semvec/pypi-packages huggingface dataset:
Pythactyl 2.18
Pterodactyl panel API wrapper
License: MIT

# Pythactyl
This Pterodactyl panel API wrapper is an unofficial wrapper. I made this in my free time and intend to improve as I go along 

## Install

    python -m pip install pythactyl

## Client

    from Pythactyl.Client import PterodactylClient
    
    client = PterodactylClient(url="https://panel.address.com", api_key="clientAPI")
    
    personal = client.listServers()
    
    print([x for x.name in personal])

    >> ['Fivem Server', 'Minecraft server awesome', 'Teamspeak 1.22']

## Admin

    from Pythactyl.Admin import PterodactylAdmin

    admin = PterodactylAdmin(url="https://panel.address.com", api_key="adminAPI"))

    user = admin.createUser('email@email.com', 'Bob', 'Simmons', root_admin=True)

    admin.editUser(user.id, username="INeedANewName")


## Information
I will be uploading documentation when the wrapper is completed. If you wish to know more syntax, you'll either have to source code dive or DM me: Gadget#6181.

## Need help?
Join my discord for more support on this wrapper: https://discord.gg/gnpZRcYqcn
mr-graph 0.2.6
A graph definition execution library for async/sync python functions.
License: MIT
Requires Python: >=3.7
Keywords: graph,mr_graph

# Mr. Graph

[![Documentation Status](https://readthedocs.org/projects/mr-graph/badge/?version=latest)](https://mr-graph.readthedocs.io/en/latest/?badge=latest)

Welcome to Mr. Graph!

Mr. Graph is a python library designed to make composing graphs of sync and async functions easy! Use google style docstrings to automagically create dataclasses and chain together function calls into graphs.

## Features

- Use with either async or sync functions
- Uses google style doc strings to name return values.
- Creates dataclasses for each function's output.
- Can infer pipelines from input and output signatures
- All directed acyclic graph layouts supported. linear, fan-in, fan-out.


## Example Usage

Building graphs can be as easy as:

```python
from mr_graph import Graph

def return_one():
    """
    return 1

    return one with no inputs

    Returns
    -------
    m : float
        equal to 1
    """
    return 1
    
async def add_1(m: float):
    """
    add 1 to a number

    add 1 to the input value n.

    Parameters
    ----------
    n : float
        number to add 1 to.

    Returns
    -------
    n : float
        equal to n + 1
    """
    return n + 1

async def build_implicit_linear_graph():
    """
    Return 2

    Simple example linear graph. Wired up automagically using the input and output variable names.

    Parameters
    ----------
    
    Returns
    -------
    two : float
        always equal to 2
    """

    g = Graph(nodes=[return_one, add_1])
    return await g()
```

More information can be found on read the docs!