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blockcode/blockcode.markdown

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title: Blockcode: A visual programming toolkit
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author: Dethe Elza
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<markdown>
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_[Dethe](https://twitter.com/dethe) is a geek dad, aesthetic programmer, mentor, and creator of the [Waterbear](http://waterbearlang.com/) visual programming tool. He co-hosts the Vancouver Maker Education Salons and wants to fill the world with robotic origami rabbits._
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</markdown>
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In block-based programming languages, you write programs by dragging and connecting blocks that represent parts of the program. Block-based languages differ from conventional programming languages, in which you type words and symbols.
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Learning a programming language can be difficult because they are extremely sensitive to even the slightest of typos. Most programming languages are case-sensitive, have obscure syntax, and will refuse to run if you get so much as a semicolon in the wrong place --- or worse, leave one out. Further, most programming languages in use today are based on English and their syntax cannot be localized.

ci/ci.markdown

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title: A Continuous Integration System
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author: Malini Das
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_Malini Das is a software engineer who is passionate about developing quickly (but safely!), and solving cross-functional problems. She has worked at Mozilla as a tools engineer and is currently honing her skills at Twitch. Follow Malini on [Twitter](https://twitter.com/malinidas) or on her [blog](http://malinidas.com/)._
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## What is a Continuous Integration System?
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When developing software, we want to be able to verify that our new

cluster/cluster.markdown

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title: Clustering by Consensus
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author: Dustin J. Mitchell
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_Dustin is an open source software developer and release engineer at Mozilla.
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He has worked on projects as varied as a host configuration system in Puppet, a
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Flask-based web framework, unit tests for firewall configurations, and a
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continuous integration framework in Twisted Python. Find him as [\@djmitche](http://github.com/djmitche) on
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GitHub or at [dustin@mozilla.com](mailto:dustin@mozilla.com)._
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## Introduction
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In this chapter, we'll explore implementation of a network protocol designed to support reliable distributed computation.

contingent/contingent.markdown

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title: Contingent: A Fully Dynamic Build System
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author: Brandon Rhodes and Daniel Rocco
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_Brandon Rhodes started using Python in the late 1990s, and for 17 years has
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maintained the PyEphem library for amateur astronomers. He works at
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Dropbox, has taught Python programming courses for corporate clients,
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things; he loves seeing the spark of wonder and delight in people's eyes when
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someone shares a novel, surprising, or beautiful idea. Daniel lives in Atlanta
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with a microbiologist and four aspiring rocketeers._
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## Introduction
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Build systems have long been a standard tool

crawler/crawler.markdown

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title: A Web Crawler With asyncio Coroutines
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author: A. Jesse Jiryu Davis and Guido van Rossum
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_A. Jesse Jiryu Davis is a staff engineer at MongoDB in New York. He wrote Motor, the async MongoDB Python driver, and he is the lead developer of the MongoDB C Driver and a member of the PyMongo team. He contributes to asyncio and Tornado. He writes at [http://emptysqua.re](http://emptysqua.re)._
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_Guido van Rossum is the creator of Python, one of the major programming languages on and off the web. The Python community refers to him as the BDFL (Benevolent Dictator For Life), a title straight from a Monty Python skit. Guido's home on the web is [http://www.python.org/~guido/](http://www.python.org/~guido/)._
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## Introduction
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Classical computer science emphasizes efficient algorithms that complete computations as quickly as possible. But many networked programs spend their time not computing, but holding open many connections that are slow, or have infrequent events. These programs present a very different challenge: to wait for a huge number of network events efficiently. A contemporary approach to this problem is asynchronous I/O, or "async".

dagoba/dagoba.markdown

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title: Dagoba: an in-memory graph database
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author: Dann Toliver
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_[Dann](https://twitter.com/dann) enjoys building things, like programming languages, databases, distributed systems, communities of smart friendly humans, and pony castles with his two year old._
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## Prologue
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> "When we try to pick out anything by itself we find that it is bound fast by a thousand invisible cords that cannot be broken, to everything in the universe."

data-store/data-store.markdown

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title: DBDB: Dog Bed Database
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author: Taavi Burns
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_As the newest bass (and sometimes tenor) in [Countermeasure](http://www.countermeasuremusic.com), Taavi strives to break the mould... sometimes just by ignoring its existence. This is certainly true through the diversity of workplaces in his career: IBM (doing C and Perl), FreshBooks (all the things), Points.com (doing Python), and now at PagerDuty (doing Scala). Aside from that—when not gliding along on his Brompton folding bike—you might find him playing Minecraft with his son or engaging in parkour (or rock climbing, or other adventures) with his wife. He knits continental._
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## Introduction
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DBDB (Dog Bed Database) is a Python library that implements a simple key/value database.

flow-shop/flow-shop.markdown

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title: A Flow Shop Scheduler
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author: Dr. Christian Muise
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_[Dr. Christian Muise](http://haz.ca) is a Research Fellow with the [MERS group](http://groups.csail.mit.edu/mers/) at [MIT's CSAIL](http://www.csail.mit.edu/). He is interested in a variety of topics including AI, data-driven projects, mapping, graph theory, and data visualization, as well as celtic music, carving, soccer, and coffee._
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## A Flow Shop Scheduler
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*Flow shop scheduling* is one of the most challenging and well-studied problems in operations research. Like many challenging optimization problems, finding the best solution is just not possible for problems of a practical size. In this chapter we consider the implementation of a flow shop scheduling solver that uses a technique called *local search*. Local search allows us to find a solution that is "pretty good" when finding the best solution isn't possible. The solver will try and find new solutions to the problem for a given amount of time, and finish by returning the best solution found.
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functionalDB/functionalDB.markdown

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title: An Archaeology-Inspired Database
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author: Yoav Rubin
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_Yoav Rubin is a Senior Software Engineer at Microsoft, and prior to that was a Research Staff Member and a Master Inventor at IBM Research. He works now in the domain of data security in the cloud, and in the past his work focused on developing cloud or web based development environments. Yoav holds an M.Sc. in Medical Research in the field of Neuroscience and B.Sc in Information Systems Engineering. He goes by [\@yoavrubin](https://twitter.com/yoavrubin) on Twitter, and occasionally blogs at [http://yoavrubin.blogspot.com](http://yoavrubin.blogspot.com)._
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## Introduction
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Software development is often viewed as a rigorous process, where the inputs are requirements and the output is the working product. However, software developers are people, with their own perspectives and biases which color the outcome of their work.

interpreter/interpreter.markdown

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title: A Python Interpreter Written in Python
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author: Allison Kaptur
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_Allison is an engineer at Dropbox, where she helps maintain one of the largest networks of Python clients in the world. Before Dropbox, she was a facilitator at the Recurse Center, a writers retreat for programmers in New York. She's spoken at PyCon North America about Python internals and loves weird bugs. She blogs at [akaptur.com](http://akaptur.com)._
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_(This chapter is also available in [Simplified Chinese](http://qingyunha.github.io/taotao/))_.
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## Introduction
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Byterun is a Python interpreter implemented in Python. Through my work on Byterun, I was surprised and delighted to discover that the fundamental structure of the Python interpreter fits easily into the 500-line size restriction. This chapter will walk through the structure of the interpreter and give you enough context to explore it further. The goal is not to explain everything there is to know about interpreters --- like so many interesting areas of programming and computer science, you could devote years to developing a deep understanding of the topic.

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