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Top 5 Python IDEs For Data Science. IDE stands for Integrated Development Environment. It’s a coding tool which allows you to write, test and debug your code in an easier way, as they typically offer code completion or code insight by highlighting, resource management, debugging tools,… And even though the IDE is a strictly defined concept, it’s starting to be redefined as other tools such as notebooks start gaining more and more features that traditionally belong to IDEs. For example, debugging your code is also possible in Jupyter Notebook. You can probably most clearly see this evolution in the results of the Stack Overflow Developer Survey below, which also includes these new tools, next to the traditional IDEs that you might already know; They all fall under the section “development environment”. Because of all the features that IDEs have to offer, they are extremely useful for development: they make your coding more comfortable and this is no different for data science. IDEs Versus Text Editors Isn’t that weird?

Spyder. The IDEs of Python — BeeWare. Install and Configure the Atom Editor for Python. In this post we’ll talk about the Atom editor which is, as they say, A hackable text editor for the 21st Century. It’s a really nice, open source and modern editor, with a broad community that provides different and new packages and functionalities. Have you tried it yet? Here, you’ll learn how to install it and how to configure it to write Python code. Let’s start! First, download Atom from the official webpage. Once installed, if you have a Mac or Windows, you’ll have two commands available: atom and apm.

Edit a Python file and use Atom’s Autocomplete Let’s start by creating a Python file with: This will open the file in Atom, and you’ll see the containing folder with all its contents on the left sidebar. In the new file, if you type de, you’ll see that it suggests if you want to create a new function. If you type the Tab key, you’ll see a template for a new function: Note that you have the fname highlighted. Def product(x,y): return x * y Also notice the blue circle next to the file name. 8 Tools That Show What's on the Horizon for Python. Galvanize recently attended the Dato Data Science Summit in San Francisco, a gathering of more than 1,000 data scientists and researchers from industry and academia to discuss and learn about the most recent advances in data science, applied machine learning, and predictive applications.

Here are eight Python tools that our instructors think data scientists will be using in the coming months and years: SFrame and SGraph One of the biggest announcements out of the Dato Data Science Summit was that SFrame and SGraph will be going open source, available for anyone with a BSD license. SFrame (short for Scaleable Data Frame) is a disk-backed columnar data structure optimized for memory efficiency and performance with a DataFrame like interface.

SGraph has a similar ethos but for representing Graphs efficiently. One of the biggest advantage of these two data structures is that they enable a data scientist to do “out of core” analytics with data on datasets that do not fit in memory. Bokeh Dask. Multivariate Techniques in Python: EcoPy Alpha Launch! I’m announcing the alpha launch of EcoPy: Ecological Data Analysis in Python. EcoPy is a Python module that contains a number of techniques (PCA, CA, CCorA, nMDS, MDS, RDA, etc.) for exploring complex multivariate data. For those of you familiar with R, think of this as the Python equivalent to the ‘vegan‘ package. However, I’m not done! This is the alpha launch, which means you should exercise caution before using this package for research. I’ve stress-tested a couple of simple examples to ensure I get equivalent output in numerous programs, but I haven’t tested it out with real, messy data yet.

There might be broken bits or quirks I don’t know about. For the moment, be sure to verify your results with other software. That said, I need help! Related Cleaning Data and Graphing in R and Python Python has some pretty awesome data-manipulation and graphing capabilities. February 10, 2014 In "R bloggers" Should you teach Python or R for data science? February 2, 2015. Meet Jiphy, the Python-to-JavaScript and JavaScript-to-Python Code Converter. Developer Timothy Crosley has put together a tiny Python module that can go over Python files and convert the code into their analogue JavaScript syntax and vice versa. The module, codenamed Jiphy, is not a fully functional Python-to-JavaScript and JavaScript-to-Python compiler that can take fully working applications and migrate them to another platform. As Mr. Crosley puts it, "Jiphy enables Python programmers to more easily write JavaScript code by allowing them to use more familiar syntax, and even JavaScript developers to more easily write Python code.

" This allows developers familiar with one language syntax more than with the other to write the code in the syntax they have a better grasp of, and then convert it into the other after they're done. 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. Python q | Technical Blog of Igor Gnatenko. InkSlide. InkSlide - quick and easy presentations using Inkscape InkSlide produces slides like this: from simple text input like this: InkSlide: Features ++++++++++++++++++ Features include wrapped top level text and - mulitple - levels - of wrapped bulleted lists with bullets and font information taken from the template file.

Slide specific content like this: which is updated when the template changes. An Inkscape file is used as a template file to define the background, title position and font, fonts and positions for text at different levels of indentation, groups to be cloned and used as bullets, etc. Content specific to a particular slide can also be created in Inkscape, this content merged with the template and text input to make the final slide, so changes to the template after a particular slide is edited in Inkscape are included. Download Copy the text below into a file called ''. Here is an example template. How it works The Template File Required contents: Optional contents: The GUI. Impressive. 0.11.0Author: Martin J. FiedlerLast updated: 2014-12-21 Table Of Contents Description Impressive is a simple presentation program that displays slideshows of image files (JPEG, PNG, TIFF and BMP) or PDF documents.

A somewhat-modern GPU (graphics processing unit) supporting OpenGL 2.0 or OpenGL ES 2.0 and appropriate drivers is required to run Impressive. Installation There are three basic ways to get an Impressive installation on your computer. The easy method: use a pre-built package For Windows systems, a ZIP file with a pre-built version of Impressive and all required external tools can be downloaded from the web site.

Most GNU/Linux distributions offer Impressive as part of their standard package repositories, among them Debian, Ubuntu, Fedora, OpenSUSE and Arch Linux. On Mac OS X, there is a py-impressive package in the MacPorts repositories, but at the time of writing, it's extremely outdated and thus not recommended. Command Line Parameters -f.

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Python and QRCodes | python, qrcodes | via matael. Few days ago, I decided to try to generate QRCodes. This article just shows a possibility using Python. Googling for QRCodes generation I found some websites proposing to generate QRCodes for you. The ZXing Generator and the Kaywa Generator seem really powerful and complete, but I was looking for a way of integring QRCode-generation in an piece of software without requiring an Internet access.

A guy (MarkTraceur) commented my post on reddit, talking about a tool he built : QRustom ! Thanks to him ! With python, you can use pyqrcode but it works using a C/C++ encoder and a Java decoder... I also found the PyQRNative lib that seems to be a rewriting of this javascript generator (pretty sure great things can be done using this JS lib and Node.js). The code (that you can wget here) would need a serious rewriting to become PEP8 compliant and documented but it works (here's a QR containing URL for this post generated using PyQRNative). Just run : $ sudo pip install pil qrcode ERROR_CORRECT_M (default) Might use this. Python JIRA. Microsoft embraces Python, Linux in new big data tools. Continuing its quest to make Microsoft Azure comfy for the non-Windows world, Microsoft just launched a preview of its Hadoop-based cloud tool (HDInsight) that runs on Linux.

It’s also making its Azure ML machine learning service widely available now with new support for Python as well as the already-planned support for the popular R language. Microsoft bought Revolution Analytics, the company behind a commercial version of R, last month. Azure HDInsight is thus “Microsoft’s first fully Linux-based service for big data,” Joseph Sirosh, Microsoft’s corporate VP of machine learning, said in an interview. Microsoft says 20 percent of all VMs running on Azure run Linux. Asked if he sees any open-source oriented developers still wary of using Microsoft’s cloud, Sirosh said the perception of Microsoft as a Windows-only company is fading.

Microsoft CEO Satya Nadella Microsoft. VIPER Python Internet Of Things Arduino Shield And Design Suite (video) Python-to-C++ compiler promises speedier execution. The more popular the language, the more varied its implementations. Python is a classic example, with most of the replacements for its default interpreter written to speed up execution of the language. Among the latest and most intriguing is Nuika. Nuika (open source on GitHub) compiles Python to C++ code, which can then be executed in-place or packaged up as a stand-alone file for redistribution.

Unlike some other replacements for existing Python interpreters, it claims full compatibility with all the language constructs in Python 2.6, 2.7, 3.2, and 3.3. According to the project's lead, Kay Hayen, Nuitka's first milestone -- feature parity with the language -- has already been met. To work its magic, Nuitka requires both a current version of the Python interpreter (2.x or 3.x branch) and a C++ compiler.

Another drawback is the creation of stand-alone executables. Still, what Nuitka can already accomplish is impressive, and Hayen's plans for its future are ambitious. PyCharm Early Preview - PyCharm. Dear colleague, Welcome to the Private Preview Program for PyCharm Educational Edition. Improving PyCharm for you and your students! We at JetBrains are committed to making PyCharm even more suitable for teaching Python and programming. We’re looking into ways to improve and simplify existing PyCharm functionality and implement additional educational features, to make the IDE friendlier and easier to use in educational environments, including classroom use, MOOCs and tutorials to assist both trainers and students.

The new educational functionality and a simpler UI will be available in an additional new - and of course free - PyCharm Educational Edition. (This will not affect PyCharm Professional Edition, which will stay as is.) We need your input! Being at the active development stage of this new edition, we’re gathering information and feedback. We look forward to hearing from you. E-mail: Thank you! Welcome to the tox automation project — tox 1.7.2 documentation. First, install tox with pip install tox or easy_install tox. Then put basic information about your project and the test environments you want your project to run in into a tox.ini file residing right next to your file: # content of: tox.ini , put in same dir as[tox]envlist = py26,py27[testenv]deps=pytest # install pytest in the venvscommands=py.test # or 'nosetests' or ...

You can also try generating a tox.ini file automatically, by running tox-quickstart and then answering a few simple questions. To sdist-package, install and test your project against Python2.6 and Python2.7, just type: and watch things happening (you must have python2.6 and python2.7 installed in your environment otherwise you will see errors). Welcome to Py4J — Py4J. Sublime Text 3 for Python, JavaScript and web developers. Sublime Text is a very powerful programmer’s text editor and popular among web and dynamic language developers (Python, Ruby, JavaScript). The editor is commercial (59 USD), though this is enforced through a nagging dialog only. Plenty of Sublime Text’s power comes from the fact that Sublime has vibrant community-maintained plugin ecosystem. This blog post is revised from an old Sublime Text 2 blog post how to tune your Sublime Text to be a powerful platform.

As the writing of this (March 2014) Sublime Text 3 is in public beta and the plugin development for the older Sublime Text 2 is slowly stalling. 1. Sublime Text does not try to be full-fledged IDE. If you need more heavy tools and you are not well-versed on the command-prompt, you can find PyCharm (Python) and WebStorm (JavaScript) IDEs – both are Java-based. 2. 3. In Sublime Text, extensions and plugins are called packages. Install Sublime Package Control. 4. 4. 4. Install from Package Control: SublimePythonIDE 4. 4. 4. 4. 4. 4. Serge-sans-paille/pythran. IPython founder details road map for interactive computing platform | Data visualization. IPython, for "interactive Python," has been gathering steam as a mechanism for interactive computing and data analysis and visualization.

It features the IPython Notebook, which provides a Web-based computational environment that combines code execution, text, mathematics, plots, and rich media. The open source IPython project was invented by Fernando Perez while at the University of Colorado in 2001, and a formal version 1.0 was released last year. Perez, who is a now a research scientist in the Brain Imaging Center at the University of California, Berkeley, sat down with InfoWorld Editor at Large Paul Krill at the recent Strata conference in Silicon Valley to talk about IPython, including its genesis, applications, and a for its future. InfoWorld: What exactly is IPython and what's the main use of it? Perez: IPython began its life when I was a grad student in physics and I wanted an improved interactive shell over the default interactive Python shell. Enthought Announces the Worldwide Launch of Its Python for Excel Solution. Austin, Texas (PRWEB) February 06, 2014 Enthought, Inc., a leading provider of scientific and analytic software powered by Python, today announced its partnership with PyXLL Ltd. to become the exclusive worldwide distributor of PyXLL, a powerful tool used to create add-ins for Microsoft Excel in the Python programming language.

This new partnership gives PyXLL customers the support of Enthought’s distinguished development team and offers Enthought Canopy customers an integrated solution for deploying to Excel. PyXLL is ideal for those who need to provide Python-based models, algorithms and analyses to end-users in Excel. “I developed PyXLL to make it possible to write add-ins for Excel in Python,” said Tony Roberts, founder and developer of PyXLL. “Using simple decorators, Python code can be instantly exposed to Excel as worksheet functions, menu items or macros. Learn more about Canopy and PyXLL by visiting About Enthought. Python + Microcontrollers = Micropython. Shed Skin - A (restricted) Python-to-C++ Compiler: Shed Skin 0.9.4.

ETE real examples | E.T.E. Building the Perfect Browser Based IDE - Codio. Hottest 'mechanize-python' Answers. Powerful Python IDE PyCharm Community Edition Now Available For Free.