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"""
Pandora Rate Limiter
"""
import time
import warnings
from .errors import PandoraException
class RateLimitExceeded(PandoraException):
"""Exception thrown when rate limit is exceeded
"""
code = 0
message = "Rate Limit Exceeded"
class TokenBucketCallbacks(object):
"""Interface for TokenBucket Callbacks
These methods get called by the token bucket during certain parts of the
bucket lifecycle.
"""
def near_depletion(self, tokens_left):
"""Bucket near depletion callback
This callback is called when the token bucket is nearly depleted, as
defined by the depletion_level member of the TokenBucket class. This
method provides a hook for clients to warn when the token bucket is
nearly consumed. The return value of this method is ignored.
"""
return
def depleted(self, tokens_wanted, tokens_left):
"""Bucket depletion callback
This callback is called when the token bucket has been depleted.
Returns a boolean indicating if the bucket should call its default
depletion handler. If this method returns False the token bucket will
not return any tokens but will also not call the default token
depletion handler.
This method is useful if clients want to customize depletion behavior.
"""
return True
def consumed(self, tokens_wanted, tokens_left):
"""Bucket consumption callback
This callback is called when a client successfully consumes tokens from
a bucket. The return value of this method is ignored.
"""
return
class TokenBucket(object):
def __init__(self, capacity, refill_tokens, refill_rate, callbacks=None):
"""Initialize a rate limiter
capacity
the number of tokens the bucket holds when completely full
refill_tokens
number of tokens to add to the bucket during each refill cycle
refill_rate
the number of seconds between token refills
"""
self.capacity = capacity
self.refill_tokens = refill_tokens
self.refill_rate = refill_rate
self.callbacks = callbacks or TokenBucketCallbacks()
# Depletion level at which the near_depletion callback is called.
# Defaults to 20% of the bucket available. Not exposed in the
# initializer because this should generally be good enough.
self.depletion_level = self.capacity / 5
self._available_tokens = capacity
self._last_refill = time.time()
@classmethod
def creator(cls, callbacks=None):
"""Returns a TokenBucket creator
This method is used when clients want to customize the callbacks but
defer class construction to the real consumer.
"""
def constructor(capacity, refill_tokens, refill_rate):
return cls(capacity, refill_tokens, refill_rate, callbacks)
return constructor
def _replentish(self):
now = time.time()
refill_unit = round((now - self._last_refill) / self.refill_rate)
if refill_unit > 0:
self._last_refill = now
self._available_tokens = min(
self.capacity, refill_unit * self.refill_tokens
)
def _insufficient_tokens(self, tokens_wanted):
return
def _sufficient_tokens(self, tokens_wanted):
return
def consume(self, tokens=1):
"""Consume a number of tokens from the bucket
May return a boolean indicating that sufficient tokens were available
for consumption. Implementations may have different behaviour when the
bucket is empty. This method may block or throw.
"""
self._replentish()
if self._available_tokens >= tokens:
self._available_tokens -= tokens
if self._available_tokens <= self.depletion_level:
self.callbacks.near_depletion(self._available_tokens)
self.callbacks.consumed(tokens, self._available_tokens)
self._sufficient_tokens(tokens)
return True
else:
if self.callbacks.depleted(tokens, self._available_tokens):
self._insufficient_tokens(tokens)
return False
class BlockingTokenBucket(TokenBucket):
"""Token bucket that blocks on exhaustion
"""
def _insufficient_tokens(self, tokens_wanted):
tokens_per_second = self.refill_rate / self.refill_tokens
excess_tokens = tokens_wanted - self._available_tokens
time.sleep(tokens_per_second * excess_tokens)
class ThrowingTokenBucket(TokenBucket):
"""Token bucket that throws on exhaustion
"""
def _insufficient_tokens(self, tokens_wanted):
raise RateLimitExceeded("Unable to acquire enough tokens")
class WarningTokenBucket(TokenBucket):
"""Token bucket that warns on exhaustion
This token bucket doesn't enforce the rate limit and is designed to be a
softer policy for backwards compatability with code that was written before
rate limiting was added.
"""
def _insufficient_tokens(self, tokens_wanted):
warnings.warn(
"Pandora API rate limit exceeded!", warnings.ResourceWarning
)
|
