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Скачать или смотреть Automate Your JSON Data Extraction with Python: A Guide to Looping Through Multiple URLs

  • vlogize
  • 2025-09-08
  • 0
Automate Your JSON Data Extraction with Python: A Guide to Looping Through Multiple URLs
loop through multiple json files from website linkspythonjsonloops
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Описание к видео Automate Your JSON Data Extraction with Python: A Guide to Looping Through Multiple URLs

Need to extract data from multiple JSON files? Learn how to automate the process using Python to loop through multiple website links efficiently.
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This video is based on the question https://stackoverflow.com/q/63370295/ asked by the user 'rojo' ( https://stackoverflow.com/u/14090905/ ) and on the answer https://stackoverflow.com/a/63370412/ provided by the user 'Pie' ( https://stackoverflow.com/u/6378788/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: loop through multiple json files from website links

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The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
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Automate Your JSON Data Extraction with Python: A Guide to Looping Through Multiple URLs

If you work with data from various sources, you might find yourself grappling with the tedious task of manually extracting and processing information from multiple JSON files. This can be especially daunting when the data is consistently structured but scattered across different URLs. Fear not, as we dive into a solution that will help you automate this process using Python.

The Problem at Hand

You're extracting data from JSON files available at different URLs, then saving that data into CSV files for analysis. Although your code works perfectly for a single JSON file, manually pasting different links 100 times and running your code to combine the CSVs isn't the most efficient approach.

The Solution: Looping Through URLs

Instead of handling each URL separately, Python allows us to handle this in a much more streamlined manner. Here's how you can set up a loop to automatically process each JSON file from a list of website links.

Step 1: Prepare Your List of URLs

First, create a list containing all the website links that you want to retrieve JSON data from. If you have these URLs in a text file or CSV, you'll need to read them into your Python script. For this example, we will manually define the list for simplicity.

[[See Video to Reveal this Text or Code Snippet]]

Step 2: Setup Your Libraries

Make sure you have the necessary libraries installed: csv, json, pandas, and requests. These will help you handle the HTTP requests and data processing.

[[See Video to Reveal this Text or Code Snippet]]

Step 3: Loop Through the URLs

Now, you can create a for loop to iterate through each URL in your list. For each link, you will make a request to fetch the JSON data and store it accordingly.

[[See Video to Reveal this Text or Code Snippet]]

Step 4: Saving the Data to CSV

Once you have collected the data from all the websites, you can proceed to extract the relevant information and save it into separate CSV files. You can utilize pandas for this part as it makes saving data to CSV straightforward.

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

By utilizing a loop to automate the extraction of data from multiple JSON files, you can save time and effort, making your work more efficient and error-proof. So, the next time you find yourself juggling multiple URLs for JSON data, remember that Python has your back.

With just a few additional lines of code, you can streamline your data retrieval process and focus more on analysis rather than manually extracting data. Happy coding and data extracting!

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