semvec/pypi-packages huggingface dataset:
pntools 0.3.1
Petri net and labelled partial order tools
License: MIT
Keywords: Petri net labelled partial order pnml lpo

PNTools
=======

PNTools is a collection of small Python 3 scripts. These
scripts support parsing of pnml and lpo files, define a
data structure for Petri nets and labelled partial orders
and contain algorithms to work with such structures.

Modules:
--------

* partialorder.py:

This module implements classes for labelled partial orders
and a parser for .lpo-files created with VipTool or MoPeBs
(http://www.fernuni-hagen.de/sttp/forschung/mopebs.shtml)

* petrinet.py:
This module implements classes for Petri nets and a parser
for .pnml-files. (http://www.pnml.org/)

* lpo_viewer_tk.py:
This module implements a GUI for viewing labeled partial 
orders. This GUI is build with Tkinter.

* petrinet_viewer_tk.py:
This module implements a GUI for viewing Petri nets. This GUI
is build with Tkinter.

* lpo_viewer.py:
This module implements a GUI for viewing labeled partial
orders. This GUI uses PyQt5!

(partial) Requirements:
-----------------------

Some of the user interfaces are build with PyQt5, therefore 
you need to install Qt5 and PyQt5 if you want to use these GUIs.
tv-extract 1.0.15
Team Viewer - Data Extract for analysis
License: MIT
Keywords: library

[![Build Status](https://travis-ci.com/rappdw/tv-extract.svg?branch=master)](https://travis-ci.org/rappdw/tv-extract) [![Coverage Status](https://codecov.io/gh/rappdw/tv-extract/branch/master/graph/badge.svg)](https://codecov.io/gh/rappdw/tv-extract) [![PyPI - Version](https://img.shields.io/pypi/v/tv-extract.svg)](https://pypi.org/project/tv-extract/) [![PyPI - Wheel](https://img.shields.io/pypi/wheel/tv-extract.svg)](https://pypi.org/project/tv-extract/)


# Team View - Extract (Data extraction for team analysis)
Extract team analysis data from git (current) 
and other relevant sources (future).

## Pre-requisites for Use

1. [Tokei](https://github.com/Aaronepower/tokei) (This [fork](https://github.com/rappdw/tokei/network) has initial, 
rudementary, support for Jupyter notebooks). Tokei is used to collect metrics on volume of source based per source 
language.

If you don't have rust installed and aren't currently using Tokei, We recommend utilizing the 
[team-view-extract](https://hub.docker.com/r/rappdw/team-view-extract/) docker image.

## Setup

A configuration file that defines the "project" for extract must be defined. The
configuration file is json.

**Example**:

```json
{
  "extracts": [
    {
      "name": "Project 1",
      "repos": [
        {
          "name": "TeamView",
          "remote": "git@github.com:rappdw/TeamViewer.git"
        },
        {
          "name": "team-view-extract",
          "remote": "git@github.com:rappdw/team-viewer-extract.git"
        }
      ],
      "start_date": "2018-07-18",
      "end_date": "2018-08-31"
    }
  ],
  "output_path": "~/.local/share/cache/TeamView",
  "mailmap_file": "~/.local/share/cache/.mailmap",
  "logging": 20
}
```

Multiple extracts can be defined in a singl configuration file. `start_date`, `end_date`, `mailmap_file` and `logging` 
are all optional. `logging` defaults to info level. `start_date` defaults to beginning of project. `end_date` defaults
to `today`. If no `mailmap_file` is specified, standard git configuration applies.

A good way to create the mailmap file is to construct based on `git shortlog -sne` for each repository.

## Results

For each extract specified in the configuration file, a sub-directory will be created in the directory spcified by 
`output_path`. The following files will be created:

* author_totals.csv - Commit counts by author and repository (excluding merge commits)
* loc.csv - File counts by language, commit and repository (commits to master branch only)
* loc_delta.csv - File Counts by author, language, commit and repository (excluding merge commits)
* prs.csv - Pull request by repo including duration between last commit to branch and merge to master
* repo.csv - Current state of volume of code by language for each repo
* revs.csv - Revision graph by repo

## 'Temporary' Files
`~/.local/share/cache` is used to cache temporary files including checkout of repos specified by extract and a cache of 
the LOC revision history of each repo. If present this cache is updated on subsequent runs. If not present it is 
recreated from scratch.
sfmc-to-json 0.2.10
Used to format FuelSDK reponses into JSON
License: MIT

# Salesforce Marketing Cloud -- Response to JSON

This is a small utility library that I built to process responses from the [Salesforce Marketing Cloud SDK](https://github.com/salesforce-marketingcloud/FuelSDK-Python). It returns JSON payloads sometimes and other times it will return a list of SUDS objects.

## Installation

pip install sfmc-to-json

## Rebuild Package

1. Update version in `setup.py` and `__init__.py`
2. `python setup.py sdist bdist_wheel`
3. `twine upload dist/*` 

## Known Issues

Sometimes error messages come back and will be malformed. They will be valid JSON, but you'll see extraneous data in them.