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A c-style macro preprocessor written in Python

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pypreprocessor

Features

support c-style directives in python

  • using an intentionally limited subset of the c directives, and then some...

can run post-processed code on-the-fly

  • pre-process and run code all in one shot
  • accurately preserves error tracebacks for the source file

can output to a file

  • as easily as setting a flag
  • with a user specified filename if defined

can strip all pre-processor data from the output

  • as easily as setting a flag
  • removes all preprocessor directives
  • removes all preprocessor specific code

#defines can be set in code prior to processing

  • useful if you need to run a file in different modes
  • eliminates the need for decision logic in the preprocessor itself

nested #ifdef directives are supported

  • helpfull for more complicated code
  • #endifall gives the opportunity to end all open blocks

Benefits

Ease of Use

  • all of the functionality required to run the pypreprocessor is contained in a single module
  • adding preprocessor support is as simple as importing pypreprocessor to a file containing preprocessor directives and telling it to run
  • the preprocessor preserves errors in the pre and post processed code as much as possible
  • the preprocessor will break execution and output traceback errors if it sees invalid preprocessor directives

Dynamic

  • pypreprocessor has multiple option of operation
  • it can generate a new post-processed version of a source file absent all of the preprocessor information
  • or it can pre-process and run code transparently the same way as c-style languages do

Simple

  • the source footprint for the pypreprocessor code is very small
  • the preprocessor is designed to be as simple and lightweight as possible

Syntax

The syntax for pypreprocessor uses a select subset of the stanard c-style preprocessor directives, and then some...

Supported directives

  • define non-value constants used by the preprocessor
#define constant
  • remove a non-value constant from the list of defined constants
#undef constant
  • makes the subsequent block of code available if one of the specified constants is set
#ifdef constant [|| constant2 ...]
  • makes the subsequent block of code available if all of the preceding #ifdef statements return false
#else
  • required to close out an #ifdef/#else block
#endif
  • possibility to close all open blocks
#endifall
  • exclude the subsequent block of code (conditionals not included). I know it doesn't fit into the standard set of c-style directives but it's too handy to exclude (no pun).
#exclude
  • required to close out an #exclude block
#endexclude

Options

The following options need to be set prior to pypreprocessor.parse()

pypreprocessor.defines.append('define')

add defines to the preprocessor programmatically, this allows the source file to have some decision logic to decide which 'defines' need to be set

pypreprocessor.run = True / False
pypreprocessor.resume = True / False
pypreprocessor.save = True / False

set the options of the preprocessor:

  • run: Run the preprocessed code if true. Default is true
  • resume: Return after a file is preprocessed and can preprocess a next file if true. Default is false
  • save: Save preprocessed code if true. Default is true
pypreprocessor.input = 'inputFile.py'

required if you are preprocessing a module that is going to be imported. you can also use it to process external files.

pypreprocessor.output = 'outputFile.py'

set this to get a user defined name for the output file, otherwise the default is used: 'inputFile_out.py'

pypreprocessor.removeMeta = True

set this to remove the metadata from the output, useful if you're generating a 'clean' version of the source

pypreprocessor.readEncoding = sys.stdin.encoding
pypreprocessor.writeEncoding = sys.stdout.encoding

set this to make preprocessor use encoding

Applications

Include support for debug-specific information

It is often useful to provide statements within code specific to debugging, such as, print statements used to verify correct outputs. But, removing those debug statements can be painful and introduce new bugs while migrating to the production version.

Why not leave them...

By setting a "#define debug" at the top of the module and wrapping all of the debug statements in "#ifdef debug" blocks; disabling that code during production is as easy as adding another hash mark before the "#define debug" statement.

For a working example see:

Python2 -> Python3 code conversion

Producing code that can be run in both Python 2 and Python 3 is as easy as...

  1. check the version of the python interpreter in use
  2. set a #define in the preprocessor indicating the version
  3. add #ifdef directives on the code that is version specific

For a working example see:

Writing code from Debug -> Production in the same file

Ever wanted to run a file with debug-specific code during development but output a clean version specific source file for release? Here's how...

  1. make a source file that takes the arguments 'debug' and 'production'
  2. put the debug code in "#ifdef debug" blocks
  3. then run 'filename.py debug' during development
  4. or 'filename.py production' to output a version without any of the pypreprocessor metadata

For a working example see:

Note: This file also contains a 'postprocessed' mode that shows what pypreprocessor actually outputs. It's so simple it'll probably make you ::facepalm:: ;)

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A c-style macro preprocessor written in Python

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