semvec/pypi-packages huggingface dataset:
deltatextsplitter 1.1.0
This packages can efficiently measure the text structure recognition capabilities ofn pdftextsplitter
License: MIT
Requires Python: >=3.10
Keywords: NLP,PDF,Text recognition,Structure recognition,ChatGPT

# DeltaTextsplitter package

This package is meant to provide an objective evaluation of the performance of the
[pdftextsplitter](https://pypi.org/project/pdftextsplitter/) package in terms of
KPI's.
<br />
<br />
The package includes a set of test documents with references in the form of excel-files.
These reference-files are human-produces excel-files containing the structure of
the test documents that the pdftextsplitter package should have recognised. This can then
be compared to the actual output of the pdftextsplitter package, so that the performance
of the package can be evaluated.
<br />
<br />
The performance is evaluated in terms of the following two KPI's <br />
structure KPI = 1 - (fp + tn)(fp + tt) <br />
where tt = true total, the total number of structure elements in the reference-file,
fp = false positive, the number of structure elements that are present in the output, but not in the reference-file,
and tn = true negative, meaning tn = tt - tp, where tp = true positive,
the number of matching structure elements between the reference-file and the actual outcome.
Two structure elements are said to match if the fuzzy match ratio of their titles is >=80.0
(determined with the package [thefuzz](https://pypi.org/project/thefuzz/)) and their main structure types are equal.
<br />
<br />
cascade kpi = 1 - uc/tp <br />
where uc = unequal cascades, a subset of the above number tp where the cascade levels
of the reference-file and the outcome of the package do not match.
<br />
<br />
With these two KPI's, it is possible to quantify improvements made to the pdftextsplitter
package by calculating KPI's for each released version of pdftextsplitter.

### Getting started

The KPI calculation can be performed efficiently by entering the following commands:
from deltattextsplitter import documentclass <br />
mydelta = deltattextsplitter()
mydelta.FullRun()
<br />
<br />
The KPI's will then be printed, but can also be retrieved from: <br />
mydelta.structure_kpi <br />
mydelta.cascade_kpi <br />
The KPI's per test document can also be retrieved from: <br />
mydelta.documentarray[index].splitter.documentname <br />
mydelta.documentarray[index].structure_kpi <br />
mydelta.documentarray[index].cascade_kpi <br />
There are 12 testdocuments in total.
<br />
<br />
The FullRun-command is very CPU-intensive, as it needs to process all the test documents
with the pdftextsplitter-package (in dummy-mode). Once this has been done, one could
speed up the process of subsequent calculations by entering <br />
mydelta.FullRun(False,False) <br />
to skip the pdftextsplitter-execution and only redo the KPI-calculation.
repobee-junit4 2.0.0
JUnit4 runner plugin for RepoBee
License: MIT
Requires Python: >=3.9

# `repobee-junit4`, a JUnit4 test runner plugin for [RepoBee](https://github.com/repobee/repobee)

[![Build Status](https://travis-ci.com/repobee/repobee-junit4.svg?branch=master)](https://travis-ci.com/repobee/repobee-junit4)
[![Code Coverage](https://codecov.io/gh/repobee/repobee-junit4/branch/master/graph/badge.svg)](https://codecov.io/gh/repobee/repobee-junit4)
[![PyPi Version](https://badge.fury.io/py/repobee-junit4.svg)](https://badge.fury.io/py/repobee-junit4)
![Supported Python Versions](https://img.shields.io/badge/python-3.9%2C%203.10%2C%203.11-blue.svg)
![Supported Platforms](https://img.shields.io/badge/platforms-Linux%2C%20macOS-blue.svg)
[![License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE)

> **repobee-junit4 v1.0.0 requires RepoBee 3:** From version 1.0,
> repobee-junit4 is only compatible with RepoBee 3+.

## Overview
This is a plugin for [RepoBee](https://github.com/repobee/repobee) that runs
JUnit4 test classes on production classes in cloned student repos. It allows
teachers and teaching assistants to quickly assess the work performed by
students in a managed and fair way. The plugin hooks into the `repos clone`
command, and executes test classes on repos when they have been cloned to disk.
A summary report is then printed to the logfile and terminal. By default, the
plugin will only report which test classes failed (and how many tests), but it
is possible to ask for more verbose output which includes detailed information
about each test failure. See this [example use
case](https://repobee-junit4.readthedocs.io/en/latest/usage.html#example-use-case)
for a more detailed look at how it works.

### Install
Use RepoBee's plugin manager to install.

```bash
$ repobee plugin install
```

### Getting started
The best way to get started with `repobee-junit4` is to head over to the
[Docs](https://repobee-junit4.readthedocs.io), where you (among
other things) will find more elaborate
[install instructions](https://repobee-junit4.readthedocs.io/en/latest/install.html)
and [usage instructions](https://repobee-junit4.readthedocs.io/en/latest/usage.html).
The latter includes an
[example use case](https://repobee-junit4.readthedocs.io/en/latest/usage.html#example-use-case)
which hopefully proves useful in clarifying how `repobee-junit4` is supposed to
be used.

## Roadmap
This plugin is in the alpha testing phase. All features currently in the plugin
will remain, but the CLI is not yet final and may change. This is partly due to
the fact that the RepoBee plugin system itself is still in alpha, and may also
change.

Versioning for the CLI adheres to
[Semantic Versioning 2.0.0](https://semver.org/spec/v2.0.0.html). The internals
of `repobee-junit4` _do not_, so this project should not be used as a library.

## License
This software is licensed under the MIT License. See the [LICENSE](LICENSE)
file for specifics.