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A pure Python Scannerless LR/GLR parser

Project Description

A pure Python scannerless LR/GLR parser.

For more information see the docs.

Quick intro

This is just a small example to get the general idea. This example shows how to parse and evaluate expressions with 5 operations with different priority and associativity. Evaluation is done using semantic/reduction actions.

The whole expression evaluator is done in under 30 lines of code!

from parglare import Parser, Grammar

grammar = r"""
E: E '+' E  {left, 1}
| E '-' E  {left, 1}
| E '*' E  {left, 2}
| E '/' E  {left, 2}
| E '^' E  {right, 3}
| '(' E ')'
| number;
number: /\d+(\.\d+)?/;

actions = {
    "E": [lambda _, nodes: nodes[0] + nodes[2],
          lambda _, nodes: nodes[0] - nodes[2],
          lambda _, nodes: nodes[0] * nodes[2],
          lambda _, nodes: nodes[0] / nodes[2],
          lambda _, nodes: nodes[0] ** nodes[2],
          lambda _, nodes: nodes[1],
          lambda _, nodes: nodes[0]],
    "number": lambda _, value: float(value),

g = Grammar.from_string(grammar)
parser = Parser(g, debug=True, actions=actions)

result = parser.parse("34 + 4.6 / 2 * 4^2^2 + 78")

print("Result = ", result)

# Output
# -- Debuging/tracing output with detailed info about grammar, productions,
# -- terminals and nonterminals, DFA states, parsing progress,
# -- and at the end of the output:
# Result = 700.8


  • Stable version:
$ pip install parglare
  • Development version:
$ git clone
$ pip install -e parglare



Python versions

Tested with 2.7, 3.3-3.6


Initial layout/content of this package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

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