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weave.trace.util

API Overview

Classes​

class ContextAwareThreadPoolExecutor​

A ThreadPoolExecutor that runs functions with the context of the caller.

This is a drop-in replacement for concurrent.futures.ThreadPoolExecutor that ensures weave calls behave as expected inside the executor. Weave requires certain contextvars to be set (see call_context.py), but new threads do not automatically copy context from the parent, which can cause the call context to be lost -- not good! This class automates contextvar copying so using this executor "just works" as the user probably expects.

You can achieve the same effect without this class by instead writing:

with concurrent.futures.ThreadPoolExecutor() as executor:
     contexts = [copy_context() for _ in range(len(vals))]

     def _wrapped_fn(*args):
         return contexts.pop().run(fn, *args)

     executor.map(_wrapped_fn, vals)

method __init__​

__init__(*args: Any, **kwargs: Any) → None

method map​

map(
    fn: Callable,
    *iterables: Iterable[Iterable],
    timeout: Optional[float] = None,
    chunksize: int = 1
) → Iterator

method submit​

submit(fn: Callable, *args: Any, **kwargs: Any) → Any

class ContextAwareThread​

A Thread that runs functions with the context of the caller.

This is a drop-in replacement for threading.Thread that ensures calls behave as expected inside the thread. Weave requires certain contextvars to be set (see call_context.py), but new threads do not automatically copy context from the parent, which can cause the call context to be lost -- not good! This class automates contextvar copying so using this thread "just works" as the user probaly expects.

You can achieve the same effect without this class by instead writing:

def run_with_context(func, *args, **kwargs):
     context = copy_context()
     def wrapper():
         context.run(func, *args, **kwargs)
     return wrapper

thread = threading.Thread(target=run_with_context(your_func, *args, **kwargs))
thread.start()

method __init__​

__init__(*args: Any, **kwargs: Any) → None

property daemon​

A boolean value indicating whether this thread is a daemon thread.

This must be set before start() is called, otherwise RuntimeError is raised. Its initial value is inherited from the creating thread; the main thread is not a daemon thread and therefore all threads created in the main thread default to daemon = False.

The entire Python program exits when only daemon threads are left.

property ident​

Thread identifier of this thread or None if it has not been started.

This is a nonzero integer. See the get_ident() function. Thread identifiers may be recycled when a thread exits and another thread is created. The identifier is available even after the thread has exited.

property name​

A string used for identification purposes only.

It has no semantics. Multiple threads may be given the same name. The initial name is set by the constructor.

property native_id​

Native integral thread ID of this thread, or None if it has not been started.

This is a non-negative integer. See the get_native_id() function. This represents the Thread ID as reported by the kernel.

method run​

run() → None