Add materials for "Python Performance Optimization: A Practical Guide"

python-performance-optimization-guide/README.md

@@ -0,0 +1,3 @@
+# Python Performance Optimization: A Practical Guide
+
+This folder provides the code examples for the Real Python tutorial Python Performance Optimization: A Practical Guide.

python-performance-optimization-guide/step-1.py

@@ -0,0 +1,36 @@
+import timeit
+
+
+def count_pairs_slow(numbers, target):
+    count = 0
+    for i in range(len(numbers)):
+        for j in range(i + 1, len(numbers)):
+            if numbers[i] + numbers[j] == target:
+                count += 1
+    return count
+
+
+sample = list(range(5_000))
+target = 4_999
+
+print(count_pairs_slow(sample, target))
+
+slow_time = timeit.timeit(lambda: count_pairs_slow(sample, target), number=10)
+print(f"count_pairs_slow: {slow_time:.4f} seconds")
+
+
+def count_pairs_fast(numbers, target):
+    seen = set()
+    count = 0
+    for number in numbers:
+        complement = target - number
+        if complement in seen:
+            count += 1
+        seen.add(number)
+    return count
+
+
+print(count_pairs_fast(sample, target))
+
+fast_time = timeit.timeit(lambda: count_pairs_fast(sample, target), number=10)
+print(f"count_pairs_fast: {fast_time:.4f} seconds")

python-performance-optimization-guide/step-2.py

@@ -0,0 +1,17 @@
+import timeit
+
+numbers_list = list(range(100_000))
+
+target = 99_999
+
+list_time = timeit.timeit(lambda: target in numbers_list, number=1000)
+
+print(target in numbers_list)
+print(f"list membership: {list_time:.8f} seconds")
+
+numbers_set = set(numbers_list)
+
+set_time = timeit.timeit(lambda: target in numbers_set, number=1000)
+
+print(target in numbers_set)
+print(f"set membership:  {set_time:.8f} seconds")

python-performance-optimization-guide/step-3.py

@@ -0,0 +1,30 @@
+import timeit
+from collections import Counter
+
+words = ["apple", "banana", "apple", "cherry", "banana", "apple"] * 1000
+
+
+def manual_count(items):
+    counts = {}
+    for item in items:
+        if item in counts:
+            counts[item] += 1
+        else:
+            counts[item] = 1
+    return counts
+
+
+print(manual_count(words))
+
+manual_time = timeit.timeit(lambda: manual_count(words), number=1000)
+print(f"manual loop: {manual_time:.4f} seconds")
+
+
+def counter_count(items):
+    return Counter(items)
+
+
+print(counter_count(words))
+
+counter_time = timeit.timeit(lambda: counter_count(words), number=1000)
+print(f"collections.Counter: {counter_time:.4f} seconds")

python-performance-optimization-guide/step-4.py

@@ -0,0 +1,33 @@
+import timeit
+from functools import cache
+
+numbers = list(range(2_000_000))
+
+
+def find_index(target):
+    for i, value in enumerate(numbers):
+        if value == target:
+            return i
+    return -1
+
+
+target = 1_999_999
+
+print(find_index(target))
+
+slow_time = timeit.timeit(lambda: find_index(target), number=20)
+print(f"without cache: {slow_time:.4f} seconds")
+
+
+@cache
+def find_index_cached(target):
+    for i, value in enumerate(numbers):
+        if value == target:
+            return i
+    return -1
+
+
+print(find_index_cached(target))
+
+fast_time = timeit.timeit(lambda: find_index_cached(target), number=20)
+print(f"with cache: {fast_time:.8f} seconds")