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Block until ready

You also have the option to try and wait for a request to pass in the given timeout. It is very similar to the limit method and takes an identifier and returns the same response. However if the current limit has already been exceeded, it will automatically wait until the next window starts and will try again. Setting the timeout parameter (in seconds) will cause the method to block a finite amount of time. 
from upstash_ratelimit import Ratelimit, SlidingWindow
from upstash_redis import Redis

# Create a new ratelimiter, that allows 10 requests per 10 seconds
ratelimit = Ratelimit(
    redis=Redis.from_env(),
    limiter=SlidingWindow(max_requests=10, window=10),
)

response = ratelimit.block_until_ready("id", timeout=30)

if not response.allowed:
    print("Unable to process, even after 30 seconds")
else:
    do_expensive_calculation()
    print("Here you go!")

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Using multiple limits

Sometimes you might want to apply different limits to different users. For example you might want to allow 10 requests per 10 seconds for free users, but 60 requests per 10 seconds for paid users. Here’s how you could do that: 
from upstash_ratelimit import Ratelimit, SlidingWindow
from upstash_redis import Redis

class MultiRL:
    def __init__(self) -> None:
        redis = Redis.from_env()
        self.free = Ratelimit(
            redis=redis,
            limiter=SlidingWindow(max_requests=10, window=10),
            prefix="ratelimit:free",
        )

        self.paid = Ratelimit(
            redis=redis,
            limiter=SlidingWindow(max_requests=60, window=10),
            prefix="ratelimit:paid",
        )

# Create a new ratelimiter, that allows 10 requests per 10 seconds
ratelimit = MultiRL()

ratelimit.free.limit("userIP")
ratelimit.paid.limit("userIP")

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Custom Rates

When rate limiting, you may want different requests to consume different amounts of tokens. This could be useful when processing batches of requests where you want to rate limit based on items in the batch or when you want to rate limit based on the number of tokens. To achieve this, you can simply pass rate parameter when calling the limit method: 

from upstash_ratelimit import Ratelimit, FixedWindow
from upstash_redis import Redis

ratelimit = Ratelimit(
    redis=Redis.from_env(),
    limiter=FixedWindow(max_requests=10, window=10),
)

# pass rate as 5 to subtract 5 from the number of
# allowed requests in the window:
identifier = "api"
response = ratelimit.limit(identifier, rate=5)