How to Speed Up File Listing in Python

When dealing with large directory structures, efficiently listing files that match a specific pattern can be crucial for optimal performance. In this article, we’ll explore a faster alternative to using `os.walk` for listing files and provide examples using Python’s `os` module.

1. Problem Overview.

  1. The user has a directory structure where top-level directories (`A`, `B`, `C`, etc.) under the `test` directory contain a subfolder named `foo`.
  2. The goal is to obtain a list of all filenames within the `foo` subfolders that match a specific pattern.
  3. The user’s initial approach, using a list comprehension with `os.walk`, is deemed slow even for small directory structures.

2. Solution.

  1. To speed up the file listing process, we can leverage the `os.listdir` function along with `os.path.join`.
  2. This approach eliminates the need for unnecessary recursive directory scans performed by `os.walk`.
  3. Additionally, using `os.path.isdir` helps ensure that only valid subdirectories are considered.

3. Example Code.

  1. Below are the example file structure.
    │   └───foo
    │           foo1.txt
    │           foo2.txt
    │           foo3.txt
    │   └───foo
    │           foo4.txt
    │           foo5.txt
    │           foo6.txt
  2. Below are the source code that implement this example.
    import os
    def list_files_matching_pattern(directory, pattern):
        file_list = []
        for entry in os.listdir(directory):
            subdir_path = os.path.join(directory, entry, 'foo')
            if os.path.isdir(subdir_path):
                files_in_subdir = [file for file in os.listdir(subdir_path) if file.startswith(pattern)]
        return file_list
    # Example Usage:
    directory_path = 'test'
    pattern_to_match = 'foo'
    result_files = list_files_matching_pattern(directory_path, pattern_to_match)
  3. Output.
    ['foo1.txt', 'foo2.txt', 'foo3.txt', 'foo4.txt', 'foo5.txt', 'foo6.txt', 'foo7.txt', 'foo8.txt', 'foo9.txt']

4. Explanation.

  1. The `list_files_matching_pattern` function takes a directory path and a pattern as input parameters.
  2. It uses `os.listdir` to iterate over the entries in the specified directory (`test` in this case).
  3. For each entry, it constructs the path to the `foo` subdirectory using `os.path.join`.
  4. It then checks if the constructed path corresponds to a valid directory using `os.path.isdir`.
  5. If the directory is valid, it uses another list comprehension to filter files in the `foo` subdirectory based on the specified pattern.
  6. The matching files are then added to the `file_list`.
  7. The final list of files that match the pattern is returned.

5. Conclusion.

  1. By replacing `os.walk` with a more targeted approach using `os.listdir`, you can significantly improve the speed of file listing, especially when dealing with large directory structures.
  2. This optimized method is more tailored to the user’s specific requirements and can enhance the performance of file-related operations in Python.

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