Glovo-Scraper is a Python project that scrapes data from a popular fast food app, organizes it based on price and location, and then saves it to both CSV and MongoDB for further analysis. This tool allows you to collect valuable data from your favorite fast food restaurants and perform various analyses on it. Ideal for when you want a good meal but don't want to pay more than necessary.
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The "Fast Food App Data Scraper" project is a powerful tool designed for efficiently collecting and organizing data from the Glovo application. Whether you're a food enthusiast, a market analyst, or just someone looking for a great meal deal, this project is your go-to solution.
To get a local copy up and running follow these simple example steps.
Before you can get started with this project, make sure you have the following prerequisites installed on your system:
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Docker: You'll need Docker to create and manage containers for this project. If you don't have Docker installed, you can download and install it from the official Docker website: Docker Installation Guide
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pip (Python Package Manager): If you plan to use Python-based components or libraries in this project, ensure that
pipis installed.pipis commonly included with Python installations, but you can upgrade it to the latest version using the following command:
pip install --upgrade pip- Clone the repo:
git clone https://github.com/AndreiRaducanu/Glovo-Scraper.git
- Install the glovo package:
pip install -e .
You'll need to have docker already installed than follow these steps:
- Install the latest package (check packages for latest version):
docker pull ghcr.io/andreiraducanu/glovo-scraper:sha-1c15d79
- Run a container using the image:
Use the "-it" flag since you'll need to input credentials
docker run -it ghcr.io/andreiraducanu/glovo-scraper:sha-1c15d79
The data stored in the database provides a rich source of information that can be leveraged to perform various queries and analyses. With this data, you can conduct targeted searches to retrieve specific information, such as finding all products with certain keywords or attributes. For instance, if you're interested in identifying all the burger-related 🍔 items in a restaurant's menu, you can perform a query using relevant keywords or filters to retrieve this subset of data.
- Scrape data from all available restaurants
- Store the aquired data in a database
- Host a fully-fledged web application
- Make it accessible for users in any country using Glovo
See the open issues for a full list of proposed features (and known issues).
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. Alternatively, you can open an issue labeled 'enhancement'. Don't forget to give the project a star! Thanks again!
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Distributed under the MIT License. See LICENSE.txt for more information.
Andrei Raducanu - LinkedIn - raducanuandrei31@gmail.com
Project Link: https://github.com/AndreiRaducanu/Glovo-Scraper
Resources I've found helpful while building this project: