[ PRACTICAL PYTHON PROGRAMMING ]

A comprehensive course for mastering the essential elements of Python programming and using it to solve real-world problems.

This course is also offered on an on-going basis in Chicago.

Overview

This course, designed for professional software developers, scientists, and engineers, is a comprehensive introduction to the Python programming language, standard library, and Python programming techniques. Although the course assumes no prior experience with Python, the course is strongly focused on practical applications including scripting, data processing, systems administration, and integrating Python with other software.

Syllabus

The course is taught over three days and covers the Python language and critical library modules for writing useful programs (testing, files, file system, subprocesses, databases, and systems integration).

1. Introduction to Python. An introduction to the Python programming language. Covers details of how to start and stop the interpreter and write programs. Introduces Python's basic datatypes, files, functions, and error handling.
2. Working with Data. A detailed tour of how to represent and work with data in Python. Covers tuples, lists, dictionaries, and sets. Students will also learn how to effectively use Python's very powerful list processing primitives such as list comprehensions. Finally, this section covers critical aspects of Python's underlying object model including variables, reference counting, copying, and type checking.
3. Program Organization and Functions. More information about how to organize larger programs into functions. A major focus of this section is on how to design functions that are reliable and can be easily reused in other settings. Also covers technical details of functions including scoping rules and documentation strings.
4. Modules and Libraries. How to organize programs into modules and details on using modules as a tool for creating extensible programs. Concludes with a tour of some of the most commonly used library modules including those related to system administration, text processing, subprocesses, XML parsing, binary data handling, and databases. In addition, an optional section on using numpy and matplotlib to process numeric data can be taught depending on student interest.
5. Classes and Objects. An introduction to object-oriented programming in Python. Describes how to create new objects, overload operators, and utilize Python special methods. Also covers basic principles of object oriented programming including inheritance and composition.
6. Inside the Python Object System. A detailed look at how objects are implemented in Python. Major topics include object representation, attribute binding, inheritance, memory management, and special properties of classes including properties, slots, and private attributes.
7. Testing, Debugging, and Software Development Practice. This section discusses many isses that are considered important to Python software development. This includes effective use of documentation strings, program testing using both the doctest and unittest modules, and effective use of assertions. The Python debugger and profiler are also described.
8. Iterators and Generators. Covers the iteration protocol, iterable objects, generators and generator expressions. A major focus of this section concerns the use of generators to set up data processing pipelines--a particularly effective technique for addressing a wide variety of common systems programming problems (e.g., processing large datafiles, handling infinite data streams, etc.).
9. Text I/O Handling. (Optional) More information on text-based I/O. Topics include text generation, template strings, and Unicode.
10. Some Advanced Topics. (Optional) A variety of more advanced programming topics including variable argument functions, anonymous functions (lambda), closures, decorators, static and class methods, and packages.
11. Python Integration Primer. (Optional) A survey of how Python is able to interact with programs written in other programming languages. Topics include network programming, accessing C code, COM extensions, Jython, and IronPython.

Instruction Format

The course is designed to be taught on a 9-5 schedule with a one hour lunch break. Class time is evenly split between presentation slides and hands-on programming exercises. Participants typically spend 3-4 hours each day working on programming exercises and using Python.

Prerequisites

Although no prior experience with Python is required, this course assumes that students have prior experience with some other programming language such as C++, Java, or Perl. This is not an introductory class for absolute beginners on how to program a computer! Participants should already be familiar with the basic concepts of programming such as variables, statements, control-flow, functions, arrays, data structures, and common programming problems (e.g., searching, sorting, etc.).

In addition, it is assumed that students already know how to work with files, folders, editors, command shells, environment settings, internet connections, and other essential aspects of using a computer for software development.

About the Instructor

David is the author of the Python Essential Reference and elected member of the Python Software Foundation. David has been an active member of the Python community since 1996 and is the creator of several Python-related packages including SWIG and PLY (Python Lex-Yacc). In addition to his work with Python, Dave has extensive experience with C, C++, and assembly language programming. Dave has a Ph.D. in computer science and a M.S. in mathematics.

Logistics

The class is best suited for 10-15 students. A larger class size is possible, but should not exceed 25 students.

You are responsible for providing the instruction space, a video projector, and machines where students can work on the programming exercises. The course can be taught on Windows, Linux, or Mac OS-X. However, all machines must be equipped with the latest version of Python (currently Python 2.7).

Although the class notes are extensive, all attendees are encouraged to bring a Python book for reference. Absolute beginners may want to consider a book such as "Learning Python" or "Dive Into Python." If you already have some Python experience, consider a book such as the "Python Essential Reference" or "Python in a Nutshell."

2011 Schedule and pricing

Classes are normally scheduled at least 8 weeks in advance. However, classes in the greater Chicago area can often be scheduled on shorter notice depending on availability.

The cost of Practical Python Programming with an enrollment of 12 students is $10000. This is an all-inclusive price that includes instructor travel expenses. Additional students can be added for $750/student.

If desired, extra course days can be added to cover additional topics such as Networks and Concurrency or Advanced Python. Extra course days are charged at $2400/day for 12 students. Additional students can be added for $200/student.

Classes can be taught internationally, but the base course rates will be charged at 1.5 times normal to cover added travel expenses. Discounts are available for government contracts and for classes in the greater Chicago area.

Contact

For more information, send email to "dave" at "dabeaz.com".

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