pyccolo 0.0.90

Declarative instrumentation for Python

Pyccolo

Pyccolo (pronounced like the instrument "piccolo") is a library for declarative instrumentation in Python; i.e., it lets you specify the what of the instrumentation you wish to perform, and takes care of the how for you. It brings metaprogramming to everybody via general, event-emitting AST transformations, and aims to be:

• ergonomic — you subclass pyc.BaseTracer and decorate a handler; there's no bytecode to patch and no ast.NodeTransformer to hand-write;
• composable — layering multiple, independently-written instrumentations usually Just Works^TM (more on this below);
• portable — the same code runs across Python 3.6 through 3.14, with few exceptions, because instrumentation is embedded at the level of source code rather than bytecode.

In the wild

Pyccolo is the instrumentation engine behind several projects — good places to see what it can do at scale:

• ipyflow — a reactive Python kernel for Jupyter that tracks dataflow between cells using Pyccolo's dynamic analysis.
• pipescript — a pipe operator (|>), placeholder ($), and macro syntax for IPython/Jupyter, built entirely on Pyccolo's syntax-augmentation and composable event handlers.
• pycograd — a small reverse-mode automatic-differentiation library that differentiates ordinary numpy code (no special "autodiff namespace"), using Pyccolo to trace the computation.
• <Your tool here!>

Other things people have built with Pyccolo include statement-level code coverage, syntactic macros (quasiquotes, quick lambdas), syntax-augmented Python (optional chaining, pipeline operators), lazy imports, concolic execution, and tools to uncover semantic memory leaks. See the example gallery for runnable versions of many of these.

Install

pip install pyccolo

Hello World

Below is a simple script that uses Pyccolo to print "Hello, world!" before every statement that executes:

import pyccolo as pyc


class HelloTracer(pyc.BaseTracer):
    @pyc.before_stmt
    def handle_stmt(self, *_, **__):
        print("Hello, world!")


if __name__ == "__main__":
    with HelloTracer:
        # prints "Hello, world!" 11 times
        pyc.exec("for _ in range(10): pass")

Instrumentation is provided by a tracer class that inherits from pyccolo.BaseTracer. This class rewrites Python source code with instrumentation that triggers whenever events of interest occur, such as when a statement is about to execute. By registering a handler with the associated event (with the @pyc.before_stmt decorator, in this case), we can enrich our programs with additional observability, or even alter their behavior altogether.

What is up with pyc.exec(...)?

A program's abstract syntax tree is fixed at import / compile time, and when our script initially started running, the tracer was not active, so unquoted Python in the same file will lack instrumentation. It is possible to instrument modules at import time (see below), but only when the imports are performed inside a tracing context. Thus, we must quote any code appearing in the same module where the tracer class was defined in order to instrument it.

The model: events and handlers

Pyccolo exposes a fine-grained taxonomy of over 100 events (see pyccolo/trace_events.py for the full list). Some of the more common ones:

• pyc.before_stmt / pyc.after_stmt, emitted around statements;
• pyc.before_attribute_load / pyc.after_attribute_load, emitted in load contexts around attribute accesses;
• pyc.load_name, emitted when a variable is used in a load context (e.g. foo in bar = foo.baz);
• pyc.before_binop / pyc.after_binop, pyc.before_unaryop / pyc.after_unaryop, emitted around binary (e.g. x + y) and unary (e.g. -x, not x) operations;
• pyc.after_assign_rhs, emitted after the right-hand side of an assignment;
• literal events like pyc.after_int / pyc.after_float / pyc.after_string;
• pyc.call and pyc.return_, two non-AST trace events built in to Python.

Every handler is passed four positional arguments:

1. the return value, for instrumented expressions;
2. the AST node (or node id, if using register_raw_handler(...), or None, for sys events);
3. the stack frame, at the point where instrumentation kicks in;
4. the event (useful when the same handler is registered for multiple events).

Some events pass additional keyword arguments, but the above four suffice for most use cases — hence the ubiquitous def handle(self, ret, *_, **__) shape.

Handlers can override behavior, not just observe it. For many events, the value a handler returns replaces the value of the instrumented expression:

class IncrementEveryAssignment(pyc.BaseTracer):
    @pyc.after_assign_rhs
    def handle(self, ret, *_, **__):
        return ret + 1


with IncrementEveryAssignment:
    env = pyc.exec("x = 42")
    assert env["x"] == 43

Returning None (or nothing) means "don't override." To actually override a value with None, return the pyc.Null sentinel. Returning pyc.Skip stops further handlers for the current event; pyc.SkipAll aborts the whole tracer stack for that event.

Note that, for AST events, Python source is only transformed to emit an event when there is at least one active tracer with at least one handler registered for that event. This keeps the transformed source from becoming bloated when only a few events are needed.

A tiny example: exact floats

Because literal events can override the value that flows out of a literal, an entire behavioral change can fit in a handler. Here's a tracer that makes every float literal exact by promoting it to Decimal:

from decimal import Decimal

import pyccolo as pyc


class ExactFloats(pyc.BaseTracer):
    @pyc.after_float
    def to_decimal(self, ret, *_, **__):
        return Decimal(str(ret))


with ExactFloats:
    pyc.exec("print(0.1 + 0.2)")  # -> 0.3   (not 0.30000000000000004)

Composing tracers

A core feature of Pyccolo is that its instrumentation is composable. It's usually tricky to use two or more ast.NodeTransformer classes simultaneously — sometimes you can just have one inherit from the other, but if they both define visit methods for the same AST node type, then typically you would need to define a bespoke node transformer that uses logic from each base transformer, handling corner cases to resolve incompatibilities. With Pyccolo, you simply nest the context managers of each tracer class whose instrumentation you wish to use, and everything usually Just Works^TM:

class AddOne(pyc.BaseTracer):
    @pyc.after_assign_rhs
    def handle(self, ret, *_, **__):
        return ret + 1


class TimesTwo(pyc.BaseTracer):
    @pyc.after_assign_rhs
    def handle(self, ret, *_, **__):
        return ret * 2


with AddOne:
    with TimesTwo:
        env = pyc.exec("x = 42")
        assert env["x"] == 86  # (42 + 1) * 2 -- handlers compose in order

Return values compose across handlers on the same tracer as well as across handlers on different tracers.

Syntax augmentation

Pyccolo can go beyond instrumenting existing Python: a tracer can define new surface syntax. It does this with an AugmentationSpec, which declares a source-level token → replacement rewrite; Pyccolo remembers where the rewrite happened, so a handler can attach to the resulting AST node. For example, JavaScript-style optional chaining rewrites ?. down to a plain ., then resolves the access to None whenever the receiver is None:

optional_chaining_spec = pyc.AugmentationSpec(
    aug_type=pyc.AugmentationType.dot_suffix, token="?.", replacement="."
)

A complete, tested implementation of optional chaining and nullish coalescing (??) ships in pyccolo/examples/optional_chaining.py:

import pyccolo as pyc
from pyccolo.examples.optional_chaining import ScriptOptionalChainer

with ScriptOptionalChainer:
    pyc.exec("bar = None\nprint(bar?.foo)")  # -> None

The most complete showcase of syntax augmentation is pipescript, which layers a whole pipe-and-placeholder dialect on top of Python:

# in IPython / Jupyter, after `%load_ext pipescript`
result = arrays |> map[$
  |> $array[np.isfinite($array)]
  |> np.abs
  |> np.max($, initial=1.0)
] |> max

Under the hood, pipescript rewrites illegal token spans like |> to legal ones (here, bitwise-or |), then uses Pyccolo to associate the resulting ast.BinOp with the |> operator and run the corresponding handler. Because a single event-emission transform is shared by every handler that cares about it, features compose without conflicting AST rewrites — see pipescript's "How it works" for the full story.

Syntax augmentation is available on Python >= 3.8. Beyond single-token replacement, Pyccolo also supports paired-delimiter (brace-block) augmentation and a pyc.CustomRewrite extension point for context-sensitive rewrites; see the example gallery and test_syntax_augmentation.py.

Source-to-source: transform, untransform, and pure mode

Sometimes you want the rewritten source, not a running program — for a linter, formatter, or source map. pyc.transform(code) returns instrumented / desugared source, and pyc.untransform(tree) reverses an augmentation, resugaring valid Python back into the augmented syntax:

import pyccolo as pyc
from pyccolo.examples.optional_chaining import ScriptOptionalChainer as OC

with OC:
    # desugar augmented syntax down to plain, valid Python:
    assert pyc.transform("y = a?.b?.c") == "y = a.b.c"

    # ...and resugar it back from the parsed tree:
    tree = pyc.parse("y = a?.b?.c", instrument=False)
    assert pyc.untransform(tree) == "y = a?.b?.c"

    # pure=True marks an analysis-only transform (no runtime side effects):
    assert pyc.transform("y = a?.b", pure=True) == "y = a.b"

Both accept a positions=[(line, col), ...] argument and return the remapped positions in the transformed (or untransformed) coordinates, for source-map-style tooling. Passing pure=True signals an analysis-only transform whose result is never executed; cooperating rewrites can consult pyc.is_pure_transform() to avoid touching execution-relevant state, and it is thread / async-safe via a ContextVar.

Compatibility with sys.settrace(...)

Pyccolo supports not only AST-level instrumentation, but also instrumentation involving Python's built-in tracing utilities. To use it, you simply register handlers for one of the corresponding Pyccolo events (call, line, return_, exception, or opcode):

import pyccolo as pyc


class SysTracer(pyc.BaseTracer):
    @pyc.call
    def handle_call(self, *_, **__):
        print("Pushing a stack frame!")

    @pyc.return_
    def handle_return(self, *_, **__):
        print("Popping a stack frame!")


if __name__ == "__main__":
    with SysTracer:
        def f():
            def g():
                return 42
            return g()
        # push, push, pop, pop
        answer_to_life_universe_everything = f()

Note that we didn't need pyc.exec(...) here, because Python's built-in tracing does not involve any AST-level transformations. If we had registered handlers for AST events such as pyc.before_stmt, we would need pyc.exec(...) to instrument code in the same file where the tracer is defined.

Pyccolo composes with an existing sys.settrace(...) function, too: its unit tests for call and return_ pass even when coverage.py is active (and without breaking it), which also uses Python's built-in tracing utilities.

Instrumenting imported modules

Instrumentation is opt-in for modules imported within tracing contexts. To determine whether a module gets instrumented, the method should_instrument_file(...) is called with the module's filename as input:

class MyTracer(pyc.BaseTracer):
    def should_instrument_file(self, filename: str) -> bool:
        return filename.endswith("foo.py")

    # handlers, etc. defined below
    ...

with MyTracer:
    import foo  # contents of `foo` get instrumented
    import bar  # contents of `bar` do not

Imports are instrumented by registering a custom finder / loader with sys.meta_path. This loader ignores cached bytecode (which may be uninstrumented), and avoids generating new cached bytecode (which would be instrumented, possibly causing confusion later when instrumentation is not desired).

Performance

Pyccolo instrumentation adds significant overhead to Python. In some cases, this overhead can be partially mitigated if, for example, you only need instrumentation the first time a statement runs. In such cases, you can deactivate instrumentation after, e.g., the first time a function executes, or after the first iteration in a loop, so that further calls (iterations, respectively) use uninstrumented code with all the mighty performance of native Python. This is implemented by activating "guards" associated with the function or loop:

class TracesOnce(pyc.BaseTracer):
    @pyc.register_raw_handler((pyc.after_for_loop_iter, pyc.after_while_loop_iter))
    def after_loop_iter(self, *_, guard, **__):
        self.activate_guard(guard)

    @pyc.register_raw_handler(pyc.after_function_execution)
    def after_function_exec(self, *_, guard, **__):
        self.activate_guard(guard)

Subsequent calls / iterations will be instrumented again only after calling self.deactivate_guard(...) on the associated function / loop guard.

Command line interface

You can execute arbitrary scripts with instrumentation enabled with the pyc command line tool. For example, to use the optional-chaining tracer, given some example script bar.py:

# bar.py
bar = None
# prints `None` since bar?.foo coalesces to `None`
print(bar?.foo)

> pyc bar.py -t pyccolo.examples.optional_chaining.ScriptOptionalChainer

You can also run bar as a module (indeed, pyc does this internally when given a file):

> pyc -m bar -t pyccolo.examples.optional_chaining.ScriptOptionalChainer

Note the use of ScriptOptionalChainer rather than the bare OptionalChainer: because pyc runs your file through Pyccolo's import machinery, the tracer must opt that file in by overriding should_instrument_file (which ScriptOptionalChainer does, and OptionalChainer does not).

You can specify multiple tracer classes after -t; in case you were not already aware, Pyccolo is composable! :)

Example gallery

Each of the following ships under pyccolo/examples/ as a self-contained, tested tracer — great starting points to adapt:

Example	Demonstrates
coverage.py	statement-level code coverage (before_stmt, should_instrument_file)
optional_chaining.py	?., .?, ?? optional chaining / nullish coalescing via AugmentationSpec
pipeline_tracer.py	|> / |>> pipeline operators (binop augmentation)
quick_lambda.py	MacroPy-style f[_ + _] quick lambdas
quasiquote.py	MacroPy-style q[...] / u[...] quasiquotes
block_lambda.py, func_block.py, brace_subscript.py	statement-bodied name{ ... } blocks (paired-delimiter augmentation)
lazy_imports.py	make (most) imports lazy, resolving on first use
future_tracer.py	implicit async: run assignments on a thread pool, unwrap futures on use
concolic.py	concolic (concrete + symbolic) execution with a Z3 / brute-force solver

License

Code in this project licensed under the BSD-3-Clause License.