semvec/pypi-packages huggingface dataset:
taskloop 0.4.1
Taskwarrior utility to continually loop through and add tasks to a project
License: MIT
Requires Python: >=3.10,<4.0

# Taskloop

This utility allows you to create multiple tasks for a
[Taskwarrior](https://taskwarrior.org) project.

# Installation

## via PyPi
` pip install taskloop`

## via git (development)
1. Clone this repo
2. cd taskloop
3. Add deps using poetry `poetry install`
4. `poetry run taskloop/loop.py`

# Running
After pip installing, you may run

`taskloop`

This requires you have a taskrc at ~/.config/task/taskrc.

More flexibility is planned for this though.  If you have an old style
~/.taskrc, you should be able to symlink it with `mkdir -p ~/.config/task/taskrc
&& ln -s ~/.taskrc ~/.config/task/taskrc`

## Entering tasks
You will be prompted for a project.  This will autocomplete from your list of
projects (currently only pending, planned to optionally pull from "completed"
also)

After entering a project, you will loop through adding tasks to the project.  if
you want to make your task dependent on the last task, start your task with a
period.

Entry will continue to loop until you end by entering an empty line

Now sync will be attempted.   There are currently no checks in place, so if you
don't have a taskserver configured,this will fail.

# Screencast Demo
[![asciicast](https://asciinema.org/a/B5IzyeUWdGRjK1bUtCjy52gpp.svg)](https://asciinema.org/a/B5IzyeUWdGRjK1bUtCjy52gpp)
devina 0.0.5
A python library that allows you to query various databases related to toxicology and gennomics
License: MIT
Keywords: ecotoxicology

A python library that allows you to query various databases related to toxicology and gennomics

Change Log
==========

0.0.1 (21/06/2022)
------------------
- First release


0.0.2 (21/06/2022)
------------------
- Fixing issues in setup.py


0.0.3 (21/06/2022)
------------------
- Fixing function issues in __init__.py

0.0.3 (21/06/2022)
------------------
- Adding a requirements.txt file

0.0.3 (21/06/2022)
------------------
- Adding dependancies
robotframeworkinteractive 1.0.5
Run Robot Framework interactively from the command line
License: MIT
Requires Python: >=3.8

# robotframework-interactive
This project is designed to allow Robot Framework (RF) commands to be ran interactively from the command line. It is 
important to note that not all RF keywords and commands will work as this is reading the input string and determining 
what to run.

![CI](https://github.com/tylerjosephrose/robotframework-interactive/actions/workflows/ci.yaml/badge.svg)

## Installation
`pip install robotframeworkinteractive`

## How To Run
`python -m robotframeworkinteractive`
![](documentation/images/Run.png)

### Running your first command
All the Robot Framework builtins are available right away. If you are on windows, they can be autocompleted by 
pressing the tab button.
![](documentation/images/FirstCommand.png)

### Importing a Library
Any library you have installed in your current python installation are available to be imported. The same can be done 
with any local resources by using the `Library` or `Resource` keywords
![](documentation/images/ImportingLibrary.png)

### Working with Variables
Just like in your testing, variables can also be set and accessed. 
![](documentation/images/Variables.png)

### Closing the prompt
The prompt can be closed by either typing `exit()` or by hitting ctrl-c twice
![](documentation/images/Exit.png)

## Limitations
* On Linux Clients the autocomplete feature does not work
* Multiline commands do not work (FOR loops, IF statements, etc)

## License
Distributed under the MIT License. See `LICENSE` for more information

## Contact
Tyler Rose - tylerjosephrose@gmail.com

Project Link: https://github.com/tylerjosephrose/robotframework-interactive
neat-ml-schema 0.1.11
A linkml based schema for the neat-ml project.
License: MIT
Requires Python: >=3.8,<4.0

# Neat-ml schema

Neat-ml schema defines the schema in the form of a [YAML file](https://github.com/Knowledge-Graph-Hub/neat-ml-schema/blob/main/neat_ml_schema/src/neat_ml_schema/schema/neat-ml-schema.yaml) for data going into graph ML pipelines (specifically [NEAT](https://github.com/Knowledge-Graph-Hub/neat-ml)). This project itself is generated using the command `linkml-ws new` derived from the [linkML](https://github.com/linkml/linkml) project.

[Documentation](https://knowledge-graph-hub.github.io/neat-ml-schema/)
installable-app-test 0.1
Sample installable django app
License: MIT
Requires Python: >=3.8

Installable App Test
=====================

This is sample code used in the Real Python article . It describes how to take an app from an existing Django project and make it a stand-alone installable package avilable on PyPI.

Installable App
---------------

This app models a list of items on a receipt. Each item has a description and a cost. A receipt may reference multiple items.
toppy-python 2.0.1
A simple API wrapper for Discord Bot List, DiscordBotsGG, and Top.gg
License: MIT
Requires Python: >=3.8.0

toppy
======

.. image:: https://raw.githubusercontent.com/chawkk6404/toppy/master/docs/toppy-logo.png
   :alt: toppy logo


An API wrapper made for discord.py or any forks for Discord Bot List, DiscordBotsGG, and Top.gg.


Documentation
--------------
https://toppy-python.readthedocs.io/en/latest/


Installation
------------
**Python 3.8 or higher is needed**

.. code:: sh

    $ pip install -U toppy-python



Example
---------

.. code:: py

    import toppy
    from discord.ext import commands
    

    dbl_token = 'Your Discord Bot List token here'
    dbgg_token = 'Your DiscordBotsGG API token here'
    topgg_token = 'your Top.gg token here'
    
    bot = commands.Bot('!')  # or discord.Client()
    toppy_client = toppy.Client(
        bot,
        dbl_token=dbl_token,
        dbgg_token=dbgg_token,
        topgg_token=topgg_token
    )
    
    
    @bot.event
    async def on_dbl_autopost_success():  # dbl/dbgg/topgg
        print('Server count posted')
        print(f'Server count: {len(bot.guilds)}')
    

    @bot.event
    async def on_dbl_autopost_error(error: toppy.HTTPException):  # dbl/dbgg/topgg
        print(f'Uh oh. An error occurred. Status: {error.resp.status}')
       
    
    
    bot.run(...)
c1algo1 0.0.1
scheduler algo
License: MIT
Requires Python: >=3.10

# algorithm-1

Branch and bound demo: Run test_assign_professors... whatever its called.

Pass in a year to generate_schedule to use historical data (WARNING: will run for 24 hours and eat all your memory before crashing)

Output is the tree structure with each path to a leaf being an optimal solution.

Number of solutions returned can be changed using the solution_limit variable, currently 10.