Python compression.zstd Module

Python 3.14 added the compression.zstd module for working with the Zstandard compression format directly from the standard library. It provides one-shot compression and decompression functions, file-oriented APIs, and incremental compressor and decompressor classes.

Zstandard, commonly called zstd, is a lossless compression format designed for fast compression and decompression with strong compression ratios. Python's new module means many applications can use zstd without installing a third-party package.

Import compression.zstd

from compression import zstd

The compression package itself is new in Python 3.14. It also exposes canonical import paths for gzip, bz2, lzma, and zlib while preserving their older module names for compatibility.

compression.zstd requires Python 3.14 or later. If your deployment still uses an older Python version, the standard-library module is not available.

Compress Data in Memory

Use zstd.compress() when you already have a bytes-like object and want a compressed bytes result.

Example:

from compression import zstd

message = (
    "Python compression example. " * 20
).encode("utf-8")

# Compress the bytes in one operation.
compressed = zstd.compress(message)

print("Original bytes:", len(message))
print("Compressed bytes:", len(compressed))

The exact compressed size can vary with the data and compression settings, but the result is a bytes object containing Zstandard-compressed data.

Decompress Data

Use zstd.decompress() to restore data produced by the compatible Zstandard format.

from compression import zstd

data = b"Backup data " * 30

compressed = zstd.compress(data)

# Restore the original bytes.
restored = zstd.decompress(compressed)

print(restored == data)

Output:

True

Choose a Compression Level

The compress() function accepts a level argument that controls the compression level. Higher levels can spend more CPU time trying to reduce output size, while lower levels can favor speed.

Example:

from compression import zstd

data = b"sensor-reading," * 1000

# Ask for a specific compression level.
compressed = zstd.compress(data, level=5)

print(len(compressed))

Do not assume a higher level is always better for every application. The right level depends on whether storage size, network bandwidth, latency, or CPU time matters most.

Read and Write .zst Files

The module provides zstd.open() and the ZstdFile class for file-based workflows. These APIs let you work with compressed files using patterns similar to other Python compression modules.

from compression import zstd

content = b"Daily report
" * 100

# Write compressed bytes to a .zst file.
with zstd.open("report.txt.zst", "wb") as file:
    file.write(content)

# Read and decompress the file.
with zstd.open("report.txt.zst", "rb") as file:
    restored = file.read()

print(restored == content)

One-Shot vs Incremental Compression

The simple compress() and decompress() functions are convenient when the complete data fits comfortably in memory. For larger streams or advanced workflows, the module also provides compressor and decompressor classes that can process data incrementally.

Use Zstandard with Archives

Python 3.14 also extends standard-library archive support so Zstandard can be used in places such as tarfile, zipfile, and shutil workflows where supported by those APIs.

This can make zstd useful for backups, package creation, data exchange, cached assets, and large generated files without requiring a separate compression library.

Handle Bytes Correctly

Compression works with binary data. Text must therefore be encoded before compression and decoded after decompression when you want a normal string again.

Example:

from compression import zstd

text = "नमस्ते from Python"

# Text becomes bytes before compression.
compressed = zstd.compress(text.encode("utf-8"))

# Decompress bytes, then decode back to text.
restored = zstd.decompress(compressed).decode("utf-8")

print(restored)

Output:

नमस्ते from Python

Common Mistakes

• Running the example on Python 3.13 or earlier: compression.zstd was added in Python 3.14.
• Passing str directly: compression functions expect bytes-like input, so encode text first.
• Assuming compression always makes data smaller: already-compressed or very small data can gain little or even become larger.
• Using one-shot APIs for very large data: incremental or file APIs can reduce peak memory use.

When to Use compression.zstd

• Compress API payloads, logs, backups, or generated data before storage.
• Read and write .zst files using only the standard library.
• Reduce transfer size when both systems support the Zstandard format.
• Replace a third-party dependency when the standard library provides the functionality you need.

Recommended Practices

• Measure compression ratio and CPU time with realistic data before choosing a level.
• Use file or incremental APIs for large inputs instead of loading everything into memory.
• Store enough metadata to know which compression format a file or payload uses.
• Verify the Python version in deployment environments before adopting the module.

Conclusion

compression.zstd gives Python 3.14 built-in support for the Zstandard format. Use compress() and decompress() for simple in-memory operations, zstd.open() for files, and incremental APIs for larger streams. It is a practical addition when you need fast, modern lossless compression without an extra package.