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A minimal Python interpreter in Python with runtime AST definition and edit-and-continue

Running

python_terp depends on pymetaterp.

pip install -r requirements
python test/python_repl.py

At the prompt, first run

p>> simport simple_ast

to use advanced features such as the for statement or boolean and. See lib/simple_ast.py. Then type in commands as usual.

p>> x = 3
p>> print x
3
p>> [x*x for x in [1,2,3,4,5] if x%2 == 1]
[1, 9, 25]

To run source from a file

python test/python_terp_test.py test/python_terp_ex.py

See test/python_terp_ex.py and test/parse_ex.py for some things the current version can handle.

Highlights

Runtime AST node semantics

This allows defining, modifying (by redefining functions) and debugging the semantics of if statements, for statements and others at run time. For example, for_stmt is a function in lib/simple_ast.py defined as

def for_stmt(index_var, iterable, block, else_block=None):
    iterator = iter(evaluate(iterable))
    while_true:
        try:
            assignment(index_var, iterator.next())
        except StopIteration:
            return
        __caller__['__continue__'] = __continue__
        __caller__['__break__'] = __break__
        evaluate(block)

See lib/boot.py, lib/globals.py and lib/simple_ast.py for more examples.

Edit and continue

Examine test/buggy_ex.py and run

python -i test/python_terp_test.py test/buggy_ex.py

Get an error

i is 1
1
i is 2
3
i is 3
6
i is 4
Traceback (most recent call last):
  File "test/python_terp_test.py", line 35, in <module>
    output = pyterp.run(pyi_tree, filename=filename)
  File "./python_terp/python_terp.py", line 198, in run
    return self._run(root)
  File "./python_terp/python_terp.py", line 206, in _run
    self.one_step()
  File "./python_terp/python_terp.py", line 256, in one_step
    raise output
KeyError: 'ii'
>>>

Do not exit the CPython interpreter! Examine the stack

>>> pyterp.st()
[...]
34 In file lib/simple_ast.py line 142 function aug_assign (evaluate)
    assignment(names, __binary__(operation[0][0], evaluate(names), evaluate(values)))
35 In file test/buggy_ex.py line 7 function __main__ (NAME)
        total += ii

find the error

>>> pyterp.last_stack[-1].root.pprint()
NAME
  str 'ii'

fix it

>>> pyterp.last_stack[-1].root[0] = 'i'

and continue execution

>>> pyterp.continue_()
Printing total
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "./python_terp/python_terp.py", line 226, in continue_
    self.one_step()
  File "./python_terp/python_terp.py", line 256, in one_step
    raise output
KeyError: 'tootal'

fix the second bug and continue

>>> pyterp.last_stack[-1].root[0] = 'total'
>>> pyterp.continue_()
10
i is 5
Printing total
15
Loop complete

This would make it easier to debug long computations without explicit pickling or debug rare bugs such as requests to a webserver.

Easy grammar modification and parsing debugging

See this example.

Low complexity

Current line counts are

Parsing
   48 pymetaterp/boot_grammar.py
  177 pymetaterp/boot_stackless.py
  233 pymetaterp/boot_tree.py
   69 pymetaterp/util.py
  171 pymetaterp/python_grammar.py
  182 pymetaterp/python.py
-------------------------
  880 total

Running
  629 python_terp/python_terp.py
   76 python_terp/debugger.py
-------------------------
  705 total

Library
  198 lib/simple_ast.py
   52 lib/global.py
  422 lib/objects.py
-------------------------
  672 total

CPython interoperability

To access CPython objects, just make them available in the namespace. For example adding

pyterp = python_terp.Interpreter(pyi)
import foo
pyterp.scope['foo'] = foo

before running pyterp.run will make foo available as a global variable.

Python compatibility

python_terp is intended to make language modification to Python easier to preview changes more quickly and is not intended for full CPython compatibility. However, currently, a large subset of Python is already included. In particular, enough to run the first stage of its parser.

python test/python_terp_test.py test/parse_ex.py

Caveats

  • Slow, as expected from running an interpreter inside another interpreter.
  • Still uses quite a bit of CPython features (so its not easy to port to another language) such as dicts and boolean operations.

Todo

Pull requests welcome.

  • Reduce dependency on Python dict and use objects.Dict. Troublesome for now because all scope depend on Python dicts.
  • Add nicer interface for edit and continue (diff the two versions of the source).
  • Add more AST node semantics like yield (make just take a portion of the call stack and pass it around).
  • Runtime grammar modifications so new AST nodes can be added (just need to chain existing tools together).
  • Replace by Python 3 (both host and target)
  • Document internals some more.

Some question and answers

What's the intended future direction?

Initial evolution would be need driven. Some effort would be spent keeping everything as small and simple as possible, which may lead to differences with CPython. Unless there's a use for tracking CPython more closely, of course. Anything to large could always be put in a separate module since almost all modifications are possible at runtime.

How does exec and compile work?

There isn't really a compile or exec. There's backticks that I've repurposed to create thunks (quotes of AST nodes with a scope) and there's evaluate that can run those thunks.

p>> n = `print(1)`
p>> n
<python_terp.python_terp.Thunk object at 0x7f273a77dc50>
p>> evaluate(n)
1
p>> x = 3
p>> n = `x += 1`
p>> evaluate(n)
p>> x
4

How does type work?

The host interpreter's type() function is passed through so python_terp objects (that aren't passed through Python objects) are all of type python_terp.Instance.

p>> simport simple_ast
p>> type
<type 'type'>
p>> import objects
p>> l = objects.List()
p>> type(l)
<class 'python_terp.python_terp.Instance'>
p>> d = objects.Dict()
p>> type(d)
<class 'python_terp.python_terp.Instance'>

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