PokeAPI-Data-Processor

PokeAPI Data Processor - Gather and Analyse Pokemon Data

📚 About

PokeAPI Data Processor is a tool for gathering Pokémon data from the PokeAPI and generating statistical results.

⚙️ Functionality

This tool is able to:

• Group Pokémon by their types (e.g., water, fire) and abilities.
• Count the number of Pokémon in each group.
• Calculate the average base experience for each type of Pokémon.
• Calculate the total number of unique abilities for each type of Pokémon.

🔧 Installation

Cloning the GitHub Repository

1. Clone the Repository: Open your terminal and run the following command to clone the GitHub repository to your local machine:

   git clone https://github.com/ValdonVitija/PokeAPI-Data-Processor.git

2. Navigate to the Repository:

   cd PokeAPI-Data-Processor

📋 Usage

1. Preparation

1. Create a virtual environment in the root of the project's directory

   python3 -m venv .venv

2. Active your virtual environment

   source .venv/bin/activate #Linux/Mac based
   ------------------------------------------
   .\.venv\Scripts\activate #Windows based

3. Install requirements in your virtual environment

   pip3 install -r requirements.txt

4. Run the app

   python3 -m src.main

   You will see something like this:

   /> python3 -m src.main
                               _
                   _ __   ___ | | _____ _ __ ___   ___  _ __
               | '_ \ / _ \| |/ / _ \ '_ ` _ \ / _ \| '_ \
               | |_) | (_) |   <  __/ | | | | | (_) | | | |
               | .__/ \___/|_|\_\___|_| |_| |_|\___/|_| |_|
       _       _|_|                                         _
   __| | __ _| |_ __ _   _ __  _ __ ___   ___ ___  ___ ___(_)_ __   __ _
   / _` |/ _` | __/ _` | | '_ \| '__/ _ \ / __/ _ \/ __/ __| | '_ \ / _` |
   | (_| | (_| | || (_| | | |_) | | | (_) | (_|  __/\__ \__ \ | | | | (_| |
   \__,_|\__,_|\__\__,_| | .__/|_|  \___/ \___\___||___/___/_|_| |_|\__, |
                           |_|                                        |___/
                           BY : VALDON VITIJA
   
   fetching all pokemons: 100%|███████████████████████████████████████████████████████████████████████████| 1302/1302 [00:13<00:00, 95.04pokemon/s]
   creating dataframe for pokemons:  44%|████████████████████████████▋                                     | 567/1302 [02:28<04:45,  2.58pokemon/s]

📁 Directory Structure

.
├── LICENSE #Software License. 
├── README.md #Contains the projects viewable documentation
├── pokeapi_logo.png #The logo of the project
├── pytest.ini #pytest configuration file.
├── requirements.txt #Contains project dependecies.
├── results #The generated results will be stored here
│   ├── csv
│   │   ├── avg_base_experience.csv
│   │   ├── pokemon_group_counts.csv
│   │   └── unique_abilities_count.csv
│   └── visual
│       ├── avg_base_experience.png
│       ├── pokemon_barplot_interactive.html
│       └── unique_abilities_count.png
├── src #contains the entire source code, modularized into python modules
│   ├── __init__.py #convert directory to a python pacakge
│   ├── api_connector.py #the interface towards the pokeapi
│   ├── data_processing.py #data structuring and processing
│   ├── main.py #the entryo point of execution
│   └── result_exporters.py #saves results into different formats
├── tests #contains unit tests
│   ├── __init__.py #convert directory to a python pacakge
│   ├── conftest.py #generic module that other modules will use 
│   ├── results #saved results for testing purposes
│   │   └── csv
│   │       ├── avg_base_experience.csv
│   │       ├── pokemon_group_counts.csv
│   │       └── unique_abilities_count.csv
│   ├── test_api_connector.py 
│   ├── test_data_processing.py
│   └── test_result_exporters.py

Abstract Execution Flow

📊 Results

1 Group Pokémon by their types (e.g., water, fire) and abilities

Important

It wouldn't be resonable to just print pokemons groups based on type and ability on a graph/plot, because we group data to apply statistical functions on them and not just group them and do nothing with such groups.

2 Count the number of Pokémon in each group

Note

The graphical result on this case is an interactive graph. To interact with it open the html file in a browser and you will find the plotted graph. Do this after you have cloned the repo locally.

• Graphical: View Interactive Graph
• CSV: View CSV 📄

3 Calculate the average base experience for each type of Pokémon

• Graphical: View Graph
• CSV: View CSV 📄

4. Calculate the total number of unique abilities for each type of Pokémon

• Graphical: View Graph
• CSV: View CSV 📄