# pycrc32
`pycrc32` is a Python module for SIMD-accelerated CRC32 checksum computation.
Big thanks to [rust-crc32fast](https://github.com/srijs/rust-crc32fast) - this project just provides Python bindings for their Rust implementation.
## Installation
```sh
pip install pycrc32
```
## Usage
```python
from pycrc32 import crc32
data = b"123456789"
print(f"crc32 for {data!r} is {crc32(data)}")
```
### Advanced Checksum Calculation with `Hasher`
For scenarios that require more flexibility, such as processing large amounts of data or computing the checksum in stages, you can use the `Hasher` class:
```python
from pycrc32 import Hasher
# Create a new Hasher instance
hasher = Hasher()
# Update the hasher with data chunks
hasher.update(b"123456")
hasher.update(b"789")
# Finalize the computation and get the checksum
checksum = hasher.finalize()
print(f"Checksum: {checksum}")
# Reset the hasher to compute another checksum
hasher.reset()
hasher.update(b"The quick brown fox jumps over the lazy dog")
new_checksum = hasher.finalize()
print(f"New checksum: {new_checksum}")
```
You can also initialize a `Hasher` with a specific initial CRC32 state:
```python
initial_crc = 12345678
hasher = Hasher.with_initial(initial_crc)
hasher.update(b"additional data")
final_checksum = hasher.finalize()
print(f"Final checksum with initial state: {final_checksum}")
```
To combine checksums from different data blocks without needing to concatenate the data, use the `combine` method:
```python
hasher1 = Hasher()
hasher1.update(b"Data block 1")
checksum1 = hasher1.finalize()
hasher2 = Hasher()
hasher2.update(b"Data block 2")
checksum2 = hasher2.finalize()
# Combine checksums from hasher1 into hasher2
hasher1.combine(hasher2) # Combine the state of hasher2 into hasher1
# The final checksum after combination
combined_checksum = hasher1.finalize()
print(f"Combined checksum: {combined_checksum}")
```
## Speed
The performance of `pycrc32` has been benchmarked on a trusty old Intel i7-8550U using 32MB of random input data. Below is a comparison of the median computation times across different libraries:
| Library | Median Time (s) |
|-----------|-----------------|
| `pycrc32` | 0.002703 |
| `zlib` | 0.019796 |
| `fastcrc` | 0.071426 |
We reach almost 10x performance improvements compared to the `zlib` baseline implementation.
See `scripts/bench.py` for more details.
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"description": "# pycrc32\n\n\n\n\n\n\n`pycrc32` is a Python module for SIMD-accelerated CRC32 checksum computation. \nBig thanks to [rust-crc32fast](https://github.com/srijs/rust-crc32fast) - this project just provides Python bindings for their Rust implementation.\n\n## Installation\n```sh\npip install pycrc32\n```\n\n## Usage\n```python\nfrom pycrc32 import crc32\n\ndata = b\"123456789\"\nprint(f\"crc32 for {data!r} is {crc32(data)}\")\n```\n\n### Advanced Checksum Calculation with `Hasher`\nFor scenarios that require more flexibility, such as processing large amounts of data or computing the checksum in stages, you can use the `Hasher` class:\n```python\nfrom pycrc32 import Hasher\n\n# Create a new Hasher instance\nhasher = Hasher()\n\n# Update the hasher with data chunks\nhasher.update(b\"123456\")\nhasher.update(b\"789\")\n\n# Finalize the computation and get the checksum\nchecksum = hasher.finalize()\nprint(f\"Checksum: {checksum}\")\n\n# Reset the hasher to compute another checksum\nhasher.reset()\nhasher.update(b\"The quick brown fox jumps over the lazy dog\")\nnew_checksum = hasher.finalize()\nprint(f\"New checksum: {new_checksum}\")\n```\n\nYou can also initialize a `Hasher` with a specific initial CRC32 state:\n```python\ninitial_crc = 12345678\nhasher = Hasher.with_initial(initial_crc)\n\nhasher.update(b\"additional data\")\nfinal_checksum = hasher.finalize()\nprint(f\"Final checksum with initial state: {final_checksum}\")\n```\n\nTo combine checksums from different data blocks without needing to concatenate the data, use the `combine` method:\n```python\nhasher1 = Hasher()\nhasher1.update(b\"Data block 1\")\nchecksum1 = hasher1.finalize()\n\nhasher2 = Hasher()\nhasher2.update(b\"Data block 2\")\nchecksum2 = hasher2.finalize()\n\n# Combine checksums from hasher1 into hasher2\nhasher1.combine(hasher2) # Combine the state of hasher2 into hasher1\n\n# The final checksum after combination\ncombined_checksum = hasher1.finalize()\nprint(f\"Combined checksum: {combined_checksum}\")\n```\n\n## Speed\nThe performance of `pycrc32` has been benchmarked on a trusty old Intel i7-8550U using 32MB of random input data. Below is a comparison of the median computation times across different libraries:\n\n| Library | Median Time (s) |\n|-----------|-----------------|\n| `pycrc32` | 0.002703 |\n| `zlib` | 0.019796 |\n| `fastcrc` | 0.071426 |\n\nWe reach almost 10x performance improvements compared to the `zlib` baseline implementation. \nSee `scripts/bench.py` for more details.\n\n",
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