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Скачать или смотреть How to Populate a List in Python Based on Object Properties

  • vlogize
  • 2025-04-09
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How to Populate a List in Python Based on Object Properties
Python - Populate a list by searching through a list of objects and seeing if they contain a specifipythonlistkeyerror
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Описание к видео How to Populate a List in Python Based on Object Properties

Discover how to efficiently search through a list of objects in Python and populate a new list based on specific values in nested lists.
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This video is based on the question https://stackoverflow.com/q/75827481/ asked by the user 'Moonlyte Demon' ( https://stackoverflow.com/u/20726724/ ) and on the answer https://stackoverflow.com/a/75834103/ provided by the user 'Eamonn Kenny' ( https://stackoverflow.com/u/2211268/ ) 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: Python - Populate a list by searching through a list of objects and seeing if they contain a specific value

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
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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How to Populate a List in Python Based on Object Properties

If you're delving into Python programming, you may encounter situations where you need to filter through a list of objects to find specific criteria. One common challenge is how to populate a new list with certain attributes from objects that contain specific values in their properties. In this guide, we will guide you through the process of extracting this information in a simple and effective manner.

The Problem Explained

Imagine you have a list of objects, which in this case represents different entities with availability times. Each object has a name, group, and a list of availability. The goal is to create a new list that includes only the entities available in the morning.

Here is what our list of objects looks like:

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

In this dataset, we need to find and extract the name and group for each object where "Morning" is listed in the availability.

Solution Approach

Step-by-Step Explanation

To achieve this, we'll loop through each object in my_list and check if "Morning" is in the availability list of that object. If it is, we can then append a new dictionary containing the name and group attributes to our new list.

Here's how we can implement this in Python:

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

Result

After running the above code, you will get the following output:

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

This means our new list now successfully contains information about the entities available in the morning.

An Alternative Inline Solution

Although the loop method is highly readable and maintainable, if you're looking for a more compact solution, you can use list comprehension. However, it's essential to keep in mind that this can impact readability, especially in larger projects.

Here’s how you can do it using list comprehension:

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

While this one-liner is concise, it's often less clear than the expanded loop version. Always prioritize clarity in your code!

Conclusion

In summary, whether you're a beginner or an experienced programmer, knowing how to traverse lists and filter results in Python is a crucial skill. The method we discussed today allows you to create new lists based on specific conditions, a valuable technique for data manipulation and analysis in Python. With practice, you'll find these techniques becoming second nature as you handle more complex datasets.

If you have any questions or want to explore more Python programming tips, feel free to reach out!

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