:

Now, create a Python file named fluxo1.py within the python_files folder. This is where you can write your Python code.

### 3 - Write the code:

Write the following code in the fluxo1.py file to create a basic flow with a task:

#### python_files/flow1.py:

```
from fluxo import Flow, Task, Minutes

interval = Minutes(1, 30).format()
flow = Flow(name='My Flow 1', interval=interval)

@Task('My Task 1', flow=flow)
async def My_func():
    print('My_func executed!')
```

### 4 - Finally, start the program with the command below:

```
python -m fluxo.init_schedule
```

### 5 - In another terminal, run the command below to start the web server::

```
python -m fluxo.init_server
```

### 6 - Open browser:

```
http://127.0.0.1:8080
```

![Logo Fluxo](https://firebasestorage.googleapis.com/v0/b/teste-nascin-cripto.appspot.com/o/fluxo-v0.14.0.png?alt=media&token=c6ac9ac9-d272-4312-be1b-219f409095e1)
punkz 0.0.6
Python utilities developed by Devpunks.
License: MIT
Requires Python: >=3.10

# PUNKZ

This is a package developed by Devpunks that contains some utilities for our projects.
At the moment it includes:

- Cache System (local, AWS S3 bucket)
- Processor Framework (very experimental)

## Table of Contents

- [Installation](#installation)
- [Usage](#usage)
- [License](#license)

## Installation

You can easily install this package using pip.

```
pip install punkz
```

## Usage

There are many utilities contained in this package.

### Cache System

#### Local Caching

Example Code for local caching.

```
from punkz.core import Cache, LocalCacheProvider
from punkz.packages import get_logger

logger = get_logger("cache_logger")
provider = LocalCacheProvider(".cache", logger=logger)
my_cache = Cache(
    provider=provider,
    cache_instance_id="test",
    expiration="1d",
    logger=logger
    )

@my_cache.cache
def my_func(x):
    return x + 1

print(my_func(99))
```

Note: not passing logger to the Cache or the Provider is possible and if done
it will simply deactivate logging and printing.

#### Caching on AWS

Example Code for caching on an AWS S3 bucket.

```
from punkz.core import Cache, AWSS3CacheProvider
from punkz.packages import get_logger

logger = get_logger("cache_logger")
provider = AWSS3CacheProvider(
    bucket_name="your-bucket-name",
    access_key_id="your-access-key-id",
    secret_access_key="your-secret-access-key",
    logger=logger
    )
my_cache = Cache(
    provider=provider,
    cache_instance_id="test",
    expiration="1d",
    logger=logger
    )

@my_cache.cache
def my_func(x):
    return x + 1

print(my_func(99))
```

### Processor Framework

This is still a work in progress functionality. Documentation will be added
in future releases.

## License

This package is released under MIT License.

## Disclaimer

This package is highly experimental and it will be further expanded and refactored in the future.