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[The trainer] knows well what scientists need, so his hints are very practical and valuable. The hands-on course [..] covers a wide range of examples and will be very helpful in my daily work. ..
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The Python Summer Course was a very good opportunity to know almost all about Python. ... Highly recommended!!
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Good course. Very competent trainer for this introduction. The course offers wide spectrum of topics and goes into depth were participants need it most.
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Fast Code with the Cython Compiler
Dates for Open Courses
|Leipzig||Fast Code with the Cython Compiler||13.06.2013|
Also available as in-house course.
This course is given by a core developer of the Cython open-source project.
The course targets medium level to experienced Python programmers who want to break through the limits of Python performance. A basic understanding of the C language is helpful but not required.
The Python programming language has been used successfully in a large number of application domains. Even performance critical applications, such as scientific computation frameworks or text processing applications, have been realized using Python in order to benefit from short development cycles and highly maintainable code.
However, the interpreted language also has its weaknesses. Tight algorithms in numerical computations and character processing often suffer from the overhead of object operations in arithmetic expressions or memory copies in string slicing. In high performance applications, the optimizations that can be performed at the language level may not be sufficient.
This is where the Cython programming language shows its strength. Cython is a general purpose programming language that forms a best-of-both-worlds cross between the Python language and the ubiquitous datatypes of the C/C++ language. It comes with an optimising compiler that translates Python code into C code for Python extension modules, and tightly adapts the generated code to the available static type information.
Cython code can be written as high-level Python code and manually optimised in well selected hot-spots by statically declaring data types or calling directly into external code written in C, C++ or compatible languages. This makes the entire range from simple, expressive Python code down to highly optimised, low-level C code available for programming in a single language.
The objective of this course is to get to know the Cython language, and to learn how to use it to speed up Python code by orders of magnitude. You will also learn how to wrap external C libraries to efficiently and comfortably use them from Python.
My first Cython extension
- using pyximport to quickly (re-)build extension modules
- using cython.inline() to compile code at runtime
- building extension modules with distutils
Speeding up Python code with Cython
- fast access to Python's builtin types
- fast looping over Python iterables and C types
- string processing
- fast arithmetic
- incrementally optimizing Cython code
- multi-threading outside of the GIL (Global Interpreter Lock)
Interfacing with external C code
- calling into external C libraries
- building against C libraries
- writing Python wrapper APIs
- calling C functions across extension module boundaries
The participants are encouraged to send in short code examples from their own experience that they would like to see running faster by using Cython. Based on general interest and practicality, one or two of these examples will be examined as a case study. These examples must be available to the teacher at least one week before the course, and must be short but complete executable examples, including sufficient input data for benchmarking. Please be aware that example code that requires a substantial amount of explanation or background knowledge about a specific application domain will not be accepted.
The participants can follow all steps directly on their computers. There are exercises at the end of each unit providing ample opportunity to apply the freshly learned knowledge.
Every participant receives comprehensive printed materials that cover the whole course content as wells a CD with all source codes and used software.
Recommended Module Combinations
You should have intermediate Python experience or attend the course Python for Programmers before. You might be interested in the modules Advanced Python, Optimizing of Python Programs or Python Extensions with Other Languages as well. Also, have a look at the Python Power Course, eight days of Python courses in a row.
The Python Academy is sponsor of EuroPython 2013.
The Python Academy is sponsor of Python BarCamp Köln.
The Python Academy is sponsor of PyCon US 2013.
The Python Academy is sponsor of EuroSciPy 2013.
The Python Academy is sponsor of PyConDE 2012.
The Python Academy is sponsor of PyConPL 2012.
The next open cousers
Python Academy sponsors EuroPython conference 2013
Python Academy sponsors Python BarCamp in Cologne
Python Academy sponsors EuroSciPy conference 2013
Next Meeting of Leipzig Python User Group, May 14, 2013
Einstieg in Django (German), June 3 - 5, 2013
Django für Fortgeschrittene (German), June 6 - 8, 2013
Python for Scientists and Engineers, June 10 - 12, 2013
Professional Testing with pytest and tox, June 24 - 26, 2013
Introduction to Django, November 11 - 13, 2013
Advanced Django, November 14 - 16, 2013
Python Academy sponsors PyCon US conference 2013
Python Academy founder receives PSF Community Service Award