Retranslate the complete English edition from Simplified Chinese (#2010)

* Retranslate the complete English edition from Simplified Chinese

* Polish three English explanations after reader-focused review

en/codes/python/chapter_dynamic_programming/unbounded_knapsack.py

@@ -6,41 +6,41 @@ Author: krahets (krahets@163.com)
 
 
 def unbounded_knapsack_dp(wgt: list[int], val: list[int], cap: int) -> int:
-    """Unbounded knapsack: Dynamic programming"""
+    """Unbounded knapsack: dynamic programming"""
     n = len(wgt)
-    # Initialize dp table
+    # Initialize the dp table
     dp = [[0] * (cap + 1) for _ in range(n + 1)]
-    # State transition
+    # State transitions
     for i in range(1, n + 1):
         for c in range(1, cap + 1):
             if wgt[i - 1] > c:
-                # If exceeds knapsack capacity, don't select item i
+                # If item i exceeds the remaining capacity, do not choose it
                 dp[i][c] = dp[i - 1][c]
             else:
-                # The larger value between not selecting and selecting item i
+                # Take the larger value obtained by excluding and including item i
                 dp[i][c] = max(dp[i - 1][c], dp[i][c - wgt[i - 1]] + val[i - 1])
     return dp[n][cap]
 
 
 def unbounded_knapsack_dp_comp(wgt: list[int], val: list[int], cap: int) -> int:
-    """Unbounded knapsack: Space-optimized dynamic programming"""
+    """Unbounded knapsack: space-optimized dynamic programming"""
     n = len(wgt)
-    # Initialize dp table
+    # Initialize the dp table
     dp = [0] * (cap + 1)
-    # State transition
+    # State transitions
     for i in range(1, n + 1):
-        # Traverse in forward order
+        # Traverse in increasing order
         for c in range(1, cap + 1):
             if wgt[i - 1] > c:
-                # If exceeds knapsack capacity, don't select item i
+                # If item i exceeds the remaining capacity, do not choose it
                 dp[c] = dp[c]
             else:
-                # The larger value between not selecting and selecting item i
+                # Take the larger value obtained by excluding and including item i
                 dp[c] = max(dp[c], dp[c - wgt[i - 1]] + val[i - 1])
     return dp[cap]
 
 
-"""Driver Code"""
+"""Driver code"""
 if __name__ == "__main__":
     wgt = [1, 2, 3]
     val = [5, 11, 15]
@@ -48,8 +48,8 @@ if __name__ == "__main__":
 
     # Dynamic programming
     res = unbounded_knapsack_dp(wgt, val, cap)
-    print(f"The maximum item value not exceeding knapsack capacity is {res}")
+    print(f"Maximum total value within the knapsack capacity: {res}")
 
     # Space-optimized dynamic programming
     res = unbounded_knapsack_dp_comp(wgt, val, cap)
-    print(f"The maximum item value not exceeding knapsack capacity is {res}")
+    print(f"Maximum total value within the knapsack capacity: {res}")