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Python Tutorial Part 2
This document provides an overview of key Python concepts: 1. Modules allow organizing Python code into files and namespaces. The file name is the module name with a .py extension. 2. Python code is compiled into bytecode cache files (.pyc) for improved performance. These files are platform independent. 3. Advanced optimizations can be applied to bytecode with command line flags, but may affect program functionality in rare cases. 4. Standard modules provide useful functions like dir() to inspect modules and packages for organizing code. Input/output, strings, files and exceptions are also covered.
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Python Tutorial Part 2
- 1. Python Tutorial Haitham El-Ghareeb,Ph.D. May, 2012 Twitter: @helghareeb
- 2. Modules • A moduleis a file containing Python definitions and statements. • The file name is the module name with the suffix .py appended. • Within a module, the module’s name (as a string) is available as the value of the global variable __name__.
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- 7. Compiled Python Files •As an important speed-up of the start-up time for short programs that use a lot of standard modules, • if a file called spam.pyc exists in the directory where spam.py is found, this is assumed to contain an already-“byte-compiled” version of the module spam. • The modification time of the version of spam.py used to create spam.pyc is recorded in spam.pyc, and the .pyc file is ignored if these don’t match.
- 8. Compiled Python Files •Normally, you don’t need to do anything to create the spam.pyc file. • Whenever spam.py is successfully compiled, an attempt is made to write the compiled version to spam.pyc. • It is not an error if this attempt fails; if for any reason the file is not written completely, the resulting spam.pyc file will be recognized as invalid and thus ignored later. • The contents of the spam.pyc file are platform independent, so a Python module directory can be shared by machines of different architectures.
- 9. Some Tips forExperts • When the Python interpreter is invoked with the -O flag, optimized code is generated and stored in .pyo files. • The optimizer currently doesn’t help much; it only removes assert statements. • When -O is used, all bytecode is optimized; .pyc files are ignored and .py files are compiled to optimized bytecode.
- 10. Some Tips forExperts • Passing two -O flags to the Python interpreter (- OO) will cause the bytecode compiler to perform optimizations that could in some rare cases result in malfunctioning programs. • Currently only __doc__ strings are removed from the bytecode, resulting in more compact .pyo files. • Since some programs may rely on having these available, you should only use this option if you know what you’re doing.
- 11. Some Tips forExperts • A program doesn’t run any faster when it is read from a .pyc or .pyo file than when it is read from a .py file; the only thing that’s faster about .pyc or .pyo files is the speed with which they are loaded.
- 12. Some Tips forExperts • When a script is run by giving its name on the command line, the bytecode for the script is never written to a .pyc or .pyo file. • Thus, the startup time of a script may be reduced by moving most of its code to a module and having a small bootstrap script that imports that module. It is also possible to name a .pyc or .pyo file directly on the command line.
- 13. Some Tips forExperts • It is possible to have a file called spam.pyc (or spam.pyo when -O is used) without a file spam.py for the same module. • This can be used to distribute a library of Python code in a form that is moderately hard to reverse engineer.
- 14. Some Tips forExperts • The module compileall can create .pyc files (or .pyo files when -O is used) for all modules in a directory.
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- 16. Dir() • The built-infunction dir() is used to find out which names a module defines. It returns a sorted list of strings.
- 17. Packages • Packages area way of structuring Python’s module namespace by using “dotted module names”. • For example, the module name A.B designates a submodule named B in a package named A. • Just like the use of modules saves the authors of different modules from having to worry about each other’s global variable names, the use of dotted module names saves the authors of multi-module packages like NumPy or the Python Imaging Library from having to worry about each other’s module names.
- 19. Input and Output •There are several ways to present the output of a program; data can be printed in a human- readable form, or written to a file for future use. This chapter will discuss some of the possibilities. • How do you convert values to strings?
- 20. Representation • The str()function is meant to return representations of values which are fairly human-readable. • repr() is meant to generate representations which can be read by the interpreter (or will force a SyntaxError if there is not equivalent syntax).
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- 24. I don’t thinkso! MORE ON STRING FORMATTING?
- 25. Reading and WritingFiles • Open() returns a file object
- 26. Reading and WritingFiles
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- 31. Errors and Exceptions •Syntax Errors
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Editor's Notes
- #5 This does not enter the names of the functions defined in fibo directly in the current symbol table; it only enters the module name fibo there. Using the module name you can access the functions
- #7 This imports all names except those beginning with an underscore (_).Note that in general the practice of importing * from a module or package is frowned upon, since it often causes poorly readable code. However, it is okay to use it to save typing in interactive sessions.
- #17 Without arguments, dir() lists the names you have defined currently
- #19 The __init__.py files are required to make Python treat the directories as containing packages
- #20 Luckily, Python has ways to convert any value to a string: pass it to the repr() or str() functions.