Creating super small docker images.
Numpy. Pytables. Distributed Messaging. Osc. Python Module of the Week - Python Module of the Week. Dbtools — dbtools 0.4.0 documentation. A simple interface to SQLite databases.
Overview This module handles simple interfacing with a SQLite database. Inspired by ipython-sql, dbtools returns pandas DataFrame objects from SELECT queries, and can handle basic forms of other SQL statements (CREATE, INSERT, UPDATE, DELETE, and DROP). The goal is not to replicate the full functionality of SQLAlchemy or really to be used for object-relational mapping at all. This is meant to be used more for scientific data collection (e.g., behavioral experiments) as convenient access to a robust form of storage. Installation The easiest way to get dbtools is with pip: Alternately, you can clone the repository and install from source: git clone email@example.com:jhamrick/dbtools.git cd dbtools python setup.py install There is also a Makefile in the root of the repository which is just a convenience wrapper around setup.py. Examples. Saving Figures From Pyplot - Jessica Hamrick. Well, it has been a while since I’ve posted.
Over the summer I moved to beautiful Berkeley, California to start my PhD in Psychology at Cal. The Demise of for Loops - Jessica Hamrick. I almost exclusively use Python in my research.
I write 3D interactive experiments using Panda3D and I collect, analyze, and visualize my data using NumPy, SciPy, and matplotlib. While I have been using Python for almost 5 years now, I only began using Python for scientific programming when I joined the Computational Cognitive Science Group at MIT. The sort of programming I do these days is very different from the software engineering I used to focus on.
In particular, I almost never use for loops when I am doing any form of serious number crunching. For loops do have applications, but I think they tend to be overused, especially in Python. Welcome to OpenCV-Python Tutorials’s documentation! — OpenCV-Python Tutorials 1 documentation. Scripted Node (Generator) — Sverchok 0.5.0 documentation. Aka Script Node or SN.
(iteration 1) Tutorials.
Debug. Ipython. Serial py. Top 20 Python Machine Learning Open Source Projects. We examine top Python Machine learning open source projects on Github, both in terms of contributors and commits, and identify most popular and most active ones.
We analyze Top 20 Python Machine learning projects on GitHub and find that scikit-Learn, PyLearn2 and NuPic are the most actively contributed projects. Explore these popular projects on Github! Fig. 1: Python Machine learning projects on GitHub, with color corresponding to commits/contributors. Bob, Iepy, Nilearn, and NuPIC have the highest such value. How to Distribute Commercial Python Applications. Most of us in the software business are not in a position to release our source code to the public.
Additionally, Jiphy has also been simplified, so it can be easily integrated into various IDEs as a plugin and made to work with multiple files at once.
Open source physics engines. A physics engine is a simulator used to create a virtual environment that incorporates laws from the physical world.
That virtual environment can include objects with accompanying forces applied to them (such as gravity) in addition to interactions between objects, such as collisions. A physics engine simulates Newtonian physics in a simulated environment and manages those forces and interactions. One of the most advertised applications of a physics engine is in the entertainment and game industry (see Figure 1), where the physics engine provides a real-time simulation of the game environment (including the player and other objects that may be present).
Prior to their use in games, physics engines found a number of applications in the scientific domain, from large-scale simulations of celestial bodies, to weather simulations, all the way down to small-scale simulations to visualize the behavior of nanoparticles and their associated forces. Figure 1. Open source options Box2D Box2D example. 6 Free E-Books on Learning to Program with Python. Python is an increasingly popular language, and it's also a favorite language teaching first time programmers.
We've compiled a list of beginner's books to choose from. Just because they're free doesn't mean they aren't good. Some of the books listed here have been used in courses such as MIT's Introduction to Computer Science and Programming course and University of California, Davis' Basic Concepts of Programming course.