How to: Use Python to Solve Optimization Problems via reddit.com. Sleepyti.me bedtime calculator. Python for Informatics: Exploring Information, an open textbook. Charles is currently a Clinical Assistant Professor and teaches in the School of Information at the University of Michigan. Charles also works with the IMS Global Learning Consortium as the IMS Affiliate Coordinator. Previously he was the Executive Director of the Sakai Foundation and the Chief Architect of the Sakai Project. Charles is the author of the book, "Using Google App Engine" from O'Reilly and Associates. He also wrote the O'Reilly book on High Performance Computing. European Supergrid Slowly Coming into Focus.
Color Scheme Designer 3. YQafj.png (773×938) Scratch. PyBrain. 10 Reasons Python Rocks for Research — Hoyt Koepke. The following is an account of my own experience with Python.
Because that experience has been so positive, it is an unabashed attempt to promote the use of Python for general scientific research and development. About four years ago, I dropped MATLAB in favor of Python as my primary language for coding research projects. 3: Qt Designer Manual. Home · All Classes · Main Classes · Grouped Classes · Modules · Functions [Next: Getting Started with Qt Designer ] Qt Designer Manual.
1. An Introduction to Distutils — Python v2.7 documentation. This document covers using the Distutils to distribute your Python modules, concentrating on the role of developer/distributor: if you’re looking for information on installing Python modules, you should refer to the Installing Python Modules chapter. 1.1.
Concepts & Terminology Using the Distutils is quite simple, both for module developers and for users/administrators installing third-party modules. As a developer, your responsibilities (apart from writing solid, well-documented and well-tested code, of course!) Are: 10 Reasons Python Rocks for Research — Hoyt Koepke. The following is an account of my own experience with Python.
Because that experience has been so positive, it is an unabashed attempt to promote the use of Python for general scientific research and development. About four years ago, I dropped MATLAB in favor of Python as my primary language for coding research projects. This article is a personal account of how rewarding I have found that experience. From python import podcast. PySnippet. Flask (A Python Microframework) Using the Cython Compiler to write fast Python code. Passionate Python developer since 2002after Basic, Logo, Pascal, Prolog, Scheme, Java, C, ...CS studies in Germany, Ireland, FrancePhD in distributed systems in 2007Language design for self-organising systemsDarmstadt University of Technologies, GermanyCurrent occupations:Employed by Senacor Technologies AG, GermanyIT transformations, SOA design, Java-Development, ...»lxml« OpenSource XML toolkit for Part 1: Intro to CythonPart 2: Building Cython modulesPart 3: Writing fast codePart 4: Talking to other extensions Cython is the missing linkbetween the simplicity of Pythonand the speed of C / C++ / Fortran.
Cython is the missing linkbetween the simplicity of Pythonand the speed of C / C++ / Fortran. Package Index : Theano 0.3.0. Optimizing compiler for evaluating mathematical expressions on CPUs and GPUs.
Latest Version: 0.6.0 Theano is a Python library that allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays. It is built on top of NumPy. Theano features: tight integration with NumPy: a similar interface to NumPy's. numpy.ndarrays are also used internally in Theano-compiled functions.transparent use of a GPU: perform data-intensive computations up to 140x faster than on a CPU (support for float32 only).efficient symbolic differentiation: Theano can compute derivatives for functions of one or many inputs.speed and stability optimizations: avoid nasty bugs when computing expressions such as log(1+ exp(x) ) for large values of x.dynamic C code generation: evaluate expressions faster.extensive unit-testing and self-verification: includes tools for detecting and diagnosing bugs and/or potential problems.
John Anderson ( sontek ) - Debugging Python with pdb. Being a great debugger is almost as important as being great at writing the software.
I think I spend just as much time debugging programs as I do writing them. pdb (python debugger) is a very powerful tool for interactively debugging the state of your application and inspecting portions of your code. For the rest of this post we are going to be debugging a file called fib.py with the following code: # fib.pydef main(): low = 0 high = 1 for i in range(10): print high new_high = get_new_high(low, high) low = high high = new_high def get_new_high(low, high): return low + high if __name__ == '__main__': main() Features of the Standard Library.