http://gisaxs.com/index.php?title=Python:Speed&feed=atom&action=history
Python:Speed - Revision history
2024-03-28T19:21:00Z
Revision history for this page on the wiki
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http://gisaxs.com/index.php?title=Python:Speed&diff=5988&oldid=prev
KevinYager: /* Make it faster */
2019-09-08T16:19:44Z
<p><span dir="auto"><span class="autocomment">Make it faster</span></span></p>
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<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td>
<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 16:19, 8 September 2019</td>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#** [http://www.celeryproject.org/ Celery] distributed task queue</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#** [http://www.celeryproject.org/ Celery] distributed task queue</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#** [https://github.com/AustralianSynchrotron/lightflow lightflow] distributed workflow</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#** [https://github.com/AustralianSynchrotron/lightflow lightflow] distributed workflow</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">#** [https://grpc.io/docs/guides/ gRPC] (via [https://pypi.org/project/grpcio/ grpcio] allows services on remote machines to be activated as a simple method call from the client perspective</ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Externals''': Critical code can be written in C/C++, and called as a function within Python. This allows the computational bottleneck to be written in a more specialized and efficient manner.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Externals''': Critical code can be written in C/C++, and called as a function within Python. This allows the computational bottleneck to be written in a more specialized and efficient manner.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* SWIG ([http://www.swig.org/ official site], [https://en.wikipedia.org/wiki/SWIG Wikipedia]) can provide a 50-200&times; speedup.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* SWIG ([http://www.swig.org/ official site], [https://en.wikipedia.org/wiki/SWIG Wikipedia]) can provide a 50-200&times; speedup.</div></td></tr>
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KevinYager
http://gisaxs.com/index.php?title=Python:Speed&diff=5971&oldid=prev
KevinYager: /* Make it faster */
2019-07-25T12:48:29Z
<p><span dir="auto"><span class="autocomment">Make it faster</span></span></p>
<table class="diff diff-contentalign-left" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 12:48, 25 July 2019</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l8" >Line 8:</td>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Re-code''': If code is running slowly, you should identify the bottleneck in the code, and rework it. Typically, using the most appropriate algorithm can improve execution by orders-of-magnitude.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Re-code''': If code is running slowly, you should identify the bottleneck in the code, and rework it. Typically, using the most appropriate algorithm can improve execution by orders-of-magnitude.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Don't worry about it''': Before spending serious effort optimizing code for speed, you should decide if it's even necessary. Does it matter if your code takes a minute or an hour to run? Oftentimes it simply isn't worth optimizing code.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Don't worry about it''': Before spending serious effort optimizing code for speed, you should decide if it's even necessary. Does it matter if your code takes a minute or an hour to run? Oftentimes it simply isn't worth optimizing code.</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># '''JIT''': Just-in-time compilation (JIT) involves compiling Python code as it is needed. The compiling adds a speed penalty as code is first run, but improves overall execution speed if the code iterates over a large dataset. This is very easy to add to existing Python code, so it's nearly "speedup for free".</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">#* Psycho ([http://psyco.sourceforge.net/ official site], [https://en.wikipedia.org/wiki/Psyco Wikipedia]) provides a 2-4&times; speedup (100&times; in some cases). It is only 32-bit.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">#* PyPy ([http://pypy.org/ official site], [https://en.wikipedia.org/wiki/PyPy Wikipedia]) is an alternative Python interpretation, which features JIT. It provides a 2-25&times; speedup. Unfortunately, modules/libraries have to be re-installed/re-compiled into the PyPy environment (separate from the usual Python environment).</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">#* '''Numba''' ([http://numba.pydata.org/ official site]) uses decorators to allow ultra-easy speedups. (CUDA extension also available.)</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">#* Pythran ([https://pythran.readthedocs.io/en/latest/ official site) is an ahead-of-time compiler.</ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Parallel''': Python has several mechanisms for adding simple parallelism to your code. For instance if you're processing hundreds of images in sequence, and have a computer with 16 cores, there's no reason you can't load and process 10 images at a time in parallel.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Parallel''': Python has several mechanisms for adding simple parallelism to your code. For instance if you're processing hundreds of images in sequence, and have a computer with 16 cores, there's no reason you can't load and process 10 images at a time in parallel.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* joblib ([https://joblib.readthedocs.io/en/latest/ official site]) allows simple distribution of tasks.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* joblib ([https://joblib.readthedocs.io/en/latest/ official site]) allows simple distribution of tasks.</div></td></tr>
<tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l19" >Line 19:</td>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Externals''': Critical code can be written in C/C++, and called as a function within Python. This allows the computational bottleneck to be written in a more specialized and efficient manner.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Externals''': Critical code can be written in C/C++, and called as a function within Python. This allows the computational bottleneck to be written in a more specialized and efficient manner.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* SWIG ([http://www.swig.org/ official site], [https://en.wikipedia.org/wiki/SWIG Wikipedia]) can provide a 50-200&times; speedup.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* SWIG ([http://www.swig.org/ official site], [https://en.wikipedia.org/wiki/SWIG Wikipedia]) can provide a 50-200&times; speedup.</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>#* Cython ([http://cython.org/ official site, [https://en.wikipedia.org/wiki/Cython Wikipedia]) is a version of Python with an interface for invoking C/C++ routines.</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>#* <ins class="diffchange diffchange-inline">'''</ins>Cython<ins class="diffchange diffchange-inline">''' </ins>([http://cython.org/ official site, [https://en.wikipedia.org/wiki/Cython Wikipedia]) is a version of Python with an interface for invoking C/C++ routines.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* ctypes ([https://docs.python.org/2/library/ctypes.html documentation]) is a function library that provides C-compatible data types, allowing external libraries to be used in Python.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* ctypes ([https://docs.python.org/2/library/ctypes.html documentation]) is a function library that provides C-compatible data types, allowing external libraries to be used in Python.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* Python/C API ([http://dan.iel.fm/posts/python-c-extensions/ documentation], [http://dan.iel.fm/posts/python-c-extensions/ tutorial]) is available in Python, allowing C extensions to be directly called in Python without much overhead. This 'manual' method lacks the clean wrapping provided by the previously-enumerated methods, but is the most direct method and works well for calling small bits of code.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* Python/C API ([http://dan.iel.fm/posts/python-c-extensions/ documentation], [http://dan.iel.fm/posts/python-c-extensions/ tutorial]) is available in Python, allowing C extensions to be directly called in Python without much overhead. This 'manual' method lacks the clean wrapping provided by the previously-enumerated methods, but is the most direct method and works well for calling small bits of code.</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;"># '''JIT''': Just-in-time compilation (JIT) involves compiling Python code as it is needed. The compiling adds a speed penalty as code is first run, but improves overall execution speed if the code iterates over a large dataset.</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">#* Psycho ([http://psyco.sourceforge.net/ official site], [https://en.wikipedia.org/wiki/Psyco Wikipedia]) provides a 2-4&times; speedup (100&times; in some cases). It is only 32-bit.</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">#* PyPy ([http://pypy.org/ official site], [https://en.wikipedia.org/wiki/PyPy Wikipedia]) is an alternative Python interpretation, which features JIT. It provides a 2-25&times; speedup. Unfortunately, modules/libraries have to be re-installed/re-compiled into the PyPy environment (separate from the usual Python environment).</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">#* Numba ([http://numba.pydata.org/ official site]) uses decorators to allow ultra-easy speedups. (CUDA extension also available.)</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">#* Pythran ([https://pythran.readthedocs.io/en/latest/ official site) is an ahead-of-time compiler.</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Translation''': There are some attempts to automatically translate Python code into optimized lower-level code.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Translation''': There are some attempts to automatically translate Python code into optimized lower-level code.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* shedskin ([http://code.google.com/p/shedskin/ official site 1], [http://shedskin.github.io/ official site 2], [https://en.wikipedia.org/wiki/Shed_Skin Wikipedia]) translates Python into C++, providing a 2-200&times; speedup. Most extensions/libraries are not currently supported. On the other hand, one can isolate some critical code and convert this to an optimized external that is called from conventional Python code.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* shedskin ([http://code.google.com/p/shedskin/ official site 1], [http://shedskin.github.io/ official site 2], [https://en.wikipedia.org/wiki/Shed_Skin Wikipedia]) translates Python into C++, providing a 2-200&times; speedup. Most extensions/libraries are not currently supported. On the other hand, one can isolate some critical code and convert this to an optimized external that is called from conventional Python code.</div></td></tr>
</table>
KevinYager
http://gisaxs.com/index.php?title=Python:Speed&diff=5970&oldid=prev
KevinYager: /* Make it faster */
2019-07-25T12:45:31Z
<p><span dir="auto"><span class="autocomment">Make it faster</span></span></p>
<table class="diff diff-contentalign-left" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td>
<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 12:45, 25 July 2019</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l5" >Line 5:</td>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Make it Pythonic''': Often code runs slowly simply because you are not taking full advantage of Python idioms. Raymond Hettinger has nice notes about "being Pythonic" (e.g. [https://gist.github.com/0x4D31/f0b633548d8e0cfb66ee3bea6a0deff9 notes] or [https://www.youtube.com/watch?feature=player_embedded&v=OSGv2VnC0go video]).</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Make it Pythonic''': Often code runs slowly simply because you are not taking full advantage of Python idioms. Raymond Hettinger has nice notes about "being Pythonic" (e.g. [https://gist.github.com/0x4D31/f0b633548d8e0cfb66ee3bea6a0deff9 notes] or [https://www.youtube.com/watch?feature=player_embedded&v=OSGv2VnC0go video]).</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div># '''Libraries''': Exploiting Python libraries (which are highly optimized and often written in lower-level languages) can greatly improve performance. In particular, using numpy for matrix-style numerical computations (rather than using expensive for-loops or other iterations) can massively speedup computations. <del class="diffchange diffchange-inline">Processing on images </del>can be improved using the Python Image Library (PIL), etc.</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div># '''Libraries''': Exploiting Python libraries (which are highly optimized and often written in lower-level languages) can greatly improve performance. In particular, using <ins class="diffchange diffchange-inline">[https://</ins>numpy<ins class="diffchange diffchange-inline">.org/ numpy] </ins>for matrix-style numerical computations (rather than using expensive for-loops or other iterations) can massively speedup computations. <ins class="diffchange diffchange-inline">[https://www.scipy.org/ Scipy] can be used for optimizations, image processing </ins>can be improved using <ins class="diffchange diffchange-inline">scipy or </ins>the Python Image Library (PIL)<ins class="diffchange diffchange-inline">, image analysis using [https://scikit-image.org/ scikit-image], simple machine-learning using [https://scikit-learn.org/stable/ scikit-learn]</ins>, etc<ins class="diffchange diffchange-inline">. Consider also libraries such as [https://github.com/pydata/numexpr NumExpr] to optimize code</ins>.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Re-code''': If code is running slowly, you should identify the bottleneck in the code, and rework it. Typically, using the most appropriate algorithm can improve execution by orders-of-magnitude.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Re-code''': If code is running slowly, you should identify the bottleneck in the code, and rework it. Typically, using the most appropriate algorithm can improve execution by orders-of-magnitude.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Don't worry about it''': Before spending serious effort optimizing code for speed, you should decide if it's even necessary. Does it matter if your code takes a minute or an hour to run? Oftentimes it simply isn't worth optimizing code.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Don't worry about it''': Before spending serious effort optimizing code for speed, you should decide if it's even necessary. Does it matter if your code takes a minute or an hour to run? Oftentimes it simply isn't worth optimizing code.</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* PyPy ([http://pypy.org/ official site], [https://en.wikipedia.org/wiki/PyPy Wikipedia]) is an alternative Python interpretation, which features JIT. It provides a 2-25&times; speedup. Unfortunately, modules/libraries have to be re-installed/re-compiled into the PyPy environment (separate from the usual Python environment).</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* PyPy ([http://pypy.org/ official site], [https://en.wikipedia.org/wiki/PyPy Wikipedia]) is an alternative Python interpretation, which features JIT. It provides a 2-25&times; speedup. Unfortunately, modules/libraries have to be re-installed/re-compiled into the PyPy environment (separate from the usual Python environment).</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* Numba ([http://numba.pydata.org/ official site]) uses decorators to allow ultra-easy speedups. (CUDA extension also available.)</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* Numba ([http://numba.pydata.org/ official site]) uses decorators to allow ultra-easy speedups. (CUDA extension also available.)</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">#* Pythran ([https://pythran.readthedocs.io/en/latest/ official site) is an ahead-of-time compiler.</ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Translation''': There are some attempts to automatically translate Python code into optimized lower-level code.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Translation''': There are some attempts to automatically translate Python code into optimized lower-level code.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* shedskin ([http://code.google.com/p/shedskin/ official site 1], [http://shedskin.github.io/ official site 2], [https://en.wikipedia.org/wiki/Shed_Skin Wikipedia]) translates Python into C++, providing a 2-200&times; speedup. Most extensions/libraries are not currently supported. On the other hand, one can isolate some critical code and convert this to an optimized external that is called from conventional Python code.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* shedskin ([http://code.google.com/p/shedskin/ official site 1], [http://shedskin.github.io/ official site 2], [https://en.wikipedia.org/wiki/Shed_Skin Wikipedia]) translates Python into C++, providing a 2-200&times; speedup. Most extensions/libraries are not currently supported. On the other hand, one can isolate some critical code and convert this to an optimized external that is called from conventional Python code.</div></td></tr>
</table>
KevinYager
http://gisaxs.com/index.php?title=Python:Speed&diff=5969&oldid=prev
KevinYager at 12:39, 25 July 2019
2019-07-25T12:39:00Z
<p></p>
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<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 12:39, 25 July 2019</td>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div></source></div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div></source></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">==See Also==</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* '''High-performance Python for crystallographic computing'''</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">** A. Boulle and J. Kieffer [http://scripts.iucr.org/cgi-bin/paper?gj5229 High-performance Python for crystallographic computing] ''J. Appl. Cryst.'' '''2019''', 52 [http://gisaxs.com/index.php?title=Python&action=edit&section=4tps://doi.org/10.1107/S1600576719008471 doi: 10.1107/S1600576719008471]</ins></div></td></tr>
</table>
KevinYager
http://gisaxs.com/index.php?title=Python:Speed&diff=5963&oldid=prev
KevinYager at 12:44, 21 June 2019
2019-06-21T12:44:15Z
<p></p>
<table class="diff diff-contentalign-left" data-mw="interface">
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<col class="diff-marker" />
<col class="diff-content" />
<tr class="diff-title" lang="en">
<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td>
<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 12:44, 21 June 2019</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l6" >Line 6:</td>
<td colspan="2" class="diff-lineno">Line 6:</td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Make it Pythonic''': Often code runs slowly simply because you are not taking full advantage of Python idioms. Raymond Hettinger has nice notes about "being Pythonic" (e.g. [https://gist.github.com/0x4D31/f0b633548d8e0cfb66ee3bea6a0deff9 notes] or [https://www.youtube.com/watch?feature=player_embedded&v=OSGv2VnC0go video]).</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Make it Pythonic''': Often code runs slowly simply because you are not taking full advantage of Python idioms. Raymond Hettinger has nice notes about "being Pythonic" (e.g. [https://gist.github.com/0x4D31/f0b633548d8e0cfb66ee3bea6a0deff9 notes] or [https://www.youtube.com/watch?feature=player_embedded&v=OSGv2VnC0go video]).</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Libraries''': Exploiting Python libraries (which are highly optimized and often written in lower-level languages) can greatly improve performance. In particular, using numpy for matrix-style numerical computations (rather than using expensive for-loops or other iterations) can massively speedup computations. Processing on images can be improved using the Python Image Library (PIL), etc.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Libraries''': Exploiting Python libraries (which are highly optimized and often written in lower-level languages) can greatly improve performance. In particular, using numpy for matrix-style numerical computations (rather than using expensive for-loops or other iterations) can massively speedup computations. Processing on images can be improved using the Python Image Library (PIL), etc.</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div># '''Re-code''': <del class="diffchange diffchange-inline">As always</del>, <del class="diffchange diffchange-inline">the first thing to try is to </del>identify the bottleneck in the code, and rework it. Typically, using the most appropriate algorithm can improve execution by orders-of-magnitude.</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div># '''Re-code''': <ins class="diffchange diffchange-inline">If code is running slowly</ins>, <ins class="diffchange diffchange-inline">you should </ins>identify the bottleneck in the code, and rework it. Typically, using the most appropriate algorithm can improve execution by orders-of-magnitude.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Don't worry about it''': Before spending serious effort optimizing code for speed, you should decide if it's even necessary. Does it matter if your code takes a minute or an hour to run? Oftentimes it simply isn't worth optimizing code.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Don't worry about it''': Before spending serious effort optimizing code for speed, you should decide if it's even necessary. Does it matter if your code takes a minute or an hour to run? Oftentimes it simply isn't worth optimizing code.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Parallel''': Python has several mechanisms for adding simple parallelism to your code. For instance if you're processing hundreds of images in sequence, and have a computer with 16 cores, there's no reason you can't load and process 10 images at a time in parallel.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Parallel''': Python has several mechanisms for adding simple parallelism to your code. For instance if you're processing hundreds of images in sequence, and have a computer with 16 cores, there's no reason you can't load and process 10 images at a time in parallel.</div></td></tr>
</table>
KevinYager
http://gisaxs.com/index.php?title=Python:Speed&diff=5962&oldid=prev
KevinYager: /* Make it faster */
2019-06-21T12:43:24Z
<p><span dir="auto"><span class="autocomment">Make it faster</span></span></p>
<table class="diff diff-contentalign-left" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 12:43, 21 June 2019</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l14" >Line 14:</td>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* multiprocessing ([https://docs.python.org/2/library/multiprocessing.html official docs]) allows one to manage processes.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* multiprocessing ([https://docs.python.org/2/library/multiprocessing.html official docs]) allows one to manage processes.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* In some cases you may want to use a more complex workflow system that allows for distributed computation:</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* In some cases you may want to use a more complex workflow system that allows for distributed computation:</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>#** [https://dask.org/ dask]</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>#** [https://dask.org/ dask] <ins class="diffchange diffchange-inline">(and [https://github.com/python-streamz/streamz Streamz]) allow one to construct workflows that use multiple workers</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline">#** [http://www.celeryproject.org/ Celery] distributed task queue</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline">#** [https://github.com/AustralianSynchrotron/lightflow lightflow] distributed workflow</ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Externals''': Critical code can be written in C/C++, and called as a function within Python. This allows the computational bottleneck to be written in a more specialized and efficient manner.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Externals''': Critical code can be written in C/C++, and called as a function within Python. This allows the computational bottleneck to be written in a more specialized and efficient manner.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* SWIG ([http://www.swig.org/ official site], [https://en.wikipedia.org/wiki/SWIG Wikipedia]) can provide a 50-200&times; speedup.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* SWIG ([http://www.swig.org/ official site], [https://en.wikipedia.org/wiki/SWIG Wikipedia]) can provide a 50-200&times; speedup.</div></td></tr>
</table>
KevinYager
http://gisaxs.com/index.php?title=Python:Speed&diff=5961&oldid=prev
KevinYager: /* Make it faster */
2019-06-21T12:39:57Z
<p><span dir="auto"><span class="autocomment">Make it faster</span></span></p>
<table class="diff diff-contentalign-left" data-mw="interface">
<col class="diff-marker" />
<col class="diff-content" />
<col class="diff-marker" />
<col class="diff-content" />
<tr class="diff-title" lang="en">
<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td>
<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 12:39, 21 June 2019</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l11" >Line 11:</td>
<td colspan="2" class="diff-lineno">Line 11:</td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* joblib ([https://joblib.readthedocs.io/en/latest/ official site]) allows simple distribution of tasks.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* joblib ([https://joblib.readthedocs.io/en/latest/ official site]) allows simple distribution of tasks.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* Parallel Python, pp ([https://www.parallelpython.com/ official site]) allows distributed computing.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* Parallel Python, pp ([https://www.parallelpython.com/ official site]) allows distributed computing.</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">#* threading ([https://docs.python.org/2/library/threading.html#module-threading official docs]) allows one to manage threads.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">#* multiprocessing ([https://docs.python.org/2/library/multiprocessing.html official docs]) allows one to manage processes.</ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* In some cases you may want to use a more complex workflow system that allows for distributed computation:</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* In some cases you may want to use a more complex workflow system that allows for distributed computation:</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#** [https://dask.org/ dask]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#** [https://dask.org/ dask]</div></td></tr>
</table>
KevinYager
http://gisaxs.com/index.php?title=Python:Speed&diff=5960&oldid=prev
KevinYager at 12:38, 21 June 2019
2019-06-21T12:38:16Z
<p></p>
<table class="diff diff-contentalign-left" data-mw="interface">
<col class="diff-marker" />
<col class="diff-content" />
<col class="diff-marker" />
<col class="diff-content" />
<tr class="diff-title" lang="en">
<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td>
<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 12:38, 21 June 2019</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l1" >Line 1:</td>
<td colspan="2" class="diff-lineno">Line 1:</td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>[[Python]] is a powerful high-level programming language with a clean syntax. However, the flexibility and generality (e.g. dynamic typing) does have an associated performance cost. There are various strategies to improve the speed of execution of Python code:</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>[[Python]] is a powerful high-level programming language with a clean syntax. However, the flexibility and generality (e.g. dynamic typing) does have an associated performance cost.</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline">==Make it faster==</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>There are various strategies to improve the speed of execution of Python code:</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Make it Pythonic''': Often code runs slowly simply because you are not taking full advantage of Python idioms. Raymond Hettinger has nice notes about "being Pythonic" (e.g. [https://gist.github.com/0x4D31/f0b633548d8e0cfb66ee3bea6a0deff9 notes] or [https://www.youtube.com/watch?feature=player_embedded&v=OSGv2VnC0go video]).</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Make it Pythonic''': Often code runs slowly simply because you are not taking full advantage of Python idioms. Raymond Hettinger has nice notes about "being Pythonic" (e.g. [https://gist.github.com/0x4D31/f0b633548d8e0cfb66ee3bea6a0deff9 notes] or [https://www.youtube.com/watch?feature=player_embedded&v=OSGv2VnC0go video]).</div></td></tr>
</table>
KevinYager
http://gisaxs.com/index.php?title=Python:Speed&diff=5959&oldid=prev
KevinYager at 12:33, 21 June 2019
2019-06-21T12:33:11Z
<p></p>
<table class="diff diff-contentalign-left" data-mw="interface">
<col class="diff-marker" />
<col class="diff-content" />
<col class="diff-marker" />
<col class="diff-content" />
<tr class="diff-title" lang="en">
<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td>
<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 12:33, 21 June 2019</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l1" >Line 1:</td>
<td colspan="2" class="diff-lineno">Line 1:</td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[Python]] is a powerful high-level programming language with a clean syntax. However, the flexibility and generality (e.g. dynamic typing) does have an associated performance cost. There are various strategies to improve the speed of execution of Python code:</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[Python]] is a powerful high-level programming language with a clean syntax. However, the flexibility and generality (e.g. dynamic typing) does have an associated performance cost. There are various strategies to improve the speed of execution of Python code:</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># '''Make it Pythonic''': Often code runs slowly simply because you are not taking full advantage of Python idioms. Raymond Hettinger has nice notes about "being Pythonic" (e.g. [https://gist.github.com/0x4D31/f0b633548d8e0cfb66ee3bea6a0deff9 notes] or [https://www.youtube.com/watch?feature=player_embedded&v=OSGv2VnC0go video]).</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># '''Libraries''': Exploiting Python libraries (which are highly optimized and often written in lower-level languages) can greatly improve performance. In particular, using numpy for matrix-style numerical computations (rather than using expensive for-loops or other iterations) can massively speedup computations. Processing on images can be improved using the Python Image Library (PIL), etc.</ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Re-code''': As always, the first thing to try is to identify the bottleneck in the code, and rework it. Typically, using the most appropriate algorithm can improve execution by orders-of-magnitude.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Re-code''': As always, the first thing to try is to identify the bottleneck in the code, and rework it. Typically, using the most appropriate algorithm can improve execution by orders-of-magnitude.</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div># '''<del class="diffchange diffchange-inline">Libraries</del>''': <del class="diffchange diffchange-inline">Exploiting </del>Python <del class="diffchange diffchange-inline">libraries (which are highly optimized </del>and <del class="diffchange diffchange-inline">often written </del>in <del class="diffchange diffchange-inline">lower-level languages) can greatly improve performance</del>. <del class="diffchange diffchange-inline">In particular, using numpy for matrix-style numerical computations </del>(<del class="diffchange diffchange-inline">rather than using expensive for-loops or other iterations</del>) <del class="diffchange diffchange-inline">can massively speedup computations</del>. <del class="diffchange diffchange-inline">Processing on images can be improved using the </del>Python <del class="diffchange diffchange-inline">Image Library </del>(<del class="diffchange diffchange-inline">PIL</del>)<del class="diffchange diffchange-inline">, etc</del>.</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div># '''<ins class="diffchange diffchange-inline">Don't worry about it''': Before spending serious effort optimizing code for speed, you should decide if it's even necessary. Does it matter if your code takes a minute or an hour to run? Oftentimes it simply isn't worth optimizing code.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline"># '''Parallel</ins>''': Python <ins class="diffchange diffchange-inline">has several mechanisms for adding simple parallelism to your code. For instance if you're processing hundreds of images in sequence, and have a computer with 16 cores, there's no reason you can't load </ins>and <ins class="diffchange diffchange-inline">process 10 images at a time </ins>in <ins class="diffchange diffchange-inline">parallel</ins>.</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline">#* joblib </ins>(<ins class="diffchange diffchange-inline">[https://joblib.readthedocs.io/en/latest/ official site]</ins>) <ins class="diffchange diffchange-inline">allows simple distribution of tasks</ins>.</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline">#* Parallel </ins>Python<ins class="diffchange diffchange-inline">, pp </ins>(<ins class="diffchange diffchange-inline">[https://www.parallelpython.com/ official site]</ins>) <ins class="diffchange diffchange-inline">allows distributed computing.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline">#* In some cases you may want to use a more complex workflow system that allows for distributed computation:</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline">#** [https://dask</ins>.<ins class="diffchange diffchange-inline">org/ dask]</ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Externals''': Critical code can be written in C/C++, and called as a function within Python. This allows the computational bottleneck to be written in a more specialized and efficient manner.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># '''Externals''': Critical code can be written in C/C++, and called as a function within Python. This allows the computational bottleneck to be written in a more specialized and efficient manner.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* SWIG ([http://www.swig.org/ official site], [https://en.wikipedia.org/wiki/SWIG Wikipedia]) can provide a 50-200&times; speedup.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#* SWIG ([http://www.swig.org/ official site], [https://en.wikipedia.org/wiki/SWIG Wikipedia]) can provide a 50-200&times; speedup.</div></td></tr>
</table>
KevinYager
http://gisaxs.com/index.php?title=Python:Speed&diff=5654&oldid=prev
Nsls2user at 20:20, 6 January 2017
2017-01-06T20:20:59Z
<p></p>
<table class="diff diff-contentalign-left" data-mw="interface">
<col class="diff-marker" />
<col class="diff-content" />
<col class="diff-marker" />
<col class="diff-content" />
<tr class="diff-title" lang="en">
<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td>
<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 20:20, 6 January 2017</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l63" >Line 63:</td>
<td colspan="2" class="diff-lineno">Line 63:</td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>print("Slow method timing: {} seconds".format(totslow))</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>print("Slow method timing: {} seconds".format(totslow))</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>print("Fast method timing: {} seconds".format(totfast))</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>print("Fast method timing: {} seconds".format(totfast))</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></source></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">==Numba==</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Using [http://numba.pydata.org/ numba] is extremely easy:</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"><source lang="python"></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">from numba import jit</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># jit decorator tells Numba to compile this function.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># The argument types will be inferred by Numba when function is called.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">@jit</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">def func(x):</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">    y = x*x</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">    return y</ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div></source></div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div></source></div></td></tr>
</table>
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