Categories
Cloud DevOps Software Engineering

GitHub

Font Awesome 5 brands github.svg
GitHub logo 2013.svg
Type of businessSubsidiary
Type of siteCollaborative version control
Available inEnglish
FoundedFebruary 8, 2008; 13 years ago (as Logical Awesome LLC)
HeadquartersSan Francisco, California, United States
Area servedWorldwide
Founder(s)Tom Preston-WernerChris WanstrathP. J. HyettScott Chacon
CEONat Friedman
Key peopleMike Taylor (CFO)
IndustryCollaborative version control (GitHub)
Blog host (GitHub Pages)
Package repository (NPM)
Employees1677[1]
ParentMicrosoft
URLgithub.com 
RegistrationOptional (required for creating and joining repositories)
Users56 million (Sep 2020)
LaunchedApril 10, 2008; 12 years ago
Current statusActive
Written inRuby
ECMAScript
Go
C [2]

GitHub, Inc. is a provider of Internet hosting for software development and version control using Git. It offers the distributed version control and source code management (SCM) functionality of Git, plus its own features. It provides access control and several collaboration features such as bug trackingfeature requests, task managementcontinuous integration and wikis for every project.[3] Headquartered in California, it has been a subsidiary of Microsoft since 2018.[4]

GitHub offers its basic services free of charge. Its more advanced professional and enterprise services are commercial.[5] Free GitHub accounts are commonly used to host open-source projects.[6] As of January 2019, GitHub offers unlimited private repositories to all plans, including free accounts, but allowed only up to three collaborators per repository for free.[7] Starting from April 15, 2020, the free plan allows unlimited collaborators, but restricts private repositories to 2,000 minutes of GitHub Actions[8] per month.[9] As of January 2020, GitHub reports having over 40 million users[10] and more than 190 million repositories[11] (including at least 28 million public repositories),[12] making it the largest host of source code in the world.[13]

History

GitHub at AWS Summit

The GitHub service was developed by Chris WanstrathP. J. HyettTom Preston-Werner and Scott Chacon using Ruby on Rails, and started in February 2008. The company, GitHub, Inc., has existed since 2007 and is located in San Francisco.[14]The shading of the map illustrates the number of users as a proportion of each country’s Internet population. The circular charts surrounding the two hemispheres depict the total number of GitHub users (left) and commits (right) per country.

On February 24, 2009, GitHub announced that within the first year of being online, GitHub had accumulated over 46,000 public repositories, 17,000 of which were formed in the previous month. At that time, about 6,200 repositories had been forked at least once and 4,600 had been merged.

That same year, the site was harnessed by over 100,000 users, according to Github, and had grown to host 90,000 unique public repositories, 12,000 having been forked at least once, for a total of 135,000 repositories.[15]

In 2010, GitHub was hosting 1 million repositories.[16] A year later, this number doubled.[17] ReadWriteWeb reported that GitHub had surpassed SourceForge and Google Code in total number of commits for the period of January to May 2011.[18] On January 16, 2013, GitHub passed the 3 million users mark and was then hosting more than 5 million repositories.[19] By the end of the year, the number of repositories were twice as much, reaching 10 million repositories.[20]

In 2012, GitHub raised $100 million in funding from Andreessen Horowitz with $750 million valuation.[21] Peter Levine, general partner at Andreessen Horowitz, stated that GitHub had been growing revenue at 300% annually since 2008 “profitably nearly the entire way”.[22] On July 29, 2015, GitHub stated it had raised $250 million in funding in a round led by Sequoia Capital. Other investors of that round included Andreessen Horowitz, Thrive Capital, and IVP (Institutional Venture Partners).[23] The round valued the company at approximately $2 billion.[24]

In 2015, GitHub opened an office in Japan that is its first office outside of the U.S.[25] In 2016, GitHub was ranked No. 14 on the Forbes Cloud 100 list.[26] It has not been featured on the 2018, 2019 and 2020 lists.[27]

On February 28, 2018, GitHub fell victim to the third largest distributed denial-of-service (DDoS) attack in history, with incoming traffic reaching a peak of about 1.35 terabits per second.[28]

On June 19, 2018, GitHub expanded its GitHub Education by offering free education bundles to all schools.[29][30]

Acquisition by Microsoft

From 2012 Microsoft became a significant user of GitHub, using it to host open-source projects and development tools such as .NET CoreChakra CoreMSBuildPowerShellPowerToysVisual Studio CodeWindows CalculatorWindows Terminal and the bulk of its product documentation (now to be found on Microsoft Docs).[31][32]

On June 4, 2018, Microsoft announced its intent to acquire GitHub for US$7.5 billion. The deal closed on October 26, 2018.[33] GitHub continued to operate independently as a community, platform and business.[34] Under Microsoft, the service was led by Xamarin‘s Nat Friedman, reporting to Scott Guthrie, executive vice president of Microsoft Cloud and AI. GitHub’s CEO, Chris Wanstrath, was retained as a “technical fellow”, also reporting to Guthrie.

There have been concerns from developers Kyle Simpson, JavaScript trainer and author, and Rafael Laguna, CEO at Open-Xchange over Microsoft’s purchase, citing uneasiness over Microsoft’s handling of previous acquisitions, such as Nokia’s mobile business or Skype.[35][36]

This acquisition was in line with Microsoft’s business strategy under CEO Satya Nadella, which has seen a larger focus on the cloud computing services, alongside development of and contributions to open-source software.[37][4][32] Harvard Business Review argued that Microsoft was intending to acquire GitHub to get access to its user base, so it can be used as a loss leader to encourage use of its other development products and services.[38]

Concerns over the sale bolstered interest in competitors: Bitbucket (owned by Atlassian), GitLab (a commercial open source product that also runs a hosted service version) and SourceForge (owned by BIZX, LLC) reported that they had seen spikes in new users intending to migrate projects from GitHub to their respective services.[39][40][41][42]

In September 2019, GitHub acquired Semmle, a code analysis tool.[43] In February 2020, GitHub launched in India under the name GitHub India Private Limited.[44] In March 2020, GitHub announced that they were acquiring npm, a JavaScript packaging vendor, for an undisclosed sum of money.[45] The deal was closed on 15 April 2020.[46]

In early July 2020, the GitHub Archive Program was established, to archive its open source code in perpetuity.[47]

Services

GitHub.com

Development of the GitHub.com platform began on October 19, 2007.[60][61][62] The site was launched in April 2008 by Tom Preston-Werner, Chris Wanstrath, P. J. Hyett and Scott Chacon after it had been made available for a few months prior as a beta release.[63]

Projects on GitHub.com can be accessed and managed using the standard Git command-line interface; all standard Git commands work with it. GitHub.com also allows users to browse public repositories on the site. Multiple desktop clients and Git plugins are also available. The site provides social networking-like functions such as feeds, followers, wikis (using wiki software called Gollum) and a social network graph to display how developers work on their versions (“forks“) of a repository and what fork (and branch within that fork) is newest.

Anyone can browse and download public repositories but only registered users can contribute content to repositories. With a registered user account, users are able to have discussions, manage repositories, submit contributions to others’ repositories, and review changes to code. GitHub.com began offering unlimited private repositories at no cost in January 2019 (limited to three contributors per project). Previously, only public repositories were free.[64][65][66] On April 14, 2020, GitHub made “all of the core GitHub features” free for everyone, including “private repositories with unlimited collaborators”.[67]

The fundamental software that underpins GitHub is Git itself, written by Linus Torvalds, creator of Linux. The additional software that provides the GitHub user interface was written using Ruby on Rails and Erlang by GitHub, Inc. developers Wanstrath,[68] Hyett, and Preston-Werner.

Scope

The main purpose of GitHub.com is to facilitate the version control and issue tracking aspects of software development. Labels, milestones, responsibility assignment, and a search engine are available for issue tracking. For version control, Git (and by extension GitHub.com) allows pull requests to propose changes to the source code. Users with the ability to review the proposed changes can see a diff of the requested changes and approve them. In Git terminology, this action is called “committing” and one instance of it is a “commit”. A history of all commits are kept and can be viewed at a later time.

In addition, GitHub supports the following formats and features:

  • Documentation, including automatically rendered README files in a variety of Markdown-like file formats (see README § On GitHub)
  • Wikis
  • GitHub Actions, which allows building continuous integration and continuous deployment pipelines for testing, releasing and deploying software without the use of third-party websites/platforms
  • Graphs: pulse, contributors, commits, code frequency, punch card, network, members
  • Integrations Directory[69]
  • Email notifications
  • Discussions
  • Option to subscribe someone to notifications by @ mentioning them.[70]
  • Emojis[71]
  • Nested task-lists within files
  • Visualization of geospatial data
  • 3D render files that can be previewed using a new integrated STL file viewer that displays the files on a “3D canvas”.[72] The viewer is powered by WebGL and Three.js.
  • Photoshop’s native PSD format can be previewed and compared to previous versions of the same file.
  • PDF document viewer
  • Security Alerts of known Common Vulnerabilities and Exposures in different packages

GitHub’s Terms of Service do not require public software projects hosted on GitHub to meet the Open Source Definition. The terms of service state, “By setting your repositories to be viewed publicly, you agree to allow others to view and fork your repositories.”[73]

GitHub Enterprise

GitHub Enterprise is a self-managed version of GitHub.com with similar functionality. It can be run on an organization’s own hardware or on a cloud provider, and it has been available since November 2011.[74] In November 2020, source code for GitHub Enterprise Server was leaked online in apparent protest against DMCA takedown of YouTube-dl. According to GitHub, the source code came from GitHub accidentally sharing the code with Enterprise customers themselves, not from an attack on GitHub servers.[75][76]

GitHub Pages

GitHub Pages is a static web hosting service offered by GitHub since 2008 to GitHub users for hosting user blogs, project documentation,[77][78] or even whole books created as a page.[79]

All GitHub Pages content is stored in a Git repository, either as files served to visitors verbatim or in Markdown format. GitHub is seamlessly integrated with Jekyll static web site and blog generator and GitHub continuous integration pipelines. Each time the content source is updated, Jekyll regenerates the website and automatically serves it via GitHub Pages infrastructure.[80]

As with the rest of GitHub, it includes both free and paid tiers of service, instead of being supported by web advertising. Web sites generated through this service are hosted either as subdomains of the github.io domain, or as custom domains bought through a third-party domain name registrar.[81] When custom domain is set on a GitHub Pages repo a Let’s Encrypt certificate for it is generated automatically. Once the certificate has been generated Enforce HTTPS can be set for the repository’s website to transparently redirect all HTTP requests to HTTPS.[82][83]

Gist

GitHub also operates other services: a pastebin-style site called Gist[63] that is for hosting code snippets (GitHub proper is for hosting larger projects).

Tom Preston-Werner presented the then-new Gist feature at a punk rock Ruby conference in 2008.[84] Gist builds on the traditional simple concept of a pastebin by adding version control for code snippets, easy forking, and TLS encryption for private pastes. Because each “gist” has its own Git repository, multiple code snippets can be contained in a single paste and they can be pushed and pulled using Git. Further, forked code can be pushed back to the original author in the form of a patch, so gists (pastes) can become more like mini-projects.[citation needed]

Before February 18, 2018, unregistered users were able to upload text to the site. Since then, uploading gists has been deactivated for unregistered users with the aim to mitigate spamming.[85]

Education program

GitHub launched a new program called the GitHub Student Developer Pack to give students free access to popular development tools and services. GitHub partnered with BitnamiCrowdflowerDigitalOceanDNSimpleHackHandsNamecheap, Orchestrate, Screenhero, SendGridStripeTravis CI and Unreal Engine to launch the program.[86]

In 2016 GitHub announced the launch of the GitHub Campus Experts program[87] to train and encourage students to grow technology communities at their universities. The Campus Experts program is open to university students of 18 years and older across the world.[88] GitHub Campus Experts are one of the primary ways that GitHub funds student oriented events and communities, Campus Experts are given access to training, funding, and additional resources to run events and grow their communities. To become a Campus Expert applicants must complete an online training course consisting of multiple modules designed to grow community leadership skills.

GitHub Marketplace service

GitHub also provides some software as a service integrations for adding extra features to projects. Those services include:

  • Waffle.io: Project management for software teams. Automatically see pull requests, automated builds, reviews, and deployments across all of your repositories in GitHub.
  • Rollbar: Integrate with GitHub to provide real time debugging tools and full-stack exception reporting. It is compatible with all well used code languages, such as JavaScriptPython.NETRubyPHPNode.jsAndroidiOSGoJava, and C#.
  • Codebeat: For automated code analysis specialized in web and mobile developers. The supported languages for this software are: ElixirGoJavaSwiftJavaScriptPythonRubyKotlinObjective-C, and TypeScript.
  • Travis CI: To provide confidence for your apps while doing test and ship. Also gives full control over the build environment, to adapt it to the code. Supported languages: GoJavaJavaScriptObjective-CPythonPHPRuby, and Swift.
  • GitLocalize: Developed for teams that are translating their content from one point to another. GitLocalize automatically syncs with your repository so you can keep your workflow on GitHub. It also keeps you updated on what needs to be translated.

GitHub Sponsors

GitHub Sponsors allows users to make monthly money donations to projects hosted on GitHub.[89] The public beta was announced on May 23, 2019 and currently the project accepts wait list registrations. The Verge said that GitHub Sponsors “works exactly like Patreon” because “developers can offer various funding tiers that come with different perks, and they’ll receive recurring payments from supporters who want to access them and encourage their work” except with “zero fees to use the program”. Furthermore, GitHub offer incentives for early adopters during the first year: it pledges to cover payment processing costs, and match sponsorship payments up to $5,000 per developer. Furthermore, users still can use other similar services like Patreon and Open Collective and link to their own websites.[90][91]

GitHub Archive Program

In July 2020, GitHub stored a February archive of the site[47] in an abandoned mountain mine in Svalbard, Norway, part of the Arctic World Archive and not far from the Svalbard Global Seed Vault. The archive contained the code of all active public repositories, as well as that of dormant, but significant public repositories. The 21TB of data was stored on piqlFilm archival film reels as QR codes, and is expected to last 500–1,000 years.[92][93][94][95]

The GitHub Archive Program is also working with partners on Project Silica, in an attempt to store all public repositories for 10,000 years. It aims to write archives into the molecular structure of quartz glass platters, using a high-precision laser that pulses a quadrillion (1,000,000,000,000,000) times per second.[95]

Developed projects

  • Atom, a free and open-source text and source code editor
  • Electron, an open-source framework to use JavaScript-based websites as desktop applications.

Prominent users

Some prominent open source organizations and projects use GitHub as a primary place for collaboration, including:

See also

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” (WP)

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Bibliography Python Software Engineering

Python in a Nutshell: A Desktop Quick Reference

See also: Python, Python Bibliography and Bibliography of Python Libraries and Web Frameworks

See: Python in a Nutshell: A Desktop Quick Reference, 3rd Edition, by Alex Martelli, Anna Ravenscroft, and Steve Holden, 2017, B06Y4DVSBM (PyNutSh)

Fair Use Source: B06Y4DVSBM (PyNutSh)

About This Book:

Useful in many roles, from design and prototyping to testing, deployment, and maintenance, Python is consistently ranked among today’s most popular programming languages. The third edition of this practical book provides a quick reference to the language—including Python 3.5, 2.7, and highlights of 3.6—commonly used areas of its vast standard library, and some of the most useful third-party modules and packages.

Ideal for programmers with some Python experience, and those coming to Python from other programming languages, this book covers a wide range of application areas, including web and network programming, XML handling, database interactions, and high-speed numeric computing. Discover how Python provides a unique mix of elegance, simplicity, practicality, and sheer power.

This edition covers:

  • Python syntax, Object-Oriented Python, standard library modules, and third-party Python packages
  • Python’s support for file and text operations, persistence and databases, concurrent execution, and numeric computations
  • Networking basics, event-driven programming, and client-side network protocol modules
  • Python extension modules, and tools for packaging and distributing extensions, modules, and applications

Reviews:

“Holden, Ravenscroft, and Martelli are well known Python masters. Their exceptional lucidity shines through in one of Python’s best references, covering the core language, libraries, and essential parts of the Python ecosystem.” — Raymond HettingerDistinguished Python Core Developer –

About the Author:

Alex Martelli spent 8 years with IBM Research, then 13 at think3 inc., followed by 4 years as a consultant (mostly for AB Strakt in Göteborg, Sweden), and lately 12 years at Google (currently as tech lead of 1:many tech support for Google Cloud Platform). He has also taught programming languages, development methods, and numerical computing at Ferrara University and other venues. He’s a Fellow of the Python Software Foundation, a winner of the Frank Willison Memorial Award for contributions to the Python community, and a top-page reputation hog on Stack Overflow. Books he’s authored or co-authored include two editions of the Python Cookbook, three of Python in a Nutshell, and “Beautiful Teams.” Dozens of his tech talks at conferences, and interviews with him, are available on YouTube.

Alex’s proudest achievement are the articles that appeared in Bridge World (January and February 2000), which were hailed as giant steps towards solving issues that had haunted contract bridge theoreticians for decades, and still get quoted in current bridge-theoretical literature, after all these years.

Book Details:

  • ASIN: B06Y4DVSBM
  • ISBN-10: 144939292X
  • ISBN-13: 978-1449392925
  • Publisher: O’Reilly Media; 3rd edition (April 7, 2017)
  • Publication date: April 7, 2017
  • Print length: 1164 pages

Table of Contents:

  • Part I, Getting Started with Python
  • Part II, Core Python Language and Built-ins
  • Part III, Python Library and Extension Modules
  • Part IV, Network and Web Programming
  • Part V, Extending, Distributing, v2/v3 Migration

Preface:

“The Python programming language reconciles many apparent contradictions: both elegant and pragmatic, both simple and powerful, it’s very high-level yet doesn’t get in your way when you need to fiddle with bits and bytes, and it’s suitable for programming novices as well as great for experts, too.” (PyNutSh)

“This book is aimed at programmers with some previous exposure to Python, as well as experienced programmers coming to Python for the first time from other languages. The book is a quick reference to Python itself, the most commonly used parts of its vast standard library, and a few of the most popular and useful third-party modules and packages, covering a wide range of application areas, including web and network programming, XML handling, database interactions, and high-speed numeric computing. The book focuses on Python’s cross-platform capabilities and covers the basics of extending Python and embedding it in other applications.” (PyNutSh)

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Bibliography

B06Y4DVSBM

See: Python in a Nutshell: A Desktop Quick Reference, 3rd Edition, by Alex Martelli, Anna Ravenscroft, and Steve Holden, 2017

Fair Use Source: B06Y4DVSBM (PyNutSh)

Categories
Bibliography Python Software Engineering

Practices of the Python Pro

See also: Python, Python Bibliography and Bibliography of Python Libraries and Web Frameworks

See: Practices of the Python Pro, by Dane Hillard, 2020, 1617296082 (PrPyPro)

Fair Use Source: 1617296082 (PrPyPro)

About This Book:

Summary

Professional developers know the many benefits of writing application code that’s clean, well-organized, and easy to maintain. By learning and following established patterns and best practices, you can take your code and your career to a new level.
With Practices of the Python Pro, you’ll learn to design professional-level, clean, easily maintainable software at scale using the incredibly popular programming language, Python. You’ll find easy-to-grok examples that use pseudocode and Python to introduce software development best practices, along with dozens of instantly useful techniques that will help you code like a pro.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the technology

Professional-quality code does more than just run without bugs. It’s clean, readable, and easy to maintain. To step up from a capable Python coder to a professional developer, you need to learn industry standards for coding style, application design, and development process. That’s where this book is indispensable.

About the book

Practices of the Python Pro teaches you to design and write professional-quality software that’s understandable, maintainable, and extensible. Dane Hillard is a Python pro who has helped many dozens of developers make this step, and he knows what it takes. With helpful examples and exercises, he teaches you when, why, and how to modularize your code, how to improve quality by reducing complexity, and much more. Embrace these core principles, and your code will become easier for you and others to read, maintain, and reuse.

What’s inside

  • Organizing large Python projects
  • Achieving the right levels of abstraction
  • Writing clean, reusable code Inheritance and composition
  • Considerations for testing and performance

About the reader

For readers familiar with the basics of Python, or another OO language.

Reviews:

“A wealth of information on general software architecture and truths that are applicable to any language.”–David T. Kerns, Rincon Research Corporation

“Get this book, and begin to write Python code like a professional.” –Davide Cadamuro, BMW Group

“Easy-to-follow book with great information on how to design your software for easy scaling and readability.” –Mike Stevens, Silver Hammer Associates

“This will take a Python developer down a path to becoming a pro.” –Joseph Perenia, Sony Interactive Entertainment

About the Author:

Dane Hillard has spent the majority of his development career using Python to build web applications. https://github.com/daneah, https://dev.to/easyaspython, https://easyaspython.com

Book Details:

  • ASIN: 1617296082
  • ISBN-10: 1617296082
  • ISBN-13: 978-1617296086
  • Publisher: Manning Publications; 1st edition (January 14, 2020)
  • Paperback: 248 pages

Table of Contents:

PART 1 WHY IT ALL MATTERS

1 ¦ The bigger picture

PART 2 FOUNDATIONS OF DESIGN

2 ¦ Separation of concerns

3 ¦ Abstraction and encapsulation

4 ¦ Designing for high performance

5 ¦ Testing your software

PART 3 NAILING DOWN LARGE SYSTEMS

6 ¦ Separation of concerns in practice

7 ¦ Extensibility and flexibility

8 ¦ The rules (and exceptions) of inheritance

9 ¦ Keeping things lightweight

10 ¦ Achieving loose coupling

PART 4 WHAT’S NEXT?

11 ¦ Onward and upward

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1617296082

See: Practices of the Python Pro, by Dane Hillard, 2020

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Bibliography Python Software Engineering

The Well-Grounded Python Developer

See also: Python, Python Bibliography and Bibliography of Python Libraries and Web Frameworks

See: The Well-Grounded Python Developer, by Doug Farrell, 2021, 1617297441 (WlGrPD)

Fair Use Source: 1617297441 (WlGrPD)

About the Technology:

Python is the perfect language for beginning programmers. It is easy to learn, with tons of helpful libraries and tools. Better still, it doesn’t run out of steam when you want to create more advanced applications for web development or machine learning. Once you’ve mastered the syntax of simple Python scripts, it can be a challenge to progress to more ambitious projects. This book helps you on that path.

About This Book:

When you’re new to Python, it can be tough to understand where and how to use its many language features. There’s a dizzying array of libraries, and it’s challenging to fit everything together. The Well-Grounded Python Developer builds on Python skills you’ve learned in isolation and shows you how to unify them into a meaningful whole. As you work through this practical guide, you’ll discover how all the bits of the Python ecosystem connect as you build and modify a typical web server application.

  • Building modules of functionality
  • Creating a well-constructed web server application
  • Using REST to present data dynamically to a user
  • Refactor and decoupling systems to help scale them
  • How to think about the big picture of your application

The Well-Grounded Python Developer teaches you how to write real software in Python by building on the basic language skills you already have. Veteran developer Doug Farrell helps you see the big picture you can create out of small pieces, introducing concepts like modular construction, APIs, and the design of a basic web server. Throughout the book, you’ll practice your skills by building a blogging platform—the kind of web app that’s in high demand by modern businesses. When you’re finished, you’ll have gone from having a basic understanding of Python’s syntax, grammar, and libraries to using them as the tools of a professional software developer.

Reviews:

“I would consider this book a bible of sorts, offering something to every level of Python developer.” — Lee Harding

About the Author:

Doug Farrell has been developing software since 1983, and has worked with Python for over 20 years.

Book Details:

  • ASIN: 1617297441
  • ISBN-10: 1617297441
  • ISBN-13: 978-1-617297441
  • Publisher: Manning Publications; 1st edition, 2021
  • Paperback: 375 pages

Table of Contents:

Brief Contents:

1 Becoming a Pythonista

2 Your Python Environment

3 Names and Namespaces

4 Application Programmers Interface

5 Object-Oriented Coding

6 Exception Handling

7 Web Servers

8 Your First Web Server

9 Your Second Web Server

10 REST: An API Convention

11 Your Third Web Server

12 Persisting Data

13 Persisting the Mini-Blog to a Database

14 Your Fourth Web Server

15 Thinking Big Picture

16 Conclusion

Preface:

“The goal of this book is to take you past beginning Python programming to the point where you think and feel like a software developer. Where the syntax and grammar of Python are not only comfortable for you but become the tools of a craftsman. With these tools you’ll be able to take on bigger and more complex projects.” (WlGrPD)

“I first discovered Python when I moved from the world of Windows development to the Linux environment. I was an accomplished C/C++ developer, but was interested in learning the scripting languages available in Linux. Fortunately, I came across Python because of its strong support for Object Oriented Programming, which I enjoyed in C++. Since then I’ve never looked back, and Python has become my primary language.” (WlGrPD)

“There are a lot of beginner Python books, Python cookbooks and reference titles, and many of them are very good. To get the most from this book you should be past the beginner level and comfortable with Python. My hope is this book provides a middle ground that gives you more context about how and why you should take certain paths when developing a program.” (WlGrPD)

“You’ll take the loops, conditionals and statements you know now and create larger constructs to handle bigger programming challenges. You’ll learn some conventions and patterns that will reduce the cognitive load on you solving smaller syntactic issues and begin to think how to solve the big picture problems. How the tools you have, and will learn about, can be combined to take goal from problem to solution.” (WlGrPD)

“The book does this by taking you along on a development journey to build a web application providing a simple blogging platform. While I think that’s an interesting application to build, the creation of that application isn’t the end goal of the book. The journey is far more important, the ideas and implementation of those ideas as code, is the real value. The chapters progress and build on the previous ones to illustrate why certain choices were made, and how those choices can be altered and improved as more is learned later in the book.” (WlGrPD)

“As developers we are at an interesting place in the history of the industry. Engineering standards are as important in software development as they are in other disciplines. However, the pace of change in the software world changes those standards as well and provides an opportunity for a great deal of craftsmanship and artistry from a developer. Python gives you a powerful palette of tools to express that.” —Doug Farrell (WlGrPD)

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1617297441

See: The Well-Grounded Python Developer, by Doug Farrell, 2021

Fair Use Source: 1617297441 (WlGrPD)

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Operating systems (OS)

An operating system (OS) is system software that manages computer hardwaresoftware resources, and provides common services for computer programs.

Time-sharing operating systems schedule tasks for efficient use of the system and may also include accounting software for cost allocation of processor timemass storage, printing, and other resources.

For hardware functions such as input and output and memory allocation, the operating system acts as an intermediary between programs and the computer hardware,[1][2] although the application code is usually executed directly by the hardware and frequently makes system calls to an OS function or is interrupted by it. Operating systems are found on many devices that contain a computer – from cellular phones and video game consoles to web servers and supercomputers.

The dominant general-purpose[3] desktop operating system is Microsoft Windows with a market share of around 76.45%. macOS by Apple Inc. is in second place (17.72%), and the varieties of Linux are collectively in third place (1.73%).[4] In the mobile sector (including smartphones and tablets), Android’s share is up to 72% in the year 2020.[5] According to third quarter 2016 data, Android’s share on smartphones is dominant with 87.5 percent with also a growth rate of 10.3 percent per year, followed by Apple’s iOS with 12.1 percent with per year decrease in market share of 5.2 percent, while other operating systems amount to just 0.3 percent.[6] Linux distributions are dominant in the server and supercomputing sectors. Other specialized classes of operating systems (special-purpose operating systems)[7][8]), such as embedded and real-time systems, exist for many applications. Security-focused operating systems also exist. Some operating systems have low system requirements (i.e. light-weight Linux distribution). Others may have higher system requirements.

Some operating systems require installation or may come pre-installed with purchased computers (OEM-installation), whereas others may run directly from media (i.e. live cd) or flash memory (i.e. usb stick).

Categories
Python Software Engineering

Benevolent dictator for life (BDFL)

See also: Python, Python Bibliography and Bibliography of Python Libraries and Web Frameworks, Python Programming Courses

Benevolent dictator for life (BDFL) is a title given to a small number of open-source software development leaders, typically project founders who retain the final say in disputes or arguments within the community. The phrase originated in 1995 with reference to Guido van Rossum, creator of the Python programming language.[1][2] Shortly after Van Rossum joined the Corporation for National Research Initiatives, the term appeared in a follow-up mail by Ken Manheimer to a meeting trying to create a semi-formal group that would oversee Python development and workshops; this initial use included an additional joke of naming Van Rossum the “First Interim BDFL”.[1] Van Rossum announced on July 12, 2018 that he would be stepping down as BDFL of Python without appointing a successor, effectively eliminating the title within the Python community structure.[3]” (WP)

“BDFL should not be confused with the more common term for open-source leaders, “benevolent dictator”, which was popularized by Eric S. Raymond‘s essay “Homesteading the Noosphere” (1999).[4] Among other topics related to hacker culture, Raymond elaborates on how the nature of open source forces the “dictatorship” to keep itself benevolent, since a strong disagreement can lead to the forking of the project under the rule of new leaders.” (WP)

Referent candidates

(WP)

NameProjectTypeReference
Sylvain BennerSpacemacsCommunity-driven Emacs distribution[5]
Vitalik ButerinEthereumBlockchain-based cryptocurrency[6]
Dries BuytaertDrupalContent management framework[7]
Haoyuan LiAlluxioData Orchestration System[8]
Evan CzaplickiElmFront-end web programming language[9][10]
David Heinemeier HanssonRuby on RailsWeb framework[11]
Rich HickeyClojureProgramming language[12]
Adrian Holovaty
and Jacob Kaplan-Moss
DjangoWeb framework[13]
Laurent DestailleurDolibarr ERP CRMSoftware suite for Enterprise Resource Planning and Customer Relationship Management[14]
Francois CholletKerasDeep learning framework[15]
Xavier LeroyOCamlProgramming language[16][17]
Yukihiro Matsumoto (Matz)RubyProgramming language[18]
Wes McKinneyPandasPython data analysis library[19]
Bram MoolenaarVimText editor[20]
Matt Mullenweg [a]WordPressContent management framework[21]
Martin OderskyScalaProgramming language[22]
Taylor OtwellLaravelWeb framework[23][24]
Theo de RaadtOpenBSDUnix-like operating system[citation needed]
Ton Roosendaal[b]Blender3D computer graphics software[25]
Sébastien RosOrchard ProjectContent management system[26]
Mark Shuttleworth[c]UbuntuLinux distribution[27]
Don Syme[d]F#Programming language[28]
Linus Torvalds[e]LinuxOperating system kernel[11][29]
José ValimElixirProgramming language[30]
Pauli VirtanenSciPyPython library used for scientific and technical computing[31][32]
Patrick VolkerdingSlackwareGNU/Linux distribution[33]
Nathan VoxlandLiquibaseDatabase schema management[34]
Shaun WalkerDotNetNukeWeb application framework[35]
Larry WallPerlProgramming language[36]
Jeremy Soller[37]RedoxOperating system[38]
Eugen RochkoMastodonOpen source, decentralized social network[39]
Dylan ArapsKISS LinuxA bare-bones Linux distribution based on musl libc and BusyBox[40]
Gavin Mendel-Gleason[f]TerminusDBOpen-source graph database for knowledge graph representation[41][42]

Organizational Positions

  1. ^ Lead Developer at the WordPress Foundation
  2. ^ Chairman of the Blender Foundation
  3. ^ Until December 2009, CEO of Canonical Ltd
  4. ^ Technical Advisor at the F# Software Foundation
  5. ^ Sponsee of the Linux Foundation. Also holds the trademark for Linux
  6. ^ CTO of TerminusDB

(WP)

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Categories
Python Software Engineering

Python Conference (PyCon)

See also: Python, Python Bibliography and Bibliography of Python Libraries and Web Frameworks, Python Programming Courses

“The Python Conference (also called PyCon[1]:564) is the largest[2][3] annual convention for the discussion and promotion of the Python programming language.[4][5] It originated in the United States but is also held in more than 40 other countries.[6][7][8] It was one of the first computer programming conferences to develop and adhere to a code of conduct.[1]:565 The conference hosts tutorials, demonstrations and training sessions.[9](WP)

“PyCon 2020 was listed as (one of) “The best software engineering conferences (to attend) of 2020” and “As Python becomes ever more popular in the scientific community and for big data, the influence of PyCon will continue to grow.”[10] PyCon is often attended by Guido van Rossum (the creator of the Python language).[2][11] It is often referred to in published articles.[13][14](WP)

“It is organized by the Python Software Foundation, and is supported by many significant companies, including Microsoft,[15][16] Google,[17] and Facebook.[18]” (WP)

Sources:

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Categories
Python Software Engineering

Guido van Rossum – Python Creator

See also: Python, Python Bibliography and Bibliography of Python Libraries and Web Frameworks, Python Programming Courses

Guido van Rossum (Dutch: [ˈɣido vɑn ˈrɔsʏm, -səm]; born 31 January 1956) is a Dutch programmer best known as the creator of the Python programming language, for which he was the “Benevolent dictator for life” (BDFL) until he stepped down from the position in July 2018.[5][6] He remained a member of the Python Steering Council through 2019, and withdrew from nominations for the 2020 election.[7]” (WP)

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Categories
Bibliography Python Software Engineering

Head First Python: A Brain-Friendly Guide

See also: Python, Python Bibliography and Bibliography of Python Libraries and Web Frameworks

See: Head First Python: A Brain-Friendly Guide, by Paul Barry, B01N0GU0OC (HFPy)

Fair Use Source: B01N0GU0OC (HFPy)

About This Book:

Want to learn the Python language without slogging your way through how-to manuals? With Head First Python, you’ll quickly grasp Python’s fundamentals, working with the built-in data structures and functions. Then you’ll move on to building your very own webapp, exploring database management, exception handling, and data wrangling. If you’re intrigued by what you can do with context managers, decorators, comprehensions, and generators, it’s all here. This second edition is a complete learning experience that will help you become a bonafide Python programmer in no time.

Why does this book look so different? Based on the latest research in cognitive science and learning theory, Head First Pythonuses a visually rich format to engage your mind, rather than a text-heavy approach that puts you to sleep. Why waste your time struggling with new concepts? This multi-sensory learning experience is designed for the way your brain really works.

About ‘Head First’ Books

We think of a Head First Reader as a Learner

Learning isn’t something that just happens to you. It’s something you do. You can’t learn without pumping some neurons. Learning means building more mental pathways, bridging connections between new and pre-existing knowledge, recognizing patterns, and turning facts and information into knowledge (and ultimately, wisdom). Based on the latest research in cognitive science, neurobiology, and educational psychology, Head First books get your brain into learning mode.

Here’s how we help you do that:

We tell stories using casual language, instead of lecturing. We don’t take ourselves too seriously. Which would you pay more attention to: a stimulating dinner party companion, or a lecture?

We make it visual. Images are far more memorable than words alone, and make learning much more effective. They also make things more fun.

We use attention-grabbing tactics. Learning a new, tough, technical topic doesn’t have to be boring. The graphics are often surprising, oversized, humorous, sarcastic, or edgy. The page layout is dynamic: no two pages are the same, and each one has a mix of text and images.

Metacognition: thinking about thinking

If you really want to learn, and you want to learn more quickly and more deeply, pay attention to how you pay attention. Think about how you think. The trick is to get your brain to see the new material you’re learning as Really Important. Crucial to your well-being. Otherwise, you’re in for a constant battle, with your brain doing its best to keep the new content from sticking.

If you answer ‘yes’ to all of these, this book is for you

  • Do you already know how to program in another programming language?
  • Do you wish you had the know-how to program Python, add it to your list of tools, and make it do new things?
  • Do you prefer actually doing things and applying the stuff you learn over listening to someone in a lecture rattle on for hours on end?
Here’s what we do:

We use pictures, because your brain is tuned for visuals, not text. As far as your brain’s concerned, a picture really is worth a thousand words. And when text and pictures work together, we embedded the text in the pictures because your brain works more effectively when the text is within the thing the text refers to, as opposed to in a caption or buried in the text somewhere.

We use redundancy, saying the same thing in different ways and with different media types, and multiple senses, to increase the chance that the content gets coded into more than one area of your brain.

We use concepts and pictures in unexpected ways because your brain is tuned for novelty, and we use pictures and ideas with at least some emotional content, because your brain is more likely to remember when you feel something.

We use a personalized, conversational style, because your brain is tuned to pay more attention when it believes you’re in a conversation than if it thinks you’re passively listening to a presentation.

We include many activities, because your brain is tuned to learn and remember more when you do things than when you read about things. And we make the exercises challenging-yet-do-able, because that’s what most people prefer.

We use multiple learning styles, because you might prefer step-by-step procedures, while someone else wants to understand the big picture first, and someone else just wants to see an example. But regardless of your own learning preference, everyone benefits from seeing the same content represented in multiple ways.

We include content for both sides of your brain, because the more of your brain you engage, the more likely you are to learn and remember, and the longer you can stay focused. Since working one side of the brain often means giving the other side a chance to rest, you can be more productive at learning for a longer period of time.

We include challenges by asking questions that don’t always have a straight answer, because your brain is tuned to learn and remember when it has to work at something.

Finally, we use people in our stories, examples, and pictures, because, well, you’re a person. Your brain pays more attention to people than to things.

About the Author:

Paul Barry is formally educated and trained in Computer Science and holds a Masters Degree in Computing Science. He has been programming professionally, on and off, for close to 25 years. Paul already has two textbooks to his name, and is also a Contributing Editor to Linux Journal magazine. His day job is with the Institute of Technology, Carlow in Ireland where he has spent over a decade preparing Ireland’s next generation of computing folk to be productive in the workforce. His role as a third level educator affords him the opportunity to explore, learn and teach the very latest programming technologies and practices, which is something that he enjoys even though he knows this makes him a bonafide “geek”. Paul lives just outside the town of Carlow in Ireland with his wife, two sons, daughter, dog and cat. There’s a bunch of computers and a growing collection of music instruments in the house, too (and like a lot of the Head First family, Paul is a struggling guitarist trapped inside a geek’s body). He has so far resisted any suggestion that the family acquire a hamster … or a set of drums.

Book Details:

  • ASIN: B01N0GU0OC
  • ISBN-10: 1491919531
  • ISBN-13: 978-1491919538
  • Publisher: O’Reilly Media; 2nd edition (November 21, 2016)
  • Publication date: November 21, 2016
  • Print length: 983 pages

Table of Contents:

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Bibliography

B01N0GU0OC

See: Head First Python: A Brain-Friendly Guide, by Paul Barry

Fair Use Source: B01N0GU0OC (HFPy)

Categories
Bibliography Python Software Engineering

Introducing Python: Modern Computing in Simple Packages, by Bill Lubanovic

See also: Python, Python Bibliography and Bibliography of Python Libraries and Web Frameworks

See: Introducing Python: Modern Computing in Simple Packages, by Bill Lubanovic, 2020, B0815R5543 (IPyBLub)

Fair Use Source: B0815R5543 (IPyBLub)

About This Book:

Easy to understand and fun to read, this updated edition of Introducing Python is ideal for beginning programmers as well as those new to the language. Author Bill Lubanovic takes you from the basics to more involved and varied topics, mixing tutorials with cookbook-style code recipes to explain concepts in Python 3. End-of-chapter exercises help you practice what you’ve learned.

You’ll gain a strong foundation in the language, including best practices for testing, debugging, code reuse, and other development tips. This book also shows you how to use Python for applications in business, science, and the arts, using various Python tools and open source packages.

About the Author:

Bill Lubanovic has developed software with UNIX since 1977, GUIs since 1981, databases since 1990, and the Web since 1993. Recently, he developed core services and distributed systems with a remote team for a Manhattan startup. Currently, he’s integrating OpenStack services for a supercomputer company.

Book Details:

  • ASIN: B0815R5543
  • ISBN-10: 1492051365
  • ISBN-13: 978-1492051367
  • Publisher: O’Reilly Media; 2nd edition (November 6, 2019)
  • Publication date: November 6, 2019
  • Print length: 960 pages

Table of Contents:

Preface Audience

Changes in the Second Edition

Outline

Python Versions

Conventions Used in This Book

Using Code Examples

O’Reilly Online Learning

How to Contact Us

Acknowledgments

I. Python Basics

  1. A Taste of Py Mysteries

Little Programs

A Bigger Program

Python in the Real World

Python Versus the Language from Planet X

Why Python?

Why Not Python?

Python 2 Versus Python 3

Installing Python

Running Python Using the Interactive Interpreter

Using Python Files

What’s Next?

Your Moment of Zen

Coming Up

Things to Do

  1. Data: Types, Values, Variables, and Names Python Data Are Objects

Types

Mutability

Literal Values

Variables

Assignment

Variables Are Names, Not Places

Assigning to Multiple Names

Reassigning a Name

Copying

Choose Good Variable Names

Coming Up

Things to Do

  1. Numbers Booleans

Integers Literal Integers

Integer Operations

Integers and Variables

Precedence

Bases

Type Conversions

How Big Is an int?

Floats

Math Functions

Coming Up

Things to Do

  1. Choose with if Comment with #

Continue Lines with \

Compare with if, elif, and else

What Is True?

Do Multiple Comparisons with in

New: I Am the Walrus

Coming Up

Things to Do

  1. Text Strings Create with Quotes

Create with str()

Escape with \

Combine by Using +

Duplicate with *

Get a Character with []

Get a Substring with a Slice

Get Length with len()

Split with split()

Combine by Using join()

Substitute by Using replace()

Strip with strip()

Search and Select

Case

Alignment

Formatting Old style: %

New style: {} and format()

Newest Style: f-strings

More String Things

Coming Up

Things to Do

  1. Loop with while and for Repeat with while Cancel with break

Skip Ahead with continue

Check break Use with else

Iterate with for and in Cancel with break

Skip with continue

Check break Use with else

Generate Number Sequences with range()

Other Iterators

Coming Up

Things to Do

  1. Tuples and Lists Tuples Create with Commas and ()

Create with tuple()

Combine Tuples by Using +

Duplicate Items with *

Compare Tuples

Iterate with for and in

Modify a Tuple

Lists Create with []

Create or Convert with list()

Create from a String with split()

Get an Item by [ offset ]

Get Items with a Slice

Add an Item to the End with append()

Add an Item by Offset with insert()

Duplicate All Items with *

Combine Lists by Using extend() or +

Change an Item by [ offset ]

Change Items with a Slice

Delete an Item by Offset with del

Delete an Item by Value with remove()

Get an Item by Offset and Delete It with pop()

Delete All Items with clear()

Find an Item’s Offset by Value with index()

Test for a Value with in

Count Occurrences of a Value with count()

Convert a List to a String with join()

Reorder Items with sort() or sorted()

Get Length with len()

Assign with =

Copy with copy(), list(), or a Slice

Copy Everything with deepcopy()

Compare Lists

Iterate with for and in

Iterate Multiple Sequences with zip()

Create a List with a Comprehension

Lists of Lists

Tuples Versus Lists

There Are No Tuple Comprehensions

Coming Up

Things to Do

  1. Dictionaries and Sets Dictionaries Create with {}

Create with dict()

Convert with dict()

Add or Change an Item by [ key ]

Get an Item by [key] or with get()

Get All Keys with keys()

Get All Values with values()

Get All Key-Value Pairs with items()

Get Length with len()

Combine Dictionaries with {**a, **b}

Combine Dictionaries with update()

Delete an Item by Key with del

Get an Item by Key and Delete It with pop()

Delete All Items with clear()

Test for a Key with in

Assign with =

Copy with copy()

Copy Everything with deepcopy()

Compare Dictionaries

Iterate with for and in

Dictionary Comprehensions

Sets Create with set()

Convert with set()

Get Length with len()

Add an Item with add()

Delete an Item with remove()

Iterate with for and in

Test for a Value with in

Combinations and Operators

Set Comprehensions

Create an Immutable Set with frozenset()

Data Structures So Far

Make Bigger Data Structures

Coming Up

Things to Do

  1. Functions Define a Function with def

Call a Function with Parentheses

Arguments and Parameters None Is Useful

Positional Arguments

Keyword Arguments

Specify Default Parameter Values

Explode/Gather Positional Arguments with *

Explode/Gather Keyword Arguments with **

Keyword-Only Arguments

Mutable and Immutable Arguments

Docstrings

Functions Are First-Class Citizens

Inner Functions Closures

Anonymous Functions: lambda

Generators Generator Functions

Generator Comprehensions

Decorators

Namespaces and Scope

Uses of _ and __ in Names

Recursion

Async Functions

Exceptions Handle Errors with try and except

Make Your Own Exceptions

Coming Up

Things to Do

  1. Oh Oh: Objects and Classes What Are Objects?

Simple Objects Define a Class with class

Attributes

Methods

Initialization

Inheritance Inherit from a Parent Class

Override a Method

Add a Method

Get Help from Your Parent with super()

Multiple Inheritance

Mixins

In self Defense

Attribute Access Direct Access

Getters and Setters

Properties for Attribute Access

Properties for Computed Values

Name Mangling for Privacy

Class and Object Attributes

Method Types Instance Methods

Class Methods

Static Methods

Duck Typing

Magic Methods

Aggregation and Composition

When to Use Objects or Something Else

Named Tuples

Dataclasses

Attrs

Coming Up

Things to Do

  1. Modules, Packages, and Goodies Modules and the import Statement Import a Module

Import a Module with Another Name

Import Only What You Want from a Module

Packages The Module Search Path

Relative and Absolute Imports

Namespace Packages

Modules Versus Objects

Goodies in the Python Standard Library Handle Missing Keys with setdefault() and defaultdict()

Count Items with Counter()

Order by Key with OrderedDict()

Stack + Queue == deque

Iterate over Code Structures with itertools

Print Nicely with pprint()

Get Random

More Batteries: Get Other Python Code

Coming Up

Things to Do

II. Python in Practice

  1. Wrangle and Mangle Data Text Strings: Unicode Python 3 Unicode Strings

UTF-8

Encode

Decode

HTML Entities

Normalization

For More Information

Text Strings: Regular Expressions Find Exact Beginning Match with match()

Find First Match with search()

Find All Matches with findall()

Split at Matches with split()

Replace at Matches with sub()

Patterns: Special Characters

Patterns: Using Specifiers

Patterns: Specifying match() Output

Binary Data bytes and bytearray

Convert Binary Data with struct

Other Binary Data Tools

Convert Bytes/Strings with binascii()

Bit Operators

A Jewelry Analogy

Coming Up

Things to Do

  1. Calendars and Clocks Leap Year

The datetime Module

Using the time Module

Read and Write Dates and Times

All the Conversions

Alternative Modules

Coming Up

Things to Do

  1. Files and Directories File Input and Output Create or Open with open()

Write a Text File with print()

Write a Text File with write()

Read a Text File with read(), readline(), or readlines()

Write a Binary File with write()

Read a Binary File with read()

Close Files Automatically by Using with

Change Position with seek()

Memory Mapping

File Operations Check Existence with exists()

Check Type with isfile()

Copy with copy()

Change Name with rename()

Link with link() or symlink()

Change Permissions with chmod()

Change Ownership with chown()

Delete a File with remove()

Directory Operations Create with mkdir()

Delete with rmdir()

List Contents with listdir()

Change Current Directory with chdir()

List Matching Files with glob()

Pathnames Get a Pathname with abspath()

Get a symlink Pathname with realpath()

Build a Pathname with os.path.join()

Use pathlib

BytesIO and StringIO

Coming Up

Things to Do

  1. Data in Time: Processes and Concurrency Programs and Processes Create a Process with subprocess

Create a Process with multiprocessing

Kill a Process with terminate()

Get System Info with os

Get Process Info with psutil

Command Automation Invoke

Other Command Helpers

Concurrency Queues

Processes

Threads

concurrent.futures

Green Threads and gevent

twisted

asyncio

Redis

Beyond Queues

Coming Up

Things to Do

  1. Data in a Box: Persistent Storage Flat Text Files

Padded Text Files

Tabular Text Files CSV

XML

An XML Security Note

HTML

JSON

YAML

Tablib

Pandas

Configuration Files

Binary Files Padded Binary Files and Memory Mapping

Spreadsheets

HDF5

TileDB

Relational Databases SQL

DB-API

SQLite

MySQL

PostgreSQL

SQLAlchemy

Other Database Access Packages

NoSQL Data Stores The dbm Family

Memcached

Redis

Document Databases

Time Series Databases

Graph Databases

Other NoSQL

Full-Text Databases

Coming Up

Things to Do

  1. Data in Space: Networks TCP/IP Sockets

Scapy

Netcat

Networking Patterns

The Request-Reply Pattern ZeroMQ

Other Messaging Tools

The Publish-Subscribe Pattern Redis

ZeroMQ

Other Pub-Sub Tools

Internet Services Domain Name System

Python Email Modules

Other Protocols

Web Services and APIs

Data Serialization Serialize with pickle

Other Serialization Formats

Remote Procedure Calls XML RPC

JSON RPC

MessagePack RPC

Zerorpc

gRPC

Twirp

Remote Management Tools

Big Fat Data Hadoop

Spark

Disco

Dask

Clouds Amazon Web Services

Google Cloud

Microsoft Azure

OpenStack

Docker Kubernetes

Coming Up

Things to Do

  1. The Web, Untangled Web Clients Test with telnet

Test with curl

Test with httpie

Test with httpbin

Python’s Standard Web Libraries

Beyond the Standard Library: requests

Web Servers The Simplest Python Web Server

Web Server Gateway Interface (WSGI)

ASGI

Apache

NGINX

Other Python Web Servers

Web Server Frameworks Bottle

Flask

Django

Other Frameworks

Database Frameworks

Web Services and Automation webbrowser

webview

Web APIs and REST

Crawl and Scrape Scrapy

BeautifulSoup

Requests-HTML

Let’s Watch a Movie

Coming Up

Things to Do

  1. Be a Pythonista About Programming

Find Python Code

Install Packages Use pip

Use virtualenv

Use pipenv

Use a Package Manager

Install from Source

Integrated Development Environments IDLE

PyCharm

IPython

Jupyter Notebook

JupyterLab

Name and Document

Add Type Hints

Test Check with pylint, pyflakes, flake8, or pep8

Test with unittest

Test with doctest

Test with nose

Other Test Frameworks

Continuous Integration

Debug Python Code Use print()

Use Decorators

Use pdb

Use breakpoint()

Log Error Messages

Optimize Measure Timing

Algorithms and Data Structures

Cython, NumPy, and C Extensions

PyPy

Numba

Source Control Mercurial

Git

Distribute Your Programs

Clone This Book

How You Can Learn More Books

Websites

Groups

Conferences

Getting a Python Job

Coming Up

Things to Do

  1. Py Art 2-D Graphics Standard Library

PIL and Pillow

ImageMagick

3-D Graphics

3-D Animation

Graphical User Interfaces

Plots, Graphs, and Visualization Matplotlib

Seaborn

Bokeh

Games

Audio and Music

Coming Up

Things to Do

  1. Py at Work The Microsoft Office Suite

Carrying Out Business Tasks

Processing Business Data Extracting, Transforming, and Loading

Data Validation

Additional Sources of Information

Open Source Python Business Packages

Python in Finance

Business Data Security

Maps Formats

Draw a Map from a Shapefile

Geopandas

Other Mapping Packages

Applications and Data

Coming Up

Things to Do

  1. Py Sci Math and Statistics in the Standard Library Math Functions

Working with Complex Numbers

Calculate Accurate Floating Point with decimal

Perform Rational Arithmetic with fractions

Use Packed Sequences with array

Handling Simple Stats with statistics

Matrix Multiplication

Scientific Python

NumPy Make an Array with array()

Make an Array with arange()

Make an Array with zeros(), ones(), or random()

Change an Array’s Shape with reshape()

Get an Element with []

Array Math

Linear Algebra

SciPy

SciKit

Pandas

Python and Scientific Areas

Coming Up

Things to Do

A. Hardware and Software for Beginning Programmers Hardware Caveman Computers

Electricity

Inventions

An Idealized Computer

The CPU

Memory and Caches

Storage

Inputs

Outputs

Relative Access Times

Software In the Beginning Was the Bit

Machine Language

Assembler

Higher-Level Languages

Operating Systems

Virtual Machines

Containers

Distributed Computing and Networks

The Cloud

Kubernetes

B. Install Python 3 Check Your Python Version

Install Standard Python macOS

Windows

Linux or Unix

Install the pip Package Manager

Install virtualenv

Other Packaging Solutions

Install Anaconda Install Anaconda’s Package Manager conda

C. Something Completely Different: Async Coroutines and Event Loops

Asyncio Alternatives

Async Versus…

Async Frameworks and Servers

D. Answers to Exercises 1. A Taste of Py

  1. Data: Types, Values, Variables, and Names
  2. Numbers
  3. Choose with if
  4. Text Strings
  5. Loop with while and for
  6. Tuples and Lists
  7. Dictionaries
  8. Functions
  9. Oh Oh: Objects and Classes
  10. Modules, Packages, and Goodies
  11. Wrangle and Mangle Data
  12. Calendars and Clocks
  13. Files and Directories
  14. Data in Time: Processes and Concurrency
  15. Data in a Box: Persistent Storage
  16. Data in Space: Networks
  17. The Web, Untangled
  18. Be a Pythonista
  19. Py Art
  20. Py at Work
  21. PySci

E. Cheat Sheets Operator Precedence

String Methods Change Case

Search

Modify

Format

String Type

String Module Attributes

Coda

Index

Preface:

“As the title promises, this book will introduce you to one of the world’s most popular programming languages: Python. It’s aimed at beginning programmers as well as more experienced programmers who want to add Python to the languages they already know.” (IPyBLub)

“In most cases, it’s easier to learn a computer language than a human language. There’s less ambiguity and fewer exceptions to keep in your head. Python is one of the most consistent and clear computer languages. It balances ease of learning, ease of use, and expressive power.” (IPyBLub)

“Computer languages are made of data (like nouns in spoken languages) and instructions or code (like verbs). You need both. In alternating chapters, you’ll be introduced to Python’s basic code and data structures, learn how to combine them, and build up to more advanced ones. The programs that you read and write will get longer and more complex. Using a woodworking analogy, we’ll start with a hammer, nails, and scraps of wood. Over the first half of this book, we’ll introduce more specialized components, up to the equivalents of lathes and other power tools.” (IPyBLub)

“You’ll not only learn the language, but also what to do with it. We’ll begin with the Python language and its “batteries included” standard library, but I’ll also show you how to find, download, install, and use some good third-party packages. My emphasis is on whatever I’ve actually found useful in more than 10 years of production Python development, rather than fringe topics or complex hacks.” (IPyBLub)

“Although this is an introduction, some advanced topics are included because I want to expose them to you. Areas like databases and the web are still covered, but technology changes fast. A Python programmer might now be expected to know something about cloud computing, machine learning, or event streaming. You’ll find something here on all of these.” (IPyBLub)

“Python has some special features that work better than adapting styles from other languages that you may know. For example, using for and iterators is a more direct way of making a loop than manually incrementing some counter variable.” (IPyBLub)

“When you’re learning something new, it’s hard to tell which terms are specific instead of colloquial, and which concepts are actually important. In other words, “Is this on the test?” I’ll highlight terms and ideas that have specific meaning or importance in Python, but not too many at once. Real Python code is included early and often.” (IPyBLub)

Note: “I’ll include a note such as this when something might be confusing, or if there’s a more appropriate Pythonic way to do it.” (IPyBLub)

“Python isn’t perfect. I’ll show you things that seem odd or that should be avoided — and offer alternatives you can use, instead.” (IPyBLub)

“Now and then, my opinions on some subjects (such as object inheritance, or MVC and REST designs for the web) may vary a bit from the common wisdom. See what you think.” (IPyBLub)

Audience:

“This book is for anybody interested in learning one of the world’s most popular computing languages, regardless of whether you have previously learned any programming.” (IPyBLub)

Changes in the Second Edition:

“What’s changed since the first edition?

About a hundred more pages, including cat pictures.

Twice the chapters, each shorter now.

An early chapter devoted to data types, variables, and names.

New standard Python features like f-strings.

New or improved third-party packages.

New code examples throughout.

An appendix on basic hardware and software, for new programmers.

An appendix on asyncio, for not-so-new programmers.

“New stack” coverage: containers, clouds, data science, and machine learning.

Hints on getting a job programming in Python.

What hasn’t changed? Examples using bad poetry and ducks. These are evergreen.” (IPyBLub)

Outline:

“Part I (Chapters 1–11) explains Python’s basics. You should read these chapters in order. I work up from the simplest data and code structures, combining them on the way into more detailed and realistic programs. Part II (Chapters 12–22) shows how Python is used in specific application areas such as the web, databases, networks, and so on; read these chapters in any order you like.” (IPyBLub)

“Here’s a brief preview of the chapters and appendixes, including some of the terms that you’ll run into there:” (IPyBLub)

Chapter 1, A Taste of Py

“Computer programs are not that different from directions that you see every day. Some little Python programs give you a glimpse of the language’s looks, capabilities, and uses in the real world. You’ll see how to run a Python program within its interactive interpreter (or shell), or from a text file saved on your computer.” (IPyBLub)

Chapter 2, Data: Types, Values, Variables, and Names

“Computer languages mix data and instructions. Different types of data are stored and treated differently by the computer. They may allow their values to be changed (mutable) or not (immutable). In a Python program, data can be literal (numbers like 78, text strings like “waffle”) or represented by named variables. Python treats variables like names, which is different from many other languages and has some important consequences.” (IPyBLub)

Chapter 3, Numbers

“This chapter shows Python’s simplest data types: booleans, integers, and floating-point numbers. You’ll also learn the basic math operations. The examples use Python’s interactive interpreter like a calculator.” (IPyBLub)

Chapter 4, Choose with if

“We’ll bounce between Python’s nouns (data types) and verbs (program structures) for a few chapters. Python code normally runs a line at a time, from the start to the end of a program. The if code structure lets you run different lines of code, depending on some data comparison.” (IPyBLub)

Chapter 5, Text Strings

“Back to nouns, and the world of text strings. Learn how to create, combine, change, retrieve, and print strings.” (IPyBLub)

Chapter 6, Loop with while and for

“Verbs again, and two ways to make a loop: for and while. You’ll be introduced to a core Python concept: iterators.” (IPyBLub)

Chapter 7, Tuples and Lists

“It’s time for the first of Python’s higher-level built-in data structures: lists and tuples. These are sequences of values, like LEGO for building much more complex data structures. Step through them with iterators, and build lists quickly with comprehensions.” (IPyBLub)

Chapter 8, Dictionaries and Sets

“Dictionaries (aka dicts) and sets let you save data by their values rather than their position. This turns out to be very handy and will be among your favorite Python features.” (IPyBLub)

Chapter 9, Functions

“Weave the data and code structures of the previous chapters to compare, choose, or repeat. Package code in functions and handle errors with exceptions.” (IPyBLub)

Chapter 10, Oh Oh: Objects and Classes

“The word object is a bit fuzzy, but important in many computer languages, including Python. If you’ve done object-oriented programming in other languages, Python is a bit more relaxed. This chapter explains how to use objects and classes, and when it’s better to use alternatives.” (IPyBLub)

Chapter 11, Modules, Packages, and Goodies

“This chapter demonstrates how to scale out to larger code structures: modules, packages, and programs. You’ll see where to put code and data, how to get data in and out, handle options, tour the Python Standard Library, and take a glance at what lies beyond.” (IPyBLub)

Chapter 12, Wrangle and Mangle Data

“Learn to manage (or mangle) data like a pro. This chapter is all about text and binary data, joy with Unicode characters, and regex text searching. It also introduces the data types bytes and bytearray, counterparts of strings that contain raw binary values instead of text characters.” (IPyBLub)

Chapter 13, Calendars and Clocks

“Dates and times can be messy to handle. This chapter shows common problems and useful solutions.” (IPyBLub)

Chapter 14, Files and Directories

“Basic data storage uses files and directories. This chapter shows you how to create and use them.” (IPyBLub)

Chapter 15, Data in Time: Processes and Concurrency

“This is the first hard-core system chapter. Its theme is data in time — how to use programs, processes, and threads to do more things at a time (concurrency). Python’s recent async additions are mentioned, with details in Appendix C.” (IPyBLub)

Chapter 16, Data in a Box: Persistent Storage

“Data can be stored and retrieved with basic flat files and directories within filesystems. They gain some structure with common text formats such as CSV, JSON, and XML. As data get larger and more complex, they need the services of databases — traditional relational ones, and some newer NoSQL data stores.” (IPyBLub)

Chapter 17, Data in Space: Networks

“Send your code and data through space in networks with services, protocols, and APIs. Examples range from low-level TCP sockets, to messaging libraries and queuing systems, to cloud deployment.” (IPyBLub)

Chapter 18, The Web, Untangled

“The web gets its own chapter — clients, servers, APIs, and frameworks. You’ll crawl and scrape websites, and then build real websites with request parameters and templates.” (IPyBLub)

Chapter 19, Be a Pythonista

“This chapter contains tips for Python developers — installation with pip and virtualenv, using IDEs, testing, debugging, logging, source control, and documentation. It also helps you to find and install useful third-party packages, package your own code for reuse, and learn where to get more information.” (IPyBLub)

Chapter 20, Py Art

“People are doing cool things with Python in the arts: graphics, music, animation, and games.” (IPyBLub)

Chapter 21, Py at Work

“Python has specific applications for business: data visualization (plots, graphs, and maps), security, and regulation.” (IPyBLub)

Chapter 22, Py Sci

“In the past few years, Python has emerged as a top language for science: math and statistics, physical science, bioscience, and medicine. Data science and machine learning are notable strengths. This chapter touches on NumPy, SciPy, and Pandas.” (IPyBLub)

Appendix A, Hardware and Software for Beginning Programmers

“If you’re fairly new to programming, this describes how hardware and software actually work. It introduces some terms that you’ll keep running into.” (IPyBLub)

Appendix B, Install Python 3

“If you don’t already have Python 3 on your computer, this appendix shows you how to install it, whether you’re running Windows, macOS, Linux, or some other variant of Unix.” (IPyBLub)

Appendix C, Something Completely Different: Async

“Python has been adding asynchronous features in different releases, and they’re not easy to understand. I mention them as they come up in various chapters, but save a detailed discussion for this appendix.” (IPyBLub)

Appendix D, Answers to Exercises

“This has the answers to the end-of-chapter exercises. Don’t peek here until you’ve tried the exercises yourself, or you might be turned into a newt.” (IPyBLub)

Appendix E, Cheat Sheets

“This appendix contains cheat sheets to use as a quick reference.” (IPyBLub)

Sources:

Fair Use Sources:

Categories
Bibliography

B0815R5543

See: Introducing Python: Modern Computing in Simple Packages, by Bill Lubanovic

Fair Use Source: B0815R5543 (IPyBLub)