ChAnalyzer is a Python script designed to analyze churn rates based on user activity data stored in a PostgreSQL database. This script fetches data from the database, cleans it, and calculates the churn rate for a specified number of days. Additionally, it provides a method to check the status of a specific user.

Before running the ChAnalyzer script, make sure you have the following prerequisites installed:

• Python 3.x
• PostgreSQL
• psycopg2 library (pip install psycopg2)
• pandas library (pip install pandas)
• dotenv library (pip install python-dotenv)

To connect to the PostgreSQL database, you need to set up a .env file in the same directory as the script. The .env file should contain the following environment variables:

• DB_HOST: The host address of the PostgreSQL database.
• DB_PORT: The port number of the PostgreSQL database.
• DB_NAME: The name of the PostgreSQL database.
• DB_USER: The username to authenticate with the PostgreSQL database.
• DB_PASSWORD: The password to authenticate with the PostgreSQL database.
• DB_SSLMODE: The SSL mode to use for the database connection (e.g., require or verify-full).

Make sure to replace the placeholder values with your actual database credentials.

To run the ChAnalyzer script, follow these steps:

1. Clone the repository or download the script file.
2. Install the required dependencies listed in the "Prerequisites" section.
3. Create a .env file and set the necessary environment variables as described in the "Configuration" section.
4. Open a terminal or command prompt and navigate to the directory where the script is located.
5. Run the following command:

  $ python ChAnalyzer.py

The script will fetch the data from the PostgreSQL database, clean it, calculate the churn rate for the specified number of days (default: 90), and display the result on the console.

Note: You can modify the number of days and the user ID to check by modifying the relevant parameters in the calculate_churn_rate and _check_user_status method calls, respectively.

6. The script will print the churn rate and the status of the specified user to the console.

The ChurnAnalyzer class represents the main logic of the churn analysis script. It has the following methods:

• __init__(): Initializes the ChurnAnalyzer object and retrieves the database connection details from environment variables.
• _load_data(): Loads data from the PostgreSQL database and converts it into a pandas DataFrame.
• _clean_data(df_refresh_tokens, df_active_users): Cleans the dataset by removing unnecessary columns and records with missing values.
• calculate_churn_rate(df, days): Calculates the churn rate within a specified number of days.
• _check_user_status(result_df, target_user): Checks the status of a specific user and prints the result to the console.

The script's entry point is the if __name__ == "__main__": block at the bottom. It creates an instance of the ChurnAnalyzer class, loads data from the database, cleans the data, calculates the churn rate, and checks the status of a specific user.

You can modify the number of days and the user ID to check by changing the arguments passed to the calculate_churn_rate and _check_user_status method calls, respectively.

The ChAnalyzer script provides a convenient way to analyze churn rates based on user activity data stored in a PostgreSQL database. By following the instructions outlined in this README, you can easily configure and run the script to obtain churn rate insights for your application or service.