Data Analytics Application

An analytics for personal finance. Sources Data from Google Sheets, Exposes Data to be used for different Analytics.

Setup

• Install Python 3.10.5
• Install dependencies from requirements.txt

Google OAuth 2.0 Setup

To run this application, you need to enable the Google Drive API and create OAuth 2.0 credentials for a web application.

1. Enable Google Drive API:

   • Go to the Google Cloud Console.
   • Create a new project or select an existing one.
   • In the navigation menu, go to APIs & Services > Library.
   • Search for "Google Drive API" and enable it.

2. Create OAuth 2.0 Credentials:

   • In the Google Cloud Console, go to APIs & Services > Credentials.
   • Click Create Credentials and select OAuth client ID.
   • For the Application type, choose Web application.
   • Give it a name (e.g., "Personal Finance App").
   • Under Authorized redirect URIs, add http://localhost:8501. This is the default address for Streamlit applications.
   • Click Create.

3. Download Credentials:

   • After creating the credentials, a dialog will appear with your Client ID and Client Secret.
   • Click the Download JSON button to download the credentials file.
   • Rename the downloaded file to credentials.json.
   • Place the credentials.json file in the src/main/config/ directory of this project.

• variables to connect to google storage

  KEY	VALUE
  SPREADSHEET_ID	1-gogole-sheets-id
  SCOPES	https://www.googleapis.com/auth/spreadsheets.readonly
  SOURCE_FILENAME	filename
  SERVICE_EMAIL	email-d
  PRIVATE_GSHEETS_URL	google-sheets-url
  SERVICE_ACCOUNT_FILE	credentials.json
  PROJECT_ID	agumbe
  PRIVATE_KEY_ID	id
  PRIVATE_KEY	key
  CLIENT_EMAIL	email
  CLIENT_ID	client-id
  CLIENT_X509_CERT_URL	client-url

• variables needed to import data to database

  KEY	VALUE
  LOAD_TYPE	full / incremental
  DBNAME	finance.db

Run

• Data Load
  • SET ENV variable LOAD_TYPE to full/incremental
  • RUN python3 -m main [will trigger the driver method]
• RUN Streamlit server
  • python -m streamlit run src/main/analyse/index_page.py
• Open your browser and navigate to http://localhost:8501.
• You will be prompted to sign in with your Google account.
• After signing in, you can enter the name of your Google Sheet and download it for analysis.