Category Archives: Python

Ultimate Python Ebook Collection

MongoDB and Python: Patterns and processes for the popular document-oriented database

Niall O’Higgins, “MongoDB and Python: Patterns and processes for the popular document-oriented database”
O’Reilly Media | 2011-09-30 | ISBN: 1449310370 | 68 pages | PDF | 4,5 MB

Learn how to leverage MongoDB with your Python applications, using the hands-on recipes in this book. You get complete code samples for tasks such as making fast geo queries for location-based apps, efficiently indexing your user documents for social-graph lookups, and many other scenarios.

This guide explains the basics of the document-oriented database and shows you how to set up a Python environment with it. Learn how to read and write to MongoDB, apply idiomatic MongoDB and Python patterns, and use the database with several popular Python web frameworks. You’ll discover how to model your data, write effective queries, and avoid concurrency problems such as race conditions and deadlocks.

The recipes will help you:

-Read, write, count, and sort documents in a MongoDB collection
-Learn how to use the rich MongoDB query language
-Maintain data integrity in replicated/distributed MongoDB environments
-Use embedding to efficiently model your data without joins
-Code defensively to avoid keyerrors and other bugs
-Apply atomic operations to update game scores, billing systems, and more with the fast accounting pattern
-Use MongoDB with the Pylons 1.x, Django, and Pyramid web frameworks


Starting Out with Python, 2nd Edition

About the Book

In “Starting Out with Python(R), Second Edition” Tony Gaddis’ evenly-paced, accessible coverage introduces students to the basics of programming and prepares them to transition into more complicated languages. Python, an easy-to-learn and increasingly popular object-oriented language, allows readers to become comfortable with the fundamentals of programming without the troublesome syntax that can be challenging for novices. With the knowledge acquired using Python, students gain confidence in their skills and learn to recognize the logic behind developing high-quality programs.
“Starting Out with Python” discusses control structures, functions, arrays, and pointers before objects and classes. As with all Gaddis texts, clear and easy-to-read code listings, concise and practical real-world examples, detail-oriented explanations, and an abundance of exercises appear in every chapter. This text is intended for a one-semester introductory programming course for students with limited programming experience.



The Quick Python Book Second Edition

pdf | 362 pages | 4.4 Mb

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I’ve been coding in Python for a number of years, longer than any other language I’ve ever used. I use Python for system administration, for web applications, for database management, and sometimes just to help myself think clearly.

To be honest, I’m sometimes a little surprised that Python has worn so well. Based on my earlier experience, I would have expected that by now some other language would have come along that was faster, cooler, sexier, whatever. Indeed, other languages have come along, but none that helped me do what I needed to do quite as effectively as Python. In fact, the more I use Python and the more I understand it, the more I feel the quality of my programming improve and mature.

This is a second edition, and my mantra in updating has been, “If it ain’t broke, don’t fix it.” Much of the content has been freshened for Python 3 but is largely as written in the first edition. Of course, the world of Python has changed since Python 1.5, so in several places I’ve had to make significant changes or add new material. On those occasions I’ve done my best to make the new material compatible with the clear and low-key style of the original.

For me, the aim of this book is to share the positive experiences I’ve gotten from coding in Python by introducing people to Python 3, the latest and, in my opinion, the best version of Python to date. May your journey be as satisfying as mine has been.


Starting out with Python

pdf | 502 pages | 33.8 Mb

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The History of Programming Languages

Before 1940

The first programming languages predate the modern computer. At first, the languages were codes.
The Jacquard loom, invented in 1801, used holes in punched cards to represent sewing loom arm movements in order to generate decorative patterns automatically.

During a nine-month period in 1842-1843, Ada Lovelace translated the memoir of Italian mathematician Luigi Menabrea about Charles Babbage’s newest proposed machine, the Analytical Engine. With the article, she appended a set of notes which specified in complete detail a method for calculating Bernoulli numbers with the Engine, recognized by some historians as the world’s first computer program

The 1940s

In the 1940s the first recognizably modern, electrically powered computers were created. The limited speed and memory capacity forced programmers to write hand tuned assembly language programs. It was soon discovered that programming in assembly language required a great deal of intellectual effort and was error-prone.
In 1945, Konrad Zuse published details of his programming language Plankalkül. However, it was not implemented in his time and his original contributions were isolated from other developments because Germany was isolated during the war.
Some important languages that were developed in this time period include:

  • 1943 – Plankalkül (Konrad Zuse)
  • 1943 – ENIAC coding system
  • 1949 – C-10

The 1950s and 1960s

In the 1950s the first three modern programming languages whose descendants are still in widespread use today were designed:

  • FORTRAN, the “FORmula TRANslator”, invented by John W. Backus et al.;
  • LISP, the “LISt Processor”, invented by John McCarthy et al.;
  • COBOL, the COmmon Business Oriented Language, created by the Short Range Committee, heavily influenced by Grace Hopper.

Another milestone in the late 1950s was the publication, by a committee of American and European computer scientists, of “a new language for algorithms”; the Algol 60 Report (the “ALGOrithmic Language”). This report consolidated many ideas circulating at the time and featured two key innovations:

  • The use of Backus-Naur Form (BNF) for describing the language’s syntax. Nearly all subsequent programming languages have used a variant of BNF to describe the context-free portion of their syntax.
  • The introduction of lexical scoping for names in arbitrarily nested scopes.

Algol 60 was particularly influential in the design of later languages, some of which soon became more popular. The Burroughs B5000 was designed to be programmed in an extended subset of Algol.
Some important languages that were developed in this time period include:

  • 1951 – Regional Assembly Language
  • 1952 – Autocode
  • 1954 – FORTRAN
  • 1958 – LISP
  • 1958 – ALGOL
  • 1959 – COBOL
  • 1962 – APL
  • 1962 – Simula
  • 1964 – BASIC
  • 1964 – PL/I 


1967-1978: establishing fundamental paradigms

The period from the late 1960s to the late 1970s brought a major flowering of programming languages. Most of the major language paradigms now in use were invented in this period:

  • Simula, invented in the late 1960s by Nygaard and Dahl as a superset of Algol 60, was the first language designed to support object-oriented programming. Smalltalk (mid 1970s) provided a complete ground-up design of an object-oriented language.
  • C, an early systems programming language, was developed by Dennis Ritchie and Ken Thompson at Bell Labs between 1969 and 1973.
  • Prolog, designed in 1972 by Colmerauer, Roussel, and Kowalski, was the first logic programming language.
  • ML built a polymorphic type system (invented by Robin Milner in 1978) on top of Lisp, pioneering statically typed functional programming languages.

Each of these languages spawned an entire family of descendants, and most modern languages count at least one of them in their ancestry.
The 1960s and 1970s also saw considerable debate over the merits of “structured programming”, which essentially meant programming without the use of GOTO. This debate was closely related to language design: some languages did not include GOTO, which forced structured programming on the programmer. Although the debate raged hotly at the time, nearly all programmers now agree that, even in languages that provide GOTO, it is bad style to use it except in rare circumstances. As a result, later generations of language designers have found the structured programming debate tedious and even bewildering.
Some important languages that were developed in this time period include:

  • 1970 – Pascal
  • 1972 – C
  • 1972 – Smalltalk
  • 1972 – Prolog
  • 1973 – ML
  • 1978 – SQL

The 1980s: consolidation, modules, performance

The 1980s were years of relative consolidation. C++ combined object-oriented and systems programming. The United States government standardized Ada, a systems programming language intended for use by defense contractors. In Japan and elsewhere, vast sums were spent investigating so-called “fifth generation” languages that incorporated logic programming constructs. The functional languages community moved to standardize ML and Lisp. Rather than inventing new paradigms, all of these movements elaborated upon the ideas invented in the previous decade.
However, one important new trend in language design was an increased focus on programming for large-scale systems through the use of modules, or large-scale organizational units of code. Modula, Ada, and ML all developed notable module systems in the 1980s. Module systems were often wedded to generic programming constructs—generics being, in essence, parameterized modules (see also parametric polymorphism).
Although major new paradigms for programming languages did not appear, many researchers expanded on the ideas of prior languages and adapted them to new contexts. For example, the languages of the Argus and Emerald systems adapted object-oriented programming to distributed systems.
The 1980s also brought advances in programming language implementation. The RISC movement in computer architecture postulated that hardware should be designed for compilers rather than for human assembly programmers. Aided by processor speed improvements that enabled increasingly aggressive compilation techniques, the RISC movement sparked greater interest in compilation technology for high-level languages.
Language technology continued along these lines well into the 1990s. However, the adoption of languages has always been driven by the adoption of new computer systems, and in the mid-1990s one of the most important new systems in computer history suddenly exploded in popularity.
Some important languages that were developed in this time period include:

  • 1983 – Ada
  • 1983 – C++
  • 1985 – Eiffel
  • 1987 – Perl
  • 1989 – FL (Backus)

The 1990s: the Internet age

The rapid growth of the Internet in the mid-1990s was the next major historic event in programming languages. By opening up a radically new platform for computer systems, the Internet created an opportunity for new languages to be adopted. In particular, the Java programming language rose to popularity because of its early integration with the Netscape Navigator web browser, and various scripting languages achieved widespread use in developing customized applications for web servers. Neither of these developments represented much fundamental novelty in language design; for example, the design of Java was a more conservative version of ideas explored many years earlier in the Smalltalk community, but the widespread adoption of languages that supported features like garbage collection and strong static typing was a major change in programming practice.
Some important languages that were developed in this time period include:

  • 1990 – Haskell
  • 1990 – Python
  • 1991 – Java
  • 1993 – Ruby
  • 1994 – PHP
  • 2000 – C#

Programming language evolution continues………


Importance of Computer Programming

Importance of Computer Programmingthumbnail
Computer programming has numerous benefits.


Developing a program involves a series of steps. The programmer defines a problem, plans a solution, codes the program, tests the program and, finally, documents the program. Usually, the programmer defines what he knows and the objective, selects a program to use, debugs the program in stages after completion to ensure no errors are introduced and then documents the design, development and testing of the program. With the ever-changing face of computer technology, programming is an exciting and always challenging environment that few programmers ever dream of leaving.

Systems Knowledge

Computer programmers have a full understanding of the how and why of computer systems, including system limitations, and can set realistic expectations and work around those limitations to fully maximize the use of the equipment and its accessories.

Creativity Platform

Programming is a platform to showcase creativity, especially in problem-solving and entertainment. Programming develops new video games, graphics and animations to showcase new business ideas or to resolve a particular problem.
Interactive Education

Programming, especially in web development, has allowed new interactive web applications that have access to system resources and provide the same level of control as desktop applications. Used on online learning platforms, these applications have allowed distance-learning programs to take off. Today, almost all major learning institutions have some form of online learning implementation, thanks to computer programming.

Defining The Future

Computer programming principles implemented today will likely influence how technologies such as voice-recognition, artificial intelligence and other sophisticated technologies will change in the future and how they will be applied to our day-to-day lives. For example, the trend toward automating Internet searches and purchases to be more localized is ongoing. While the hardware platforms developed will play a major role, computer technology will likely be at the centre of it all and programming future systems will be an important aspect.

Machine Language

Since computers work with numbers, programming allows a person to represent machine-language in human-readable format. This reduces the chances of introducing errors and wasted time in debugging and correcting mistakes.