StringZilla 🦖

StringZilla is the Godzilla of string libraries, splitting, sorting, and shuffling large textual datasets faster than you can say "Tokyo Tower" 😅

• Python docs
• C docs
• JavaScript docs.
• Rust docs.

Performance

StringZilla uses a heuristic so simple it's almost stupid... but it works. It matches the first few letters of words with hyper-scalar code to achieve memcpy speeds. The implementation fits into a single C 99 header file and uses different SIMD flavors and SWAR on older platforms. So if you're haunted by open(...).readlines() and str().splitlines() taking forever, this should help 😊

Substring Search

Backend \ Device	IoT	Laptop	Server
Speed Comparison 🐇
Python for loop	4 MB/s	14 MB/s	11 MB/s
C++ for loop	520 MB/s	1.0 GB/s	900 MB/s
C++ string.find	560 MB/s	1.2 GB/s	1.3 GB/s
Scalar StringZilla	2 GB/s	3.3 GB/s	3.5 GB/s
Hyper-Scalar StringZilla	4.3 GB/s	12 GB/s	12.1 GB/s
Efficiency Metrics 📊
CPU Specs	8-core ARM, 0.5 W/core	8-core Intel, 5.6 W/core	22-core Intel, 6.3 W/core
Performance/Core	2.1 - 3.3 GB/s	11 GB/s	10.5 GB/s
Bytes/Joule	4.2 GB/J	2 GB/J	1.6 GB/J

Partition & Sort

Coming soon.

Quick Start: Python 🐍

1️. Install via pip: pip install stringzilla
2. Import classes: from stringzilla import Str, File, Strs

Basic Usage

StringZilla offers two mostly interchangeable core classes:

from stringzilla import Str, File

text1 = Str('some-string')
text2 = File('some-file.txt')

The Str is designed to replace long Python str strings and wrap our C-level API. On the other hand, the File memory-maps a file from persistent memory without loading its copy into RAM. The contents of that file would remain immutable, and the mapping can be shared by multiple Python processes simultaneously. A standard dataset pre-processing use case would be to map a sizeable textual dataset like Common Crawl into memory, spawn child processes, and split the job between them.

Basic Operations

• Length: len(text) -> int
• Indexing: text[42] -> str
• Slicing: text[42:46] -> str

Advanced Operations

• 'substring' in text -> bool
• text.contains('substring', start=0, end=9223372036854775807) -> bool
• text.find('substring', start=0, end=9223372036854775807) -> int
• text.count('substring', start=0, end=9223372036854775807, allowoverlap=False) -> int
• text.splitlines(keeplinebreaks=False, separator='\n') -> Strs
• text.split(separator=' ', maxsplit=9223372036854775807, keepseparator=False) -> Strs

Collection-Level Operations

Once split into a Strs object, you can sort, shuffle, and reorganize the slices.

lines: Strs = text.split(separator='\n')
lines.sort()
lines.shuffle(seed=42)

Need copies?

sorted_copy: Strs = lines.sorted()
shuffled_copy: Strs = lines.shuffled(seed=42)

Basic list-like operations are also supported:

lines.append('Pythonic string')
lines.extend(shuffled_copy)

Quick Start: C 🛠️

There is an ABI-stable C 99 interface, in case you have a database, an operating system, or a runtime you want to integrate with StringZilla.

#include "stringzilla.h"

// Initialize your haystack and needle
strzl_haystack_t haystack = {your_text, your_text_length};
strzl_needle_t needle = {your_subtext, your_subtext_length, your_anomaly_offset};

// Perform string-level operations
size_t character_count = strzl_naive_count_char(haystack, 'a');
size_t character_position = strzl_naive_find_char(haystack, 'a');
size_t substring_position = strzl_naive_find_substr(haystack, needle);

// Perform collection level operations
strzl_array_t array = {your_order, your_count, your_get_begin, your_get_length, your_handle};
strzl_sort(&array, &your_config);

Contributing 👾

Future development plans include:

• Replace PyBind11 with CPython.
• Reverse-order operations in Python #12.
• Bindings for JavaScript #25, Java, and Rust.
• Faster string sorting algorithm.
• Splitting CSV rows into columns.
• Splitting with multiple separators at once #29.
• UTF-8 validation.
• Arm SVE backend.

Here's how to set up your dev environment and run some tests.

Development

CPython:

# Clean up and install
rm -rf build && pip install -e . && pytest scripts/test.py -s -x

# Install without dependencies
pip install -e . --no-index --no-deps

NodeJS:

npm install && node javascript/test.js

Benchmarking

To benchmark on some custom file and pattern combinations:

python scripts/bench.py --haystack_path "your file" --needle "your pattern"

To benchmark on synthetic data:

python scripts/bench.py --haystack_pattern "abcd" --haystack_length 1e9 --needle "abce"

Packaging

To validate packaging:

cibuildwheel --platform linux

Compiling C++ Tests

# Install dependencies
brew install libomp llvm

# Compile and run tests
cmake -B ./build_release \
    -DCMAKE_C_COMPILER="/opt/homebrew/opt/llvm/bin/clang" \
    -DCMAKE_CXX_COMPILER="/opt/homebrew/opt/llvm/bin/clang++" \
    -DSTRINGZILLA_USE_OPENMP=1 \
    -DSTRINGZILLA_BUILD_TEST=1 \
    && \
    make -C ./build_release -j && ./build_release/stringzilla_test

License 📜

Feel free to use the project under Apache 2.0 or the Three-clause BSD license at your preference.

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