textX is a meta-language for building Domain-Specific Languages (DSLs) in Python. It is inspired by Xtext.

In a nutshell, textX will help you build your textual language in an easy way. You can invent your own language or build a support for already existing textual language or file format.

From a single language description (grammar), textX will build a parser and a meta-model (a.k.a. abstract syntax) for the language. See the docs for the details.

textX follows the syntax and semantics of Xtext but differs in some places and is implemented 100% in Python using Arpeggio PEG parser - no grammar ambiguities, unlimited lookahead, interpreter style of work.

Quick intro

from textx import metamodel_from_str, children_of_type

grammar = """
Model: shapes*=Shape;
Shape: Circle | Line;
Circle: 'circle' center=Point '/' radius=INT;
Line: 'line' start=Point '/' end=Point;
Point: x=INT ',' y=INT;
"""

mm = metamodel_from_str(grammar)

# Meta-model knows how to parse and instantiate models.
model = mm.model_from_str("""
    line 10, 10 / 20, 20
    line 14, 78 / 89, 33
    circle 14, 20/10
    line 18, 89 / 78, 65
""")

# At this point model is plain Python object graph with instances of
# dynamically created classes and attributes following the grammar.

def _(p):
    "returns coordinate of the given Point as string"
    return "{},{}".format(p.x, p.y)

for shape in model.shapes:
    if shape.__class__.__name__ == 'Circle':
        print('Circle: center={}, radius={}'
              .format(_(shape.center), shape.radius))
    else:
        print('Line: from={} to={}'.format(_(shape.start), _(shape.end)))

# Output:
# Line: from=10,10 to=20,20
# Line: from=14,78 to=89,33
# Circle: center=14,20, radius=10
# Line: from=18,89 to=78,65

# Collect all points starting from the root of the model
points = children_of_type("Point", model)
for point in points:
    print('Point: {}'.format(_(point)))

# Output:
# Point: 10,10
# Point: 20,20
# Point: 14,78
# Point: 89,33
# Point: 14,20
# Point: 18,89
# Point: 78,65

Video tutorials

Introduction to textX

Implementing Martin Fowler's State Machine DSL in textX

Docs and tutorials

The full documentation with tutorials is available at http://igordejanovic.net/textX/

Discussion and help

For general discussion and help please join [the textX google group](https://groups.google.com/forum/#!forum/textx-talk).

Python EMF support

TextX also supports PyEcore as metamodel and model layer alternative. This support enables the metamodel code generation from a grammar (if needed) and gives the ability to handle the model and the metamodel part with an EMF compatible API. It also gives, out-of-the-box, an XMI/JSON serialization support for the model and/or metamodel, opposite relationships, and code generation facilities.

Python EMF support activation

In order to enable PyEcore (Python EMF), you need to import the textx package and use the enable_pyecore_support() method:

from textx.metamodel import metamodel_from_str  # regular textX import
import textx

textx.enable_pyecore_support()

The package importation can be made in any order. For more details, check the documentation at this adress not yet available, and the PyEcore README.

License

MIT

Python versions

Tested for 2.7, 3.3+