semvec/pypi-packages huggingface dataset:
testaroonie 0.0.1
A test package
Requires Python: >=3.6

# testaroonie

This is a Python package that facilitates testing with abstract scenarios. Utilizing PyTest, it offers extra utilities to streamline the creation and execution of abstract tests.


## Installation

You can install the `testaroonie` module via pip:

```sh
pip install testaroonie
```

Or directly from the source:

## Usage

Below is a usage example of the `testaroonie`:

```python
from testaroonie import create_test, execute_test

test = create_test(name="Test 1", scenario=[...])
execute_test(test)
```

This example creates an abstract test and then executes it.

## Documentation

The `testaroonie` module provides the following classes and functions:

### `create_test(name: str = 'Test', scenario: list = [...])`

Generates an abstract test scenario with the provided name and details.

### `execute_test(test: any)`

Executes the given abstract test scenario.

### `validate_test(test: any) -> bool`

Verifies if the given object is a valid test scenario.

### `calculate_test_results(test: any) -> dict`

Calculates the results of a given abstract test scenario.

### `compare_test_results(test1: any, test2: any) -> bool`

Compares two test scenarios and returns True if their results are equivalent, False otherwise.

... and many more!

Please refer to the source code for the complete list of classes and functions provided by the module, as well as their detailed documentation.

## Contributing

Contributions are welcome! Please fork this repository and open a pull request to add snippets, make grammar tweaks, etc.

## Contact

If you have any questions, feel free to reach out to us at partners@abstractendeavors.com.

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.

## Authors

* putkoff - main developer

This README file was last updated on May 29, 2023.
st-track-analysis 0.0.7
A Streamlit component for visualizing track data on images
Requires Python: >=3.6


      st-track-analysis
      ================

      st-track-analysis is a Python package that provides a custom Streamlit component for visualizing track data on images. It allows you to easily plot and analyze tracks with associated ground data on top of images.

      Features
      --------
      - Supports visualizing multiple tracks with their associated ground data on the same image.
      - Easily overlay shape data, such as bounding boxes, on the images.
      - Option to provide names for each track for better identification.
      - Customizable key for using the component in Streamlit apps.
      - Automatic conversion of images created by matplotlib into base64-encoded URLs for display.

      Requirements
      ------------
      - Python 3.x
      - streamlit
      - matplotlib
wikidata-dl 2023.7.27
Download data from Wikidata based on input SPARQL query.
Requires Python: >=3.9
Keywords: cli,command line,dl,download,sparql,wikidata

# wikidata-dl

## Description

**wikidata-dl** is a command line program for downloading data from [Wikidata](https://www.wikidata.org/) based on [SPARQL](https://en.wikipedia.org/wiki/SPARQL) queries.

## Installation

    pip install wikidata-dl

## Usage

Download result returned from the query and save it in the directory `./wikidata`:

    wikidata-dl /path/to/my-query.sparql

For a complete reference of the command line options run:

    wikidata-dl --help

## Sample Query

The following query returns IDs for all Wikidata entities that are an instance of ([P31](https://www.wikidata.org/wiki/Property:P31)) a continent ([Q5107](https://www.wikidata.org/wiki/Q5107)).

    SELECT ?item WHERE {
        ?item wdt:P31 wd:Q5107.
    }

[Try the query](https://query.wikidata.org/#SELECT%20%3Fitem%20WHERE%20%7B%20%3Fitem%20wdt%3AP31%20wd%3AQ5107.%20%7D)