Add rate limiting code

implementations/python/rate_limiting/fixed_window_counter.py

@@ -0,0 +1,33 @@
+import time
+
+class FixedWindowCounter:
+    def __init__(self, window_size, max_requests):
+        self.window_size = window_size  # Size of the window in seconds
+        self.max_requests = max_requests  # Maximum number of requests per window
+        self.current_window = time.time() // window_size
+        self.request_count = 0
+
+    def allow_request(self):
+        current_time = time.time()
+        window = current_time // self.window_size
+
+        # If we've moved to a new window, reset the counter
+        if window != self.current_window:
+            self.current_window = window
+            self.request_count = 0
+
+        # Check if we're still within the limit for this window
+        if self.request_count < self.max_requests:
+            self.request_count += 1
+            return True
+        return False
+
+# Usage example
+limiter = FixedWindowCounter(window_size=60, max_requests=5)  # 5 requests per minute
+
+for _ in range(10):
+    print(limiter.allow_request())  # Will print True for the first 5 requests, then False
+    time.sleep(0.1)  # Wait a bit between requests
+
+time.sleep(60)  # Wait for the window to reset
+print(limiter.allow_request())  # True

implementations/python/rate_limiting/leaky_bucket.py

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+from collections import deque
+import time
+
+class LeakyBucket:
+    def __init__(self, capacity, leak_rate):
+        self.capacity = capacity  # Maximum number of requests in the bucket
+        self.leak_rate = leak_rate  # Rate at which requests leak (requests/second)
+        self.bucket = deque()  # Queue to hold request timestamps
+        self.last_leak = time.time()  # Last time we leaked from the bucket
+
+    def allow_request(self):
+        now = time.time()
+        # Simulate leaking from the bucket
+        leak_time = now - self.last_leak
+        leaked = int(leak_time * self.leak_rate)
+        if leaked > 0:
+            # Remove the leaked requests from the bucket
+            for _ in range(min(leaked, len(self.bucket))):
+                self.bucket.popleft()
+            self.last_leak = now
+
+        # Check if there's capacity and add the new request
+        if len(self.bucket) < self.capacity:
+            self.bucket.append(now)
+            return True
+        return False
+
+# Usage example
+limiter = LeakyBucket(capacity=5, leak_rate=1)  # 5 requests, leak 1 per second
+
+for _ in range(10):
+    print(limiter.allow_request())  # Will print True for the first 5 requests, then False
+    time.sleep(0.1)  # Wait a bit between requests
+
+time.sleep(1)  # Wait for bucket to leak
+print(limiter.allow_request())  # True

implementations/python/rate_limiting/sliding_window_counter.py

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+import time
+
+class SlidingWindowCounter:
+    def __init__(self, window_size, max_requests):
+        self.window_size = window_size  # Size of the sliding window in seconds
+        self.max_requests = max_requests  # Maximum number of requests per window
+        self.current_window = time.time() // window_size
+        self.request_count = 0
+        self.previous_count = 0
+
+    def allow_request(self):
+        now = time.time()
+        window = now // self.window_size
+
+        # If we've moved to a new window, update the counts
+        if window != self.current_window:
+            self.previous_count = self.request_count
+            self.request_count = 0
+            self.current_window = window
+
+        # Calculate the weighted request count
+        window_elapsed = (now % self.window_size) / self.window_size
+        threshold = self.previous_count * (1 - window_elapsed) + self.request_count
+
+        # Check if we're within the limit
+        if threshold < self.max_requests:
+            self.request_count += 1
+            return True
+        return False
+
+# Usage example
+limiter = SlidingWindowCounter(window_size=60, max_requests=5)  # 5 requests per minute
+
+for _ in range(10):
+    print(limiter.allow_request())  # Will print True for the first 5 requests, then gradually become False
+    time.sleep(0.1)  # Wait a bit between requests
+
+time.sleep(30)  # Wait for half the window to pass
+print(limiter.allow_request())  # Might be True or False depending on the exact timing

implementations/python/rate_limiting/sliding_window_log.py

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+import time
+from collections import deque
+
+class SlidingWindowLog:
+    def __init__(self, window_size, max_requests):
+        self.window_size = window_size  # Size of the sliding window in seconds
+        self.max_requests = max_requests  # Maximum number of requests per window
+        self.request_log = deque()  # Log to keep track of request timestamps
+
+    def allow_request(self):
+        now = time.time()
+        
+        # Remove timestamps that are outside the current window
+        while self.request_log and now - self.request_log[0] >= self.window_size:
+            self.request_log.popleft()
+
+        # Check if we're still within the limit
+        if len(self.request_log) < self.max_requests:
+            self.request_log.append(now)
+            return True
+        return False
+
+# Usage example
+limiter = SlidingWindowLog(window_size=60, max_requests=5)  # 5 requests per minute
+
+for _ in range(10):
+    print(limiter.allow_request())  # Will print True for the first 5 requests, then False
+    time.sleep(0.1)  # Wait a bit between requests
+
+time.sleep(60)  # Wait for the window to slide
+print(limiter.allow_request())  # True

implementations/python/rate_limiting/token_bucket.py

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+import time
+
+class TokenBucket:
+    def __init__(self, capacity, fill_rate):
+        self.capacity = capacity  # Maximum number of tokens the bucket can hold
+        self.fill_rate = fill_rate  # Rate at which tokens are added (tokens/second)
+        self.tokens = capacity  # Current token count, start with a full bucket
+        self.last_time = time.time()  # Last time we checked the token count
+
+    def allow_request(self, tokens=1):
+        now = time.time()
+        # Calculate how many tokens have been added since the last check
+        time_passed = now - self.last_time
+        self.tokens = min(self.capacity, self.tokens + time_passed * self.fill_rate)
+        self.last_time = now
+
+        # Check if we have enough tokens for this request
+        if self.tokens >= tokens:
+            self.tokens -= tokens
+            return True
+        return False
+
+# Usage example
+limiter = TokenBucket(capacity=10, fill_rate=1)  # 10 tokens, refill 1 token per second
+
+for _ in range(15):
+    print(limiter.allow_request())  # Will print True for the first 10 requests, then False
+    time.sleep(0.1)  # Wait a bit between requests
+
+time.sleep(5)  # Wait for bucket to refill
+print(limiter.allow_request())  # True