https://github.com/spacexnu/job_finder
Automate Job Search & Analysis Using AI
https://github.com/spacexnu/job_finder
ai automation django job nlp openai python search spacy
Last synced: 28 days ago
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Automate Job Search & Analysis Using AI
- Host: GitHub
- URL: https://github.com/spacexnu/job_finder
- Owner: spacexnu
- License: mit
- Created: 2025-01-27T21:50:39.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2025-02-06T20:56:54.000Z (3 months ago)
- Last Synced: 2025-04-11T00:59:07.529Z (28 days ago)
- Topics: ai, automation, django, job, nlp, openai, python, search, spacy
- Language: Python
- Homepage:
- Size: 154 KB
- Stars: 3
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# **Job Finder 🕵️♂️**
## 🚀 Automate Job Search & Analysis Using AI
**Job Finder** is an open-source project that **scrapes job postings**
from multiple sources and **analyzes them using AI** based on user-defined criteria.
It helps developers and job seekers **find the best job opportunities efficiently**.
⚠️ **Note:** This is a **personal project** in an **early-stage of development**.
---
## **✨ Features**
✅ Scrapes job postings from multiple sources (e.g., GitHub Issues, LinkedIn, etc.)
✅ Uses **AI-powered analysis** to evaluate job descriptions
✅ Filters jobs based on **remote work, technologies, and contract types**
✅ **Fully customizable and extensible**
✅ Uses **Django & Celery** for background job execution
✅ Includes **Django Admin** for managing jobs & analysis criteria
---
## **📦 Installation**
### **Prerequisites**
- Python **3.12+**
- PostgreSQL **or** SQLite (for local testing)
- Docker & Docker Compose (optional, recommended)
- Redis (for Celery workers)
### **1️⃣ Clone the Repository**
```bash
git clone https://github.com/adlermedrado/job-finder.git
cd job-finder
```
2️⃣ Install Dependencies
Using [poetry](https://python-poetry.org/):
```bash
poetry install
```
Or using pip (requires a virtual environment):
```bash
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
```
3️⃣ Set Up the Database
Apply migrations:
```bash
poetry run python manage.py migrate
```
Or using venv:
```bash
python manage.py migrate
```
5️⃣ Setup environment variables
To run locally, rename [.env.sample](.env.sample) to **.env** and fill the required values,
or load the environment variables directly into your shell.
Setting up the .env file you can load them as below:
After setting up .env, load the variables as follows:
```bash
# Using Poetry
poetry shell
source load_env.sh # For Bash/Zsh
source load_env.fish # If using Fish shell
# Using venv
source load_env.sh # For Bash/Zsh
source load_env.fish # If using Fish shell
```
4️⃣ Run the Project
Start the Django server:
```bash
poetry run python manage.py runserver
```
Or using venv:
```bash
source load_env.sh (or if using fish: load_env.fish)
&& python manage.py runserver
```
Start celery workers:
```bash
celery -A job_finder worker --loglevel=info
```
Start celery beat:
```beat
celery -A job_finder beat --loglevel=info
```
(Optional) Run Redis & PostgreSQL via Docker:
```bash
docker-compose up -d
```
### 📌 Initial Sample Data (Optional)
If you want to load **initial configuration data** for Celery workers, Celery Beat, and job sources, run the following SQL script:
```bash
psql -U -d -f docs/sources_automation_samples.sql
```
⚠ **Note**: This data is for example purposes only and has not been included in Django migrations to keep a clear separation between database structure and sample data. Feel free to modify it as needed.
### 🔑 Django Admin Setup
To manage jobs, sources, and analysis criteria via Django Admin,
you need to **create a superuser**:
```bash
poetry run python manage.py createsuperuser
```
Or using venv:
```bash
python manage.py createsuperuser
```
You’ll be prompted to enter:
* **Username**
* **Email**
* **Password**
After creation, start the server and access Django Admin at:
**🔗 http://127.0.0.1:8000/admin/**
Log in with the credentials you just created.
### 👨💻 Contributing
Contributions are welcome! To contribute:
1. **Fork** the repo and create a **new branch** (git checkout -b feature-name)
2. Make your changes and test them
3. **Run tests** with `pytest`
4. **Submit a pull request (PR)**
### 📢 Support
If you find this project useful, ⭐ star the repository and share it with your network!
### 📅 Roadmap
✔ **Supported job sources:** Currently, the project scrapes job postings from **open-source repositories using GitHub Issues**
🚀 **Planned features:**
* Add support for **more job sources** (LinkedIn, Indeed, etc.)
* Improve **AI job matching accuracy** enabling **job analysis criteria configuration** via Django Admin
* Add support for **more AI providers** (currently it matches only remote positions, for example)
* Implement a **web dashboard** for job management
* Increase **test coverage**
* Improve documentation
### 📜 License
This project is licensed under the MIT License.
See [LICENSE](LICENSE) for details.
### 🔄 Basic Flow
```mermaid
graph TD;
A[Start] -->|Scrape job postings| B[Workers Job Scraper]
B -->|Save to database| C[(PostgreSQL)]
C -->|Sanitize Data using NLP| D[(spaCy)]
D -->|Analyze jobs using AI| E[OpenAI API]
E -->|Store analysis results| F[(Database)]
F -->|Display results| G[User Interface]
G -->|Done| H[End]