| Version 16 (modified by zooko, 14 years ago) (diff) |
|---|
StringChain
Sometimes you want to accumulate data from some source while at the same time processing the data that arrived first. The naïve way to do it in Python is like this:
def __init__(self):
self.accum = '' # Will hold all unprocessed bytes
def add_data(self, some_more_data):
# some_more_data is a string
self.accum += some_more_data
def process_some(self, how_much):
some = self.accum[:how_much]
del self.accum[:how_much]
This works fine as long as the total amount of bytes accumulated and the number of separate add_data() events stay small, but it has O(N2) behavior and has bad performance if those numbers get large. Here are some benchmarks generated by running python -OOu -c 'from stringchain.bench import bench; bench.quick_bench()' as instructed by the README.txt file.
The N: in the left-hand column is how many bytes were in the test dataset. The results are all in ns/op: nanoseconds per byte. "Stringy" means the string-based idiom sketched above and "StringChain" means using the StringChain class. "StringIOy" means another implementation using the cStringIO class.
$ python -OOu -c 'from stringchain.bench import bench; bench.slow_bench()' impl: StringChain task: _accumulate_then_one_gulp N: 10000, ns/op: best: 2.79, 2th-best: 3.39, ave: 3.90, 2th-worst: 4.70, worst: 4.82 (of 5) N: 50000, ns/op: best: 2.76, 2th-best: 2.78, ave: 2.95, 2th-worst: 2.94, worst: 3.36 (of 5) N: 100000, ns/op: best: 2.33, 2th-best: 2.34, ave: 2.40, 2th-worst: 2.45, worst: 2.54 (of 5) N: 500000, ns/op: best: 2.03, 2th-best: 2.10, ave: 2.26, 2th-worst: 2.28, worst: 2.70 (of 5) N: 1000000, ns/op: best: 1.98, 2th-best: 2.01, ave: 2.30, 2th-worst: 2.45, worst: 2.68 (of 5) N: 5000000, ns/op: best: 2.11, 2th-best: 2.14, ave: 2.18, 2th-worst: 2.20, worst: 2.25 (of 5) task: _many_gulps_str N: 10000, ns/op: best: 5.20, 2th-best: 5.51, ave: 6.60, 2th-worst: 6.10, worst: 10.61 (of 5) N: 50000, ns/op: best: 3.24, 2th-best: 3.24, ave: 3.42, 2th-worst: 3.42, worst: 3.88 (of 5) N: 100000, ns/op: best: 2.87, 2th-best: 2.88, ave: 2.96, 2th-worst: 2.93, worst: 3.22 (of 5) N: 500000, ns/op: best: 2.80, 2th-best: 2.84, ave: 2.90, 2th-worst: 2.95, worst: 3.00 (of 5) N: 1000000, ns/op: best: 2.70, 2th-best: 2.70, ave: 2.77, 2th-worst: 2.84, worst: 2.88 (of 5) N: 5000000, ns/op: best: 2.70, 2th-best: 2.71, ave: 2.72, 2th-worst: 2.74, worst: 2.76 (of 5) task: _alternate_str N: 10000, ns/op: best: 6.79, 2th-best: 7.10, ave: 7.84, 2th-worst: 8.61, worst: 8.80 (of 5) N: 50000, ns/op: best: 4.74, 2th-best: 4.78, ave: 4.83, 2th-worst: 4.88, worst: 4.90 (of 5) N: 100000, ns/op: best: 4.34, 2th-best: 4.35, ave: 4.50, 2th-worst: 4.53, worst: 4.78 (of 5) N: 500000, ns/op: best: 3.98, 2th-best: 4.12, ave: 4.25, 2th-worst: 4.36, worst: 4.50 (of 5) N: 1000000, ns/op: best: 3.96, 2th-best: 4.00, ave: 4.07, 2th-worst: 4.02, worst: 4.36 (of 5) N: 5000000, ns/op: best: 3.96, 2th-best: 3.97, ave: 4.07, 2th-worst: 4.18, worst: 4.19 (of 5) impl: StringIOy task: _accumulate_then_one_gulp N: 10000, ns/op: best: 4.10, 2th-best: 4.29, ave: 4.84, 2th-worst: 5.29, worst: 5.51 (of 5) N: 50000, ns/op: best: 5.06, 2th-best: 5.60, ave: 5.75, 2th-worst: 6.14, worst: 6.32 (of 5) N: 100000, ns/op: best: 4.51, 2th-best: 4.52, ave: 4.60, 2th-worst: 4.67, worst: 4.69 (of 5) N: 500000, ns/op: best: 3.80, 2th-best: 3.90, ave: 4.70, 2th-worst: 5.10, worst: 6.71 (of 5) N: 1000000, ns/op: best: 4.19, 2th-best: 4.29, ave: 4.69, 2th-worst: 5.08, worst: 5.49 (of 5) N: 5000000, ns/op: best: 5.27, 2th-best: 5.30, ave: 5.57, 2th-worst: 5.89, worst: 6.00 (of 5) task: _many_gulps_str N: 10000, ns/op: best: 4.70, 2th-best: 5.51, ave: 5.70, 2th-worst: 5.70, worst: 6.91 (of 5) N: 50000, ns/op: best: 24.28, 2th-best: 24.34, ave: 27.87, 2th-worst: 25.36, worst: 40.90 (of 5) N: 100000, ns/op: best: 38.64, 2th-best: 38.84, ave: 39.03, 2th-worst: 39.22, worst: 39.38 (of 5) N: 500000, ns/op: best: 158.61, 2th-best: 159.18, ave: 162.47, 2th-worst: 165.73, worst: 168.40 (of 5) N: 1000000, ns/op: best: 455.90, 2th-best: 459.57, ave: 471.79, 2th-worst: 488.72, worst: 490.74 (of 5) N: 5000000, ns/op: best: 2730.39, 2th-best: 2734.04, ave: 2771.03, 2th-worst: 2734.04, worst: 2848.67 (of 3) task: _alternate_str N: 10000, ns/op: best: 6.99, 2th-best: 7.08, ave: 8.10, 2th-worst: 7.70, worst: 11.11 (of 5) N: 50000, ns/op: best: 8.34, 2th-best: 8.34, ave: 8.52, 2th-worst: 8.38, worst: 9.18 (of 5) N: 100000, ns/op: best: 22.37, 2th-best: 22.68, ave: 22.82, 2th-worst: 22.90, worst: 23.44 (of 5) N: 500000, ns/op: best: 74.92, 2th-best: 75.96, ave: 76.61, 2th-worst: 76.87, worst: 78.45 (of 5) N: 1000000, ns/op: best: 135.24, 2th-best: 136.14, ave: 139.87, 2th-worst: 137.46, worst: 153.85 (of 5) N: 5000000, ns/op: best: 1000.30, 2th-best: 1003.59, ave: 1076.12, 2th-worst: 1003.59, worst: 1224.47 (of 3) impl: Stringy task: _accumulate_then_one_gulp N: 10000, ns/op: best: 2.38, 2th-best: 2.69, ave: 3.01, 2th-worst: 3.00, worst: 4.20 (of 5) N: 50000, ns/op: best: 15.86, 2th-best: 16.16, ave: 18.65, 2th-worst: 16.34, worst: 28.66 (of 5) N: 100000, ns/op: best: 26.60, 2th-best: 26.80, ave: 30.51, 2th-worst: 34.00, worst: 35.07 (of 5) N: 500000, ns/op: best: 102.15, 2th-best: 102.16, ave: 103.20, 2th-worst: 103.29, worst: 105.36 (of 5) N: 1000000, ns/op: best: 266.58, 2th-best: 266.73, ave: 280.54, 2th-worst: 286.67, worst: 311.59 (of 5) N: 5000000, ns/op: best: 1543.46, 2th-best: 1554.51, ave: 1553.37, 2th-worst: 1554.51, worst: 1562.16 (of 3) task: _many_gulps_str N: 10000, ns/op: best: 2.60, 2th-best: 2.91, ave: 3.15, 2th-worst: 3.50, worst: 3.72 (of 5) N: 50000, ns/op: best: 15.06, 2th-best: 15.08, ave: 15.34, 2th-worst: 15.60, worst: 15.86 (of 5) N: 100000, ns/op: best: 24.20, 2th-best: 24.21, ave: 25.17, 2th-worst: 24.88, worst: 27.80 (of 5) N: 500000, ns/op: best: 98.93, 2th-best: 101.46, ave: 101.85, 2th-worst: 102.31, worst: 105.05 (of 5) N: 1000000, ns/op: best: 264.17, 2th-best: 266.87, ave: 268.33, 2th-worst: 270.90, worst: 272.28 (of 5) N: 5000000, ns/op: best: 1556.56, 1th-best: 1556.56, ave: 1586.65, 1th-worst: 1616.73, worst: 1616.73 (of 2) task: _alternate_str N: 10000, ns/op: best: 4.29, 2th-best: 4.70, ave: 5.48, 2th-worst: 6.01, worst: 6.39 (of 5) N: 50000, ns/op: best: 5.16, 2th-best: 5.20, ave: 5.38, 2th-worst: 5.44, worst: 5.68 (of 5) N: 100000, ns/op: best: 20.53, 2th-best: 20.65, ave: 20.77, 2th-worst: 20.71, worst: 21.30 (of 5) N: 500000, ns/op: best: 81.43, 2th-best: 81.60, ave: 82.35, 2th-worst: 82.54, worst: 84.52 (of 5) N: 1000000, ns/op: best: 143.76, 2th-best: 146.12, ave: 146.30, 2th-worst: 146.19, worst: 149.30 (of 5) N: 5000000, ns/op: best: 917.51, 2th-best: 925.97, ave: 923.90, 2th-worst: 925.97, worst: 928.21 (of 3)
The naïve approach is slower than the StringChain class, and the bigger the dataset the slower it goes. The StringChain class is fast and also it is scalable (with regard to these benchmarks at least...).
Okay how do you use it? It is very simple -- see stringchain/stringchain.py and let me know if that interface doesn't fit your use case.
You can get the package from http://pypi.python.org/pypi/stringchain or with darcs get http://tahoe-lafs.org/source/stringchain/trunk.
It has unit tests. It is in pure Python (it uses collections.deque and string).
LICENCE
You may use this package under the GNU General Public License, version 2 or, at your option, any later version. You may use this package under the Transitive Grace Period Public Licence, version 1.0, or at your option, any later version. (You may choose to use this package under the terms of either licence, at your option.) See the file COPYING.GPL for the terms of the GNU General Public License, version 2. See the file COPYING.TGPPL.html for the terms of the Transitive Grace Period Public Licence, version 1.0.
Starting Points
- TracGuide -- Built-in Documentation
- The Trac project -- Trac Open Source Project
- Trac FAQ -- Frequently Asked Questions
- TracSupport -- Trac Support
For a complete list of local wiki pages, see TitleIndex.
