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compression libraries 2
(version: 0)
Comparing performance of:
unzip pako a vs unzip pako b vs zip pako a vs zip pako b vs unzip fflate a vs unzip fflate b vs zip fflate a vs zip fflate b
Created:
5 years ago
by:
Guest
Jump to the latest result
HTML Preparation code:
<script src="https://unpkg.com/fflate"></script> <script src="https://cdnjs.cloudflare.com/ajax/libs/pako/2.0.3/pako.es5.min.js"></script>
Script Preparation code:
var enc = new TextEncoder(); var a = new Uint8Array([...Array(1000000).keys()]); var b = enc.encode('The quick brown fox jumps over the lazy dog') var ca = pako.gzip(a) var cb = pako.gzip(b) console.log(cb)
Tests:
unzip pako a
pako.inflate(ca)
unzip pako b
pako.inflate(cb)
zip pako a
pako.deflate(a)
zip pako b
pako.deflate(b)
unzip fflate a
fflate.decompressSync(ca);
unzip fflate b
fflate.decompressSync(cb);
zip fflate a
fflate.gzipSync(a)
zip fflate b
fflate.gzipSync(b)
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (8)
Previous results
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Test case name
Result
unzip pako a
unzip pako b
zip pako a
zip pako b
unzip fflate a
unzip fflate b
zip fflate a
zip fflate b
Fastest:
N/A
Slowest:
N/A
Latest run results:
No previous run results
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
The provided JSON represents a benchmarking test suite for comparing the performance of two compression libraries: pako and fflate. The test suite consists of eight individual test cases, each measuring the execution time of various operations on input data. **Compression Operations** 1. **Zip**: `pako.deflate(a)` and `fflate.gzipSync(a)`. These operations compress the input data (`a`) using the pako and fflate algorithms, respectively. 2. **Unzip**: `pako.inflate(ca)` and `fflate.decompressSync(ca)`, where `ca` is the compressed output of the corresponding zip operation above. These operations decompress the previously compressed data using the pako and fflate algorithms. **Library Overview** 1. **Pako**: The pako library provides a simple, efficient way to compress and decompress data using the DEFLATE algorithm. It's primarily used for zipping and unzipping files. 2. **Fflate**: Fflate is a high-performance compression library based on the DEFLATE algorithm. It's designed to be fast and efficient while maintaining good compression ratios. **Options Compared** In each test case, two options are compared: 1. **Pako vs. Fflate**: Each test compares the performance of pako with that of fflate for both zip and unzip operations. 2. **Zip vs. Unzip**: Within each library (pako or fflate), a test compares the execution time of zipping data versus unzipping previously compressed data. **Pros and Cons** * **Pako Pros:** * Simpler to use, with fewer dependencies. * Typically more performant than fflate for small to medium-sized inputs. * **Pako Cons:** * May not provide the best compression ratios compared to fflate. * Can be slower for very large inputs. * **Fflate Pros:** * Provides better compression ratios and faster performance for larger inputs. * More flexible than pako, with more options for tuning compression settings. **Other Considerations** 1. **Input Data**: The benchmark tests the performance of each library on a specific input dataset (a large array of numbers) that is sufficient to reveal differences in performance between pako and fflate. 2. **Compression Algorithm**: Both libraries use the DEFLATE algorithm, which provides a good balance between compression ratio and speed. **Alternatives** If you're looking for alternative compression libraries, consider: 1. **Zlib**: A widely used, open-source library that provides a simple way to compress data using the DEFLATE algorithm. 2. **lz-string**: Another lightweight JavaScript library that provides fast compression and decompression algorithms. 3. **Brotli**: An open-source compression format developed by Google, which is designed for web use cases. In conclusion, this benchmark test suite helps compare the performance of two popular JavaScript compression libraries: pako and fflate. By understanding the pros and cons of each library, developers can choose the best tool for their specific needs, whether it's simplicity, performance, or compression ratios.
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