Coding

At PyCon Indonesia, I spoke about a project we worked on with the World Mosquito Program. The World Mosquito Program (WMP) modifies mosquitoes with a bacteria – Wolbachia. This reduces their ability to carry deadly viruses. (It makes me perversely happy that we’re infecting mosquitoes now 😉.) Modifying mosquitoes is an expensive process. With a limited set of “good mosquitoes”, it is critical to find the best release points that will help them replicate rapidly. ...

Minecraft lets you connect to a websocket server when you’re in a game. The server can receive and send any commands. This lets you build a bot that you can … (well, I don’t know what it can do, let’s explore.) Minecraft has commands you can type on a chat window. For example, type / to start a command and type setblock ~1 ~0 ~0 grass changes the block 1 north of you into grass. (~ means relative to you. Coordinates are specified as X, Y and Z.) ...

One problem I’ve had in Markdown is rendering a content in columns. On Bootstrap, the markup would look like this: <div class="row"> <div class="col">...</div> <div class="col">...</div> </div> How do we get that into Markdown without writing HTML? On Python, the attribute lists extension lets you add a class. For example: This is some content {: .row} … renders <p class="row">This is some content</p>. But I can’t do that to multiple paragraphs. Nor can I next content, i.e. add a .col inside the .row. ...

With Office 365, PowerPoint supports SVG editing. This is really powerful. It means you can draw in PowerPoint and render it on the web – including as interactive or animated visuals. For example, the SVG in this simulator was created just with PowerPoint. The process is simple. Draw anything. Select any shapes and right-click. Select Save As Picture… and choose SVG. For example, you can use PowerPoint to create Smart Art, export it as SVG, and embed it into a page. See this example on CodePen. ...

Given the blazing speed of Node.js these days, I expected HTML parsing to be faster on Node than on Python. So I compared lxml with htmlparser2 – the fastest libraries on Python and JS in parsing the reddit home page (~700KB). lxml took ~8.6 milliseconds htmlparser2 took ~14.5 milliseconds Looks like lxml is much faster. I’m likely to stick around with Python for pure HTML parsing (without JavaScript) for a while longer. In [1]: from lxml.html import parse In [2]: %timeit tree = parse('reddit.html') 8.69 ms ± 190 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) const { Parser } = require("htmlparser2"); const { DomHandler } = require("domhandler"); const fs = require("fs"); const html = fs.readFileSync("reddit.html"); const handler = new DomHandler(function(error, dom) {}); const start = +new Date(); for (var i = 0; i < 100; i++) { const parser = new Parser(); parser.write(html); parser.end(); } const end = +new Date(); console.log((end - start) / 100); Note: If I run the htmlparser2 code 100 times instead of 10, it only takes 7ms per loop. The more the number of loops, the faster it parses. I guess Node.js optimizes repeated loops. But I’m only interested in the first iteration, since I’ll be parsing files only once.

It’s easy to convert addresses into latitudes and longitudes into addresses in Excel. Here’s the Github project with a downloadable Excel file. This is via Visual Basic code for a GoogleGeocode function that geocodes addresses. Function GoogleGeocode(address As String) As String Dim xDoc As New MSXML2.DOMDocument xDoc.async = False xDoc.Load ("http://maps.googleapis.com/maps/api/geocode/" + _ "xml?address=" + address + "&sensor=false") If xDoc.parseError.ErrorCode <> 0 Then GoogleGeocode = xDoc.parseError.reason Else xDoc.setProperty "SelectionLanguage", "XPath" lat = xDoc.SelectSingleNode("//lat").Text lng = xDoc.SelectSingleNode("//lng").Text GoogleGeocode = lat & "," & lng End If End Function Comments Ryan 8 Jun 2015 9:28 pm: I find this isn’t working and says, Compile Error; User defined type not defined xDoc As New MSXML2.DOMDocument what do I change to fix it? Thank you Richie Lionell 27 Jul 2016 6:40 am: Ryan, Inside the VBE, Go to Tools -> References, then Select Microsoft XML, v6.0 . If that doesn’t work unselect that and select Microsoft XML, v3.0

Github offers Github Pages that let you host web pages on Github. You create these by adding a branch to git called gh-pages, and this is often in addition to the default branch master. I just needed the gh-pages branch. So thanks to YJL, here’s the simplest way to do it. Create the repositoryon github. Create your local repository and git commitinto it. Type git push -u origin master:gh-pages In .git/config, under the [remote "origin"] section, add push = +refs/heads/master:refs/heads/gh-pages The magic is the last :gh-pages.

I just scraped the scientific packages on pypi. Here are the top 50 by downloads. Name Description Size Downloads numpy NumPy: array processing for numbers, strings, records, and objects. 2000000 133076 scipy SciPy: Scientific Library for Python 7000000 33990 pygraphviz Python interface to Graphviz 99000 22828 geopy Python Geocoding Toolbox 32000 18617 googlemaps Easy geocoding, reverse geocoding, driving directions, and local search in Python via Google. 69000 15135 Rtree R-Tree spatial index for Python GIS 495000 14370 nltk Natural Language Toolkit 1000000 12844 Shapely Geometric objects, predicates, and operations 93000 12635 pyutilib.component.doc Documentation for the PyUtilib Component Architecture. 372000 10181 geojson Encoder/decoder for simple GIS features 12000 9407 GDAL GDAL: Geospatial Data Abstraction Library 410000 8957 scikits.audiolab A python module to make noise from numpy arrays 1000000 8856 pupynere NetCDF file reader and writer. 16000 8809 scikits.statsmodels Statistical computations and models for use with SciPy 3000000 8761 munkres munkres algorithm for the Assignment Problem 42000 8409 scikit-learn A set of python modules for machine learning and data mining 2000000 7735 networkx Python package for creating and manipulating graphs and networks 1009000 7652 pyephem Scientific-grade astronomy routines 927000 7644 PyBrain PyBrain is the swiss army knife for neural networking. 255000 7313 scikits.learn A set of python modules for machine learning and data mining 1000000 7088 obspy.seisan SEISAN read support for ObsPy. 3000000 6990 obspy.wav WAV(audio) read and write support for ObsPy. 241000 6985 obspy.seishub SeisHub database client for ObsPy. 237000 6941 obspy.sh Q and ASC (Seismic Handler) read and write support for ObsPy. 285000 6926 crcmod CRC Generator 128000 6714 obspy.fissures DHI/Fissures request client for ObsPy. 1000000 6339 stsci.distutils distutils/packaging-related utilities used by some of STScI’s packages 25000 6215 pyopencl Python wrapper for OpenCL 1000000 6124 Kivy A software library for rapid development of hardware-accelerated multitouch applications. 11000000 5879 speech A clean interface to Windows speech recognition and text-to-speech capabilities. 17000 5809 patsy A Python package for describing statistical models and for building design matrices. 276000 5517 periodictable Extensible periodic table of the elements 775000 5498 pymorphy Morphological analyzer (POS tagger + inflection engine) for Russian and English (+perhaps German) languages. 70000 5174 imposm.parser Fast and easy OpenStreetMap XML/PBF parser. 31000 4940 hcluster A hierarchical clustering package for Scipy. 442000 4761 obspy.core ObsPy - a Python framework for seismological observatories. 487000 4608 Pyevolve A complete python genetic algorithm framework 99000 4509 scikits.ann Approximate Nearest Neighbor library wrapper for Numpy 82000 4368 obspy.imaging Plotting routines for ObsPy. 324000 4356 obspy.xseed Dataless SEED, RESP and XML-SEED read and write support for ObsPy. 2000000 4331 obspy.sac SAC read and write support for ObsPy. 306000 4319 obspy.arclink ArcLink/WebDC client for ObsPy. 247000 4164 obspy.iris IRIS Web service client for ObsPy. 261000 4153 Orange Machine learning and interactive data mining toolbox. 14000000 4099 obspy.neries NERIES Web service client for ObsPy. 239000 4066 pandas Powerful data structures for data analysis, time series,and statistics 2000000 4037 pycuda Python wrapper for Nvidia CUDA 1000000 4030 GeoAlchemy Using SQLAlchemy with Spatial Databases 159000 3881 pyfits Reads FITS images and tables into numpy arrays and manipulates FITS headers 748000 3746 HTSeq A framework to process and analyze data from high-throughput sequencing (HTS) assays 523000 3720 pyopencv PyOpenCV - A Python wrapper for OpenCV 2.x using Boost.Python and NumPy 354000 3660 thredds THREDDS catalog generator. 25000 3622 hachoir-subfile Find subfile in any binary stream 16000 3540 fluid Procedures to study geophysical fluids on Python. 210000 3520 pygeocoder Python interface for Google Geocoding API V3. Can be used to easily geocode, reverse geocode, validate and format addresses. 7000 3514 csc-pysparse A fast sparse matrix library for Python (Commonsense Computing version) 111000 3455 topex A very simple library to interpret and load TOPEX/JASON altimetry data 7000 3378 arrayterator Buffered iterator for big arrays. 7000 3320 python-igraph High performance graph data structures and algorithms 3000000 3260 csvkit A library of utilities for working with CSV, the king of tabular file formats. 29000 3236 PyVISA Python VISA bindings for GPIB, RS232, and USB instruments 237000 3201 Quadtree Quadtree spatial index for Python GIS 40000 3000 ProxyHTTPServer ProxyHTTPServer – from the creator of PyWebRun 3000 2991 mpmath Python library for arbitrary-precision floating-point arithmetic 1000000 2901 bigfloat Arbitrary precision correctly-rounded floating point arithmetic, via MPFR. 126000 2879 SimPy Event discrete, process based simulation for Python. 5000000 2871 Delny Delaunay triangulation 18000 2790 pymc Markov Chain Monte Carlo sampling toolkit. 1000000 2727 PyBUFR Pure Python library to encode and decode BUFR. 10000 2676 collective.geo.bundle Plone Maps (collective.geo) 11000 2676 dap DAP (Data Access Protocol) client and server for Python. 125000 2598 rq RQ is a simple, lightweight, library for creating background jobs, and processing them. 29000 2590 pyinterval Interval arithmetic in Python 397000 2558 StarCluster StarCluster is a utility for creating and managing computing clusters hosted on Amazon’s Elastic Compute Cloud (EC2). 2000000 2521 fisher Fast Fisher’s Exact Test 43000 2503 mathdom MathDOM - Content MathML in Python 169000 2482 img2txt superseded by asciiporn, http://pypi.python.org/pypi/asciiporn 443000 2436 DendroPy A Python library for phylogenetics and phylogenetic computing: reading, writing, simulation, processing and manipulation of phylogenetic trees (phylogenies) and characters. 6000000 2349 geolocator geolocator library: locate places and calculate distances between them 26000 2342 MyProxyClient MyProxy Client 67000 2325 PyUblas Seamless Numpy-UBlas interoperability 51000 2252 oroboros Astrology software 1000000 2228 textmining Python Text Mining Utilities 1000000 2198 scikits.talkbox Talkbox, a set of python modules for speech/signal processing 147000 2188 asciitable Extensible ASCII table reader and writer 312000 2160 scikits.samplerate A python module for high quality audio resampling 368000 2151 tabular Tabular data container and associated convenience routines in Python 52000 2114 pywcs Python wrappers to WCSLIB 2000000 2081 DeliciousAPI Unofficial Python API for retrieving data from Delicious.com 19000 2038 hachoir-regex Manipulation of regular expressions (regex) 31000 2031 Kamaelia Kamaelia - Multimedia & Server Development Kit 2000000 2007 seawater Seawater Libray for Python 2000000 1985 descartes Use geometric objects as matplotlib paths and patches 3000 1983 vectorformats geographic data serialization/deserialization library 10000 1949 PyMT A framework for making accelerated multitouch UI 18000000 1945 times Times is a small, minimalistic, Python library for dealing with time conversions between universal time and arbitrary timezones. 4000 1929 CocoPy Python implementation of the famous CoCo/R LL(k) compiler generator. 302000 1913 django-shapes Upload and export shapefiles using GeoDjango. 9000 1901 sympy Computer algebra system (CAS) in Python 5000000 1842 pyfasta fast, memory-efficient, pythonic (and command-line) access to fasta sequence files 14000 1836 ...

After watching Bret Victor’s Inventing on Principle, I just had to figure out a way of getting live reloading to work. I know about LiveReload, of course, and everything I’ve heard about it is good. But their Windows version is in alpha, and I’m not about to experiment just yet. This little script does it for me instead: (function(interval, location) { var lastdate = ""; function updateIfChanged() { var req = new XMLHttpRequest(); req.open("HEAD", location.href, false); req.send(null); var date = req.getResponseHeader("Last-Modified"); if (!lastdate) { lastdate = date; } else if (lastdate != date) { location.reload(); } } setInterval(updateIfChanged, interval); })(300, window.location); It checks the current page every 300 milliseconds and reloads it if the Last-Modified header is changed. I usually include it as a minified script: ...

Here’s the easiest way to set up a Windows XP virtual machine that I could find. (This is useful if you want to try out programs without installing it on your main machine; test your code on a new machine; or test your website on IE6 / IE7 / IE8.) Go to the Virtual PC download site. (I tried VirtualBox and VMWare Player. Virtual PC is better if you’re running Windows on Windows.) If you have Windows 7 Starter or Home, select “Don’t need XP Mode and want VPC only? Download Windows Virtual PC without Windows XP Mode.” If you have Windows Vista or Windows 7, select “Looking for Virtual PC 2007?” Download it. (You may have to jump through a few hoops like activation.) Download Windows XP and run it to extract the files. (It’s a 400MB download.) Open the “Windows XP.vmc” file – just double-clicking ought to work. At this point, you have a working Windows XP version. (The Administrator password is “Password1”.) Under Tools – Settings – Networking – Adapter 1, select “Shared Networking (NAT)” That’s pretty much it. You’ve got a Windows XP machine running inside your other Windows machine. ...

Lisp users would laugh, since they have macros, but Python supports some basic code inspection and modification. Consider the following pieces of code: margin = lambda v: 1 - v['cost'] / v['sales'] What if you wanted another function that lists all the dictionary indices used in the function? That is, you wanted to extract cost and sales? This is a real-life problem I encountered this morning. I have 100 functions, each defining a metric. For example, ...

When processing data at a large scale, there are two characteristics that make a huge difference to my life. Restartability. When something goes wrong, being able to continue from where it stopped. In my opinion, this is more important than parallelism. There’s nothing as depressing as having to start from scratch every time. Think of it as the ability to save a game as opposed to starting from Level 1 in every life. ...

In reality, a colour is a combination of light waves with frequencies between 400-700THz, just like sound is a combination of sound waves with frequencies from 20-20000Hz. Just like mixing various pure notes produces a new sound, mixing various pure colours (like from a rainbow) produces new colours (like white, which isn’t on the rainbow.) Our eyes aren’t like our ears, though. They have 3 sensors that are triggered differently by different frequencies. The sensors roughly peak around red, green and blue. Roughly. ...

Google’s Protocol Buffers is a “language-neutral, platform-neutral, extensible mechanism for serializing structured data – think XML, but smaller, faster, and simpler” XML is slow and large. There’s no doubting that. JSON’s my default alternative, though it’s a bit large. CSV’s ideal for tabular data, but ragged hierarchies are a bit difficult. I was trying to see if Protocol Buffers would be smaller and faster, at least when using Python. I took JSON as the base, and checked the write speed, read speed and file sizes. Here’s the comparison: ...

Turns out that you can use data URIs in the <audio> tag. Just upload an MP3 file to http://dataurl.net/#dataurlmaker and you’ll get a long string starting with data:audio/mp3;base64... Insert this into your HTML: <audio controls src=”data:audio/mp3;base64...”> That’s it – the entire MP3 file is embedded into your HTML page without requiring additional downloads. This takes a bit more bandwidth than the MP3, and won’t work on Internet Explorer. But for modern browsers, and small audio files, it reduces the overall load time – sort of like CSS sprites. ...

This year, I’ve converted the bulk of my content into Markdown – a simple way of formatting text files in a way that can be rendered into HTML. Not out of choice, really. It was the only solution if I wanted to: Edit files on my iPad / iPhone (I’ve started doing that a lot more recently) Allow the contents to be viewable as HTML as well as text, and Allow non techies to edit the file As a bonus, it’s already the format Github and Bitbucket use for markup. ...

I moved from static HTML pages to web applications and back to static HTML files. There’s a lot to be said for the simplicity and portability of a bunch of files. Static site generators like Jekyll are increasingly popular; I’ve built a simple publisher that I use extensively. Web apps give you something else, though, that are still useful on a static site. Access control. I’ve been resorting to htpasswd to protect static files, and it’s far from optimal. I don’t want to know or manage users’ passwords. I don’t want them to remember a new ID. I just want to allow specific people to log in via their Google Accounts. (OpenID is too confusing, and most people use Google anyway.) ...

The best way to explain code to a group of people is by walking through it. If they’re far away in space or time, then a video is the next best thing. You can recommend them to try out the best coding apps as well. The trouble with videos, though, is that they’re big. I can’t host them on my server – I’d need YouTube. Editing them is tough. You can’t copy & paste code from videos. And so on. One interesting alternative is to use presentations with audio. Slideshare, for instance, lets you share slides and sync it with audio. That almost works. But it’s still not good enough. I’d like code to be stored as code. What I really need is codecasting: a YouTube or Slideshare for code. The closest I’ve seen until day-before was etherpad or ttyrec – but neither support audio. Enter Popcorn. It’s a Javascript library from Mozilla that, among other things, can fire events when an audio/video element reaches a particular point. ...

Summary: Arrays are a lot smaller than objects, but only slightly faster on newer browsers. I’m writing an in-memory Javascript app that handles several thousand rows. Each row could be stored either as an array [1,2,3] or an object {"x":1,"y":2,"z":3}. Having read up on the performance of arrays vs objects, I thought I’d do a few tests on storing numbers from 0 to 1 million. The results for Chrome are below. (Firefox 7 was similar.) ...

Yesterday, I wrote about node.js being fast. Here are some numbers. I ran Apache Benchmark on the simplest Hello World program possible, testing 10,000 requests with 100 concurrent connections (ab -n 10000 -c 100). These are on my Dell E5400, with lots of application running, so take them with a pinch of salt. PHP5 on Apache 2.2.6 <?php echo “Hello world” ?> 1,550/sec Base case. But this isn’t too bad Tornado/Python See Tornadoweb example 1,900/sec Over 20% faster Static HTML on Apache 2.2.6 Hello world 2,250/sec Another 20% faster Static HTML on nginx 0.9.0 Hello world 2,400/sec 6% faster node.js 0.4.1 See nodejs.org example 2,500/sec Faster than a static file on nginx! I was definitely NOT expecting this result… but it looks like serving a static file with node.js could be faster than nginx. This might explain why Markup.io is exposing node.js directly, without an nginx or varnish proxy. ...