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Скачать или смотреть How to Pack and Unpack Data in Python Using struct for Binary Values

  • vlogize
  • 2025-05-17
  • 32
How to Pack and Unpack Data in Python Using struct for Binary Values
Pack into c types and obtain the binary value backpythonstructencodingutf 16binascii
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Описание к видео How to Pack and Unpack Data in Python Using struct for Binary Values

Discover how to pack integers into binary data and unpack them back correctly in Python with `struct`. Avoid errors and understand encoding with clear examples.
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This video is based on the question https://stackoverflow.com/q/72679002/ asked by the user 'user1241241' ( https://stackoverflow.com/u/13037510/ ) and on the answer https://stackoverflow.com/a/72680380/ provided by the user 'Mark Tolonen' ( https://stackoverflow.com/u/235698/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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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.

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How to Pack and Unpack Data in Python Using struct for Binary Values

In the world of programming, particularly when dealing with low-level data manipulation, understanding how to pack and unpack data correctly is crucial. If you’ve ever attempted to convert an integer into its binary representation and back, you may have encountered some obstacles. In this guide, we'll explore a common problem and provide a clear, step-by-step solution to successfully pack an integer into a binary format and later retrieve the original value without errors.

The Problem: ValueError When Unpacking Binary Data

Imagine you are using Python to pack an integer, specifically the number 40, into an unsigned short (binary format). Your initial thought is to use the struct module to pack this number into little-endian format. Here’s what your initial code might look like:

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

After packing the data, you may attempt to decode this binary data back into a human-readable format using UTF-16 encoding, only to be met with a perplexing error:

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

The Solution: Properly Unpacking Binary Data

The root of this issue lies in the method used to unpack the data. Since the binary data isn't actually UTF-encoded, employing UTF encodings is unnecessary. Instead, you should leverage the unpacking capabilities provided by the struct module to revert to the original integer. Let's break down this solution into manageable steps:

Step 1: Using struct.unpack

To reverse the earlier packing operation, use struct.unpack. This function retrieves the original data stored in the packed format.

Here's how you can modify your code:

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

Step 2: Accessing the Unpacked Value

The unpack function returns a tuple. To get the individual value, index into the tuple:

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

Step 3: Converting to Binary

Once you have retrieved your integer, you may want to display it in binary format. Python offers several ways to accomplish this:

Method 1: Using format()

You can format your integer to a binary string with leading zeros like this:

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

Method 2: Using f-strings (Python 3.6+ )

Another elegant way to format the binary output is using f-strings:

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

Conclusion

In conclusion, when dealing with binary data in Python, it’s essential to correctly pack and unpack your integers using the tools built into the struct module. By directly unpacking the already packed data and avoiding unnecessary encodings, you can retrieve your original values with ease. This guide not only solves the error you faced but also ensures you have a robust understanding of how to manipulate binary data effectively.

If you've faced similar issues or have queries about working with binary data in Python, feel free to share your experiences in the comments!

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