LinkedIn Auto Applier is a Python-based application designed to automate the LinkedIn Easy Apply process. It integrates with LinkedIn's API and OpenAI to generate personalized application content while ensuring user data security.
- Automates LinkedIn Easy Apply process.
- Generates personalized application content using OpenAI.
- Ensures user data security with encryption.
- Allows users to review and edit application content.
- Tracks the status of submitted applications.
-
Clone the repository:
git clone <repository-url> cd linkedin_auto_applier
-
Create a virtual environment and activate it:
python -m venv venv # On Unix or macOS source venv/bin/activate # On Windows .\venv\Scripts\Activate.ps1
-
Install dependencies:
pip install -r requirements.txt
-
Set up environment variables in a
.envfile. The LinkedIn and OpenAI credentials are required at startup:LINKEDIN_CLIENT_ID=<your-client-id> LINKEDIN_CLIENT_SECRET=<your-client-secret> OPENAI_API_KEY=<your-openai-api-key> ENCRYPTION_KEY=<your-encryption-key>
If
LINKEDIN_CLIENT_ID,LINKEDIN_CLIENT_SECRET, orOPENAI_API_KEYare missing, the application will raise an error when launched. -
Run the application:
python linkedin_auto_applier/app.py
To run the automated test suite, create a virtual environment and install the
project dependencies if you haven't already, then execute pytest:
# Create and activate a virtual environment
python -m venv venv
source venv/bin/activate # On Windows use `.\\venv\\Scripts\\Activate.ps1`
# Install dependencies
pip install -r requirements.txt
# Run the tests
pytest- Fork the repository and create a new branch for your feature or bug fix.
- Write clear and concise commit messages.
- Ensure your code adheres to PEP 8 standards.
- Write tests for your changes and ensure all tests pass.
This project is licensed under the MIT License. See the LICENSE file for details.