Metadata-Version: 2.1
Name: testrail-data
Version: 0.0.4
Summary: Pandas DataFrame integrated API wrapper for Testrail
Home-page: https://github.com/maxleow/testrail_data
Author: Max Leow
Author-email: maxengiu@outlook.com
License: UNKNOWN
Project-URL: Bug Tracker, https://github.com/maxleow/testrail_data/issues
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE

# Testrail Data: a handy Testrail data analysis tool
[![Python package][gh-action-python-package-badge]][gh-action-python-package]
[![PyPI][pypi-latest-release-badge]][pypi]
[![Downloads][pepy-downloads-badge]][pepy-downloads-link]
[![PyPI - Python Version][pypi-python-versions-badge]][pypi]
[![PyPI - Implementation][pypi-implementations-badge]][pypi]
[![License][license-badge]][license-link]

## What is it?

This is a wrapper of [Testrail Api](https://github.com/tolstislon/testrail-api) with [pandas](https://github.com/pandas-dev/pandas) DataFrame extended. Especially when you are working on huge data-set, say years of results, this is a handly library. 

## Installation

```shell
pip install testrail-data
```

## Main Features

- Transform pulled data into DataFrame object, covering:
  - Case
  - Case Fields
  - Case Type
  - Milestone
  - Plan
  - Priority
  - Results
  - Run
  - Sections
  - Suite
  - Statuses
  - Template
  - Test
- Complete pull with `auto-offset` capability to walk through all pagination, avalaible to:
  - Run
  - Result
  - Plan
- Meta data filling option to all IDs in:
  - Case
  - Test
  - Result (not in this version)

### Example usage with DataFrame

```python
from testrail_data import TestRailAPI

api = TestRailAPI("https://example.testrail.com/", "example@mail.com", "password")

# if use environment variables
# TESTRAIL_URL=https://example.testrail.com/
# TESTRAIL_EMAIL=example@mail.com
# TESTRAIL_PASSWORD=password
# api = TestRailAPI()

# if you having a big project with more than 250 runs, 
# this method would help you too pull them down in single call.
df_run = api.runs.to_dataframe(project_id=1)
df_run.info()

# Pulling all Run by Plan
df_run = api.runs.dataframe_from_plan(plan_id=3)
```

### Example usage with Meta data

```python
# continue ...

df_case = api.cases.to_dataframe(project_id=1, suite_id=2, with_meta=True)
# Additional name-columns created base on 
# section_id, template_id, type_id, priority_id, suite_id
# all custom_columns are replaced with meta data.

```

[gh-action-python-package]: https://github.com/maxleow/testrail_data/actions/workflows/python-package.yml
[gh-action-python-package-badge]: https://github.com/maxleow/testrail_data/actions/workflows/python-package.yml/badge.svg
[license-badge]: https://img.shields.io/badge/License-MIT-blue.svg
[license-link]: https://github.com/maxleow/testrail_data/blob/main/LICENSE
[pypi]: https://pypi.org/project/testrail-data/
[pypi-latest-release-badge]: https://img.shields.io/pypi/v/testrail-data?color=blue&label=pypi&logo=version
[pypi-implementations-badge]: https://img.shields.io/pypi/implementation/testrail-data-model
[pypi-python-versions-badge]: https://img.shields.io/pypi/pyversions/testrail-data.svg
[pepy-downloads-badge]: https://static.pepy.tech/personalized-badge/testrail-data?period=total&units=international_system&left_color=gray&right_color=blue&left_text=Downloads
[pepy-downloads-link]: https://pepy.tech/project/testrail-data


