The Poke-berries statistics API provides information about different types of berries. all the information is retrieved from the PokeAPI (https://pokeapi.co/docs/v2#berries-section).
- Python 3.x
- Flask
- requests
- cachetools
- asyncio
- aiohttp
- pytest
- gunicorn
- matlplotlib
Clone the repository:
$ git clone https://github.com/luis/pokeapi.git
Navigate to the project directory:
$ cd pokeapiCreate a virtual environment:
$ python3 -m venv venv
Activate the virtual environment:
$ source venv/bin/activateInstall the dependencies:
$ pip install -r requirements.txt
The API offers the following endpoint to retrieve statistics about the berries:
Get Berry Statistics
Endpoint: /allBerryStats Method: GET Response: JSON with berry statistics
Example response:
{
"berries_names": [
"aguav",
"apicot",
"aspear",
...
],
"frequency_growth_time": {
"2": 5,
"3": 5,
...
},
"max_growth_time": 24,
"mean_growth_time": 15.0,
"median_growth_time": 15.0,
"min_growth_time": 2,
"variance_growth_time": 61.5
}Get Berry statistics histogram
Endpoint: /allBerryStats/histogram Method: GET Response: html with berry statistics histogram
Example response:
<!DOCTYPE html>
<html>
- <head>
- <title>Poke-Berries Statistics Histogram</title>
</head>
- <body>
- <img src="data:image/png;base64,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" alt="Histogram">
</body>
</html>
If you wish to contribute to this project, follow these steps:
Create a new branch:
$ git checkout -b feature/new-feature
Make the necessary changes.
Commit your changes:
$ git commit -m "Add new feature"Push your changes to the repository:
$ git push origin feature/new-feature
Open a pull request on GitHub.
This project is licensed under the MIT License. See the LICENSE file for more details.