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Taco module for Python

Project description

Introduction

Taco is a system for bridging between scripting languages. Its goal is to allow you to call routines written for one language from another. It does this by running the second language interpreter in a sub-process, and passing messages about actions to be performed inside that interpreter.

In principle, to interface scripting languages it might be preferable to embed the interpreter for one as an extension of the other. However this might not be convenient or possible, and would need to be repeated for each combination of languages. Instead Taco only requires a “client” module and “server” script for each language, which should be straightforward to install, and its messages are designed to be generic so that they can be used between any combination of languages.

For more information about Taco, please see the Taco Homepage.

Examples

Here are examples of the different types of responses which may result from a Taco call:

  • Function Results

    If you find that you need the weighted roll_dice() function from the Acme::Dice Perl module, you can import it and call the function as follows:

    >>> from taco import Taco
    >>> taco = Taco(lang='perl')
    >>> taco.import_module('Acme::Dice', 'roll_dice')
    >>> taco.call_function('roll_dice', dice=1, sides=6, favor=6, bias=100)
    6
    

    In this example, instantiating a Taco object starts a sub-process running a Perl script. This “server” script then handles the instructions to import a module and call one of its functions, returning the value 6.

  • Object References

    To allow the use of object-oriented modules such as Acme::PricelessMethods, references to objects are returned as instances of the TacoObject class.

    >>> taco.import_module('Acme::PricelessMethods')
    >>> pm = taco.construct_object('Acme::PricelessMethods')
    >>> type(pm)
    <class 'taco.object.TacoObject'>
    

    These objects can be used to invoke further actions:

    >>> pm.call_method('is_machine_on')
    1
    
  • Exceptions

    roll_dice() raises an exception if we try to roll more than 100 dice. The exception is caught and re-raised on the “client” side:

    >>> taco.call_function('roll_dice', dice=1000)
    Traceback (most recent call last):
    ...
    taco.error.TacoReceivedError: ... Really? Roll 1000 dice? ...
    

Installation

The module can be installed using the setup.py script:

python setup.py install

Before doing that, you might like to run the unit tests:

PYTHONPATH=lib python -m unittest -v

For Python 2, it might be necessary to include the command discover after the unittest module name. If successful you should see a number of test cases being run.

Integration Tests

This package also includes further integration tests which test the complete system. These tests are stored in files named ti_*.py to avoid them being found by unittest discovery with its default parameters. They all use the Python “client” module but a variety of “server” scripts.

  • Python

    The tests using a Python “server” script can be run directly from this package:

    PYTHONPATH=lib python -m unittest discover -v -s 'ti-python' -p 'ti_*.py'
  • Other Languages

    The following tests all require a Taco “server” script for the corresponding language to be installed in your search path.

    • Perl

      PYTHONPATH=lib python -m unittest discover -v -s 'ti-perl' -p 'ti_*.py'

License

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see <http://www.gnu.org/licenses/>.

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