GZIP

With compression we trade time for space. In compression we apply algorithms that change data to require less physical memory.

This slows down parts of programs

But it makes other parts faster: less data needs transferring. An important compression algorithm is GZIP.

First example

Many web pages are transferred with GZIP compression. This reduces the time required to load pages. In Python, we can use the gzip module.

And We open the source file and then open an output file. We then apply the gzip open() method to write the compressed file.

Tip The with statement is helpful here. This statement ensures that system resources are properly freed.

import gzip

# Open source file.
with open("C:\perls.txt", "rb") as file_in:
    # Open output file.
    with gzip.open("C:\perls.gz", "wb") as file_out:
        # Write output.
        file_out.writelines(file_in)perls.txt size: 4404 bytes
perls.gz  size: 2110 bytes

Decompress

The gzip module has two main functions. It compresses data and decompresses data. In this next example we decompress the same file that was written in the previous program.

And In the output, we find the original file length is the same. No data was lost. We also have the file, in string format, in memory.

So Instead of written the decompressed file to disk and reading that in, we can directly use the string contents.

import gzip

# Use open method.
with gzip.open("C:\perls.gz", "rb") as f:
    # Read in string.
    content = f.read()

    # Print length.
    print(len(content))
4404

7-Zip, `subprocess`

We can invoke 7-Zip with the subprocess module in Python. This can be done on Windows or other platforms (but modifications to the executable name are needed).

Some notes

The Python site has some useful information on GZIP. Compression collapses space. And it often reduces the time required to process data.