Web scraping in Python - Step by step guide

• Become familiar with a web environment in which you want to extract certain information.
• Develop a code to obtain its content and extract it from a specific table.
• Use a database to store the data and process it.

🌱 How to start this project

Follow the instructions below:

1. Create a new repository by forking the Git project or by clicking here.
2. Open the newly created repository in Codespace using the Codespace button extension.
3. Once the Codespace VSCode has finished opening, start your project by following the instructions below.

📝 Instructions

1. Read the ./INSTRUCTIONS.es.md file to learn the detailed steps of the project.

2. Develop your solution in ./src/explore.ipynb. When you are in the ./src/explore.ipynb file, make sure to select the appropriate kernel. Upon opening the notebook, a message will appear at the top indicating "Select Kernel". Click on "Select Kernel" (as shown in the image).

   

   A list with available options will be displayed. Select "Python Environments" and choose the Python version you want to use. Make sure to select the version specified in the devcontainer.json file, as this is the recommended one for the project.

   

3. Transfer the clean code to ./src/app.py once you have finished testing.

4. Delete ./src/explore.ipynb after ensuring you no longer need it. This will keep the project clean and organized.

Follow these steps and proceed with the project in a structured manner! 🚀

Note: We also incorporated the solution samples on ./src/solution.ipynb that we strongly suggest you only use if you are stuck for more than 30 min or if you have already finished and want to compare it with your approach.

🚛 How to deliver this project

Once you have finished solving the exercises, be sure to commit your changes, push them to your repository, and go to 4Geeks.com to upload the repository link.