How to read large text files in Python?

How to read large text files in Python?

Reading large text files in Python can be memory-intensive if you attempt to load the entire file into memory at once. However, Python provides several methods to read large files more efficiently:

  1. Reading Line by Line: You can use a for loop to iterate over each line in the file. This is memory-efficient because only one line is loaded into memory at a time.

    with open('large_file.txt', 'r') as file: for line in file: # process each line here pass

  2. Reading in Chunks: Instead of reading line by line, you can read a fixed number of bytes (a chunk) at a time. This is useful if you want more control over the size of data being read.

    chunk_size = 1024 # 1KB with open('large_file.txt', 'r') as file: while True: data = file.read(chunk_size) if not data: break # process the data here pass

  3. Using pandas with Chunking: If you are working with structured data (like CSV or Excel files) and use pandas, you can read in chunks of the file using the chunksize parameter.

    import pandas as pd chunk_iter = pd.read_csv('large_file.csv', chunksize=10000) # read 10,000 rows at a time for chunk in chunk_iter: # process each chunk (which is a DataFrame) here pass

  4. Memory-Mapped Files: The mmap module allows you to create a memory view of a file. Memory-mapped files can be useful for large files that need to be accessed randomly.

    import mmap with open('large_file.txt', 'r') as file: mmapped_file = mmap.mmap(file.fileno(), 0, access=mmap.ACCESS_READ) # Now you can access mmapped_file like a bytearray # For example, to read 10 bytes at offset 100: mmapped_file[100:110]

  5. Lazy Evaluation with Generators: Generators are a way to produce items one by one using the yield keyword, rather than creating a large list of items. They can be useful to process large files in a more modular way.

    def read_large_file(file_path): with open(file_path, 'r') as file: for line in file: yield line file_gen = read_large_file('large_file.txt') for line in file_gen: # process each line here pass

When dealing with large files, it's also a good practice to monitor the memory usage of your program and test on a smaller subset of the data first. This helps in ensuring that your code scales efficiently.

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