semvec/pypi-packages huggingface dataset:
pytest-chic-report 2.0.3
Simple pytest plugin for generating and sending report to messengers.
License: MIT
Requires Python: >=3.8
Keywords: pytest, report, messenger, teams, slack

## pytest-chic-report


`pytest-chic-report` is a plugin for pytest that allows you to generate test result summaries in Markdown format and send them to Slack or Teams channels.

### Installation

You can install `pytest-chic-report` via pip from [PyPI](https://pypi.org/project/pytest-chic-report/).

```bash
pip install pytest-chic-report
```

### Usage

**Adding Command Line Options**

The plugin adds several command line options to customize the reports:

- `--summary` Print a summary in the terminal (enabled by default).
- `--suite-name` Specify the name of the test suite (default: "Regression").
- `--whois` Specify the name of the user who triggered the tests.
- `--verify-ssl` Enable TLS certificate verification.
- `--slack-webhook` Specify the webhook URL for Slack to send the report.
- `--teams-webhook` Specify the webhook URL for Teams to send the report.
- `--include-failed` Include a template of failed tests in the message.
- `--include-errors` Include a template of error tests in the message.
- `--include-all-tests` Include a template of all tests in the message.

### Example Usage:

```bash
pytest --slack-webhook https://hooks.slack.com/services/XXXXX/XXXXX/XXXXX
```


### Report Format

The report is generated in Markdown format and sent to the specified channel, featuring color-coded test results:

- green ✅ - all tests passed
- red ❌ - at least one test failed or error
- yellow ⏸️ - all tests skipped

**Example Report**

```markdown
--------- Suite Summary ---------
Suite name:    Regression
Passed amount: 7
Failed amount: 1
Skipped amount: 1
Xfailed amount: 4
Xpassed amount: 2
Total tests: 15
Total duration: 0.02 seconds
Successful tests: 47 %
From: Linux-6.8.0-47-generic-x86_64-with-glibc2.39
Show less
Sent by Anonymous | Today at 10:32 AM
```

**Note:** This does not work with the pytest-xdist plugin.
end-of-distribution 0.1.0
A Python library for detecting outliers at the end of the distribution
License: MIT
Requires Python: >=3.6

# End of Distribution

`end_of_distribution` is a Python library designed for statistical outlier detection, focusing on identifying values at the "end of the distribution" in datasets. It provides methods for detecting outliers using both **Z-score** and **Interquartile Range (IQR)**, commonly used techniques in data preprocessing and analysis.

## Features

- **Z-Score Outliers**: Identify outliers based on their distance from the mean.
- **IQR Outliers**: Detects outliers based on the interquartile range, robust against extreme values.

## Installation

After cloning the repository:

```bash
git clone https://github.com/adityayadav0111/end_of_distribution.git
cd end_of_distribution
```

To install directly if available on PyPI:

```bash
pip install end_of_distribution
```

## Usage

Import the functions from `end_of_distribution` to detect outliers in your data.

```python
from lib.end_of_distribution import z_score_outliers, iqr_outliers

# Example data
data = [1, 2, 3, 4, 100, 5]

# Detect outliers with Z-score
z_outliers = z_score_outliers(data, threshold=3)
print("Z-score Outliers:", z_outliers)

# Detect outliers with IQR
iqr_outliers = iqr_outliers(data)
print("IQR Outliers:", iqr_outliers)
```

### API Reference

- **`z_score_outliers(data, threshold=3)`**
  - Parameters:
    - `data` (list): List of numerical values to check for outliers.
    - `threshold` (float): Z-score threshold for identifying outliers. Default is 3.
  - Returns: A list with True/False for outliers in the dataset.

- **`iqr_outliers(data)`**
  - Parameters:
    - `data` (list): List of numerical values to check for outliers.
  - Returns: A list with True/False indicating outliers.

## Contributing

We welcome contributions! Hereâ€™s how to get started:

1. **Fork** the repository and **clone** it locally.
2. Create a new **branch** for your contribution.
3. Make your changes and **commit**.
4. **Push** your changes and open a **pull request**.

## License

This project is licensed under the MIT License - see the `LICENSE` file for details.