Delayed iteration for polling and retries.
Does Python need yet another retry / poll library? It needs at least one that isn't coupled to decorators and functions. Decorators prevent the caller from customizing delay options, and organizing the code around functions hinders any custom handling of failures.
Waiter is built around iteration instead, because the foundation of retrying / polling is a slowly executing loop. The resulting interface is both easier to use and more flexible, decoupling the delay algorithms from the application logic.
Supply a number of seconds to repeat endlessly, or any iterable of seconds.
from waiter import wait
wait(1) # 1, 1, 1, 1, ...
wait([1] * 3) # 1, 1, 1
wait([0.5, 0.5, 60]) # circuit breaker
Iterable delays can express any waiting strategy, and constructors for common algorithms are also provided.
wait.count(1) # incremental backoff 1, 2, 3, 4, 5, ...
wait(1) + 1 # alternate syntax 1, 2, 3, 4, 5, ...
wait.fibonacci(1) # 1, 1, 2, 3, 5, ...
wait.polynomial(2) # 0, 1, 4, 9, 16, ...
wait.exponential(2) # exponential backoff 1, 2, 4, 8, ...
backoff = wait(1) * 2 # alternate syntax 1, 2, 4, 8, ...
backoff[:3] # limit attempt count 1, 2, 4
backoff <= 5 # set maximum delay 1, 2, 4, 5, 5, 5, ...
backoff.random(-1, 1) # add random jitter
Then simply use the wait
object like any iterable, yielding the amount of elapsed time. Timeouts also supported of course.
from waiter import wait, suppress, first
for elapsed in wait(delays): # first iteration is immediate
with suppress(exception): # then each subsequent iteration sleeps as necessary
...
break
for _ in wait(delays, timeout): # standard convention for ignoring a loop variable
... # won't sleep past the timeout
if ...:
break
results = (... for _ in wait(delays)) # expressions are even easier
first(predicate, results[, default]) # filter for first true item
assert any(results) # perfect for tests too
Yes, functional versions are provided, as well as being trivial to implement.
wait(...).throttle(iterable) # generate items from iterable
wait(...).repeat(func, *args, **kwargs) # generate successive results
wait(...).retry(exception, func, *args, **kwargs) # return first success or re-raise exception
wait(...).poll(predicate, func, *args, **kwargs) # return first success or raise StopIteration
The decorator variants are simply partial applications of the corresponding methods. Note decorator syntax doesn't support arbitrary expressions.
backoff = wait(0.1) * 2
@backoff.repeating
@backoff.retrying(exception)
@backoff.polling(predicate)
But in the real world:
So consider the block form, just as decorators don't render with
blocks superfluous. Also note wait
objects are re-iterable provided their original delays were.
Waiters also support async iteration. throttle
optionally accepts an async iterable. repeat
, retry
, and poll
optionally accept coroutine functions.
Waiter objects have a stats
attribute for aggregating statistics about the calls made. The base implementation provides total
and failure
counts. The interface of the stats
object itself is considered provisional for now, but can be extended by overriding the Stats
class attribute. This also allows customization of the iterable values; elapsed time is the default.
% pip install waiter
100% branch coverage.
% pytest [--cov]