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Advanced PyCamp Syllabus

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The outline of Advanced PyCamp, the follow-on week to PyCamp. The organization of topics in which you will further your journey through Python programming. This organization is unique compared to other course outlines. Rather than memorizing a litany of APIs before applying them to problem solving, you will learn the Pythonic way of programming by examining solutions to common programming problems.

See syllabi for other TriZPUG Python Boot Camp weeks: PyCamp SyllabusSciPyCamp Syllabus

Contents

DAY ONE: New Language Features
DAY TWO: Development Best Practices
DAY THREE: Performance and Debugging
DAY FOUR: Graphical User Interfaces
DAY FIVE: Threads and Sockets

DAY ONE: New Language Features

Generative ProgrammingAspect Oriented ProgrammingNew Object FeaturesNew Syntaxback to contents

Generative Programming

  • The Iterator Protocol
  • Generators
  • Generator Expressions

Aspect Oriented Programming

  • Function Attributes
  • Decorators
  • Properties

New Object Features

  • New Style Classes
  • Static and Class Methods
  • Metaclasses

New Syntax

  • The Tenary Operator
  • The With Statement

DAY TWO: Development Best Practices

Development EnvironmentsTest Driven Developmentback to contents

Development Environments

  • IDLE
  • IPython
  • Wing
  • Komodo

Test Driven Development

  • unittest
  • doctest
  • nose
  • figleaf

DAY THREE: Performance and Debugging

Performance TuningDebuggingback to contents

Performance Tuning

  • Profiling
  • timeit
  • Common Gotchas
  • C Extentions

Debugging

  • pdb
  • inspect
  • Wing
  • Komodo

DAY FOUR: Graphical User Interfaces

TkinterwxPythonDaboback to contents

Tkinter

  • Event Loops
  • Containers
  • Widgets
  • Layout Managers

wxPython

Dabo

DAY FIVE: Threads and Sockets

ThreadsSocketsback to contents

Threads

  • Thread Objects
  • The Global Interpreter Lock
  • Interprocess Communications

Sockets

  • TCP
  • UDP
  • select
  • asyncore
  • twisted

TriPython endorses:

PyLadies RDU

September 14-16, 2016:

PyData Carolinas 2016

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