update python backend.

BackCodes.py

+import pandas as pd
+import difflib
+
+# Read data
+df = pd.read_excel('DataSet.xlsx')
+
+
+def find_most_similar_word(input_word, word_list):
+    similarities = difflib.get_close_matches(input_word, word_list)
+    return similarities[0] if similarities else None
+
+
+def find_different_letters(input_word, similar_word):
+    differences = []
+    for char1, char2 in zip(input_word, similar_word):
+        if char1 != char2:
+            differences.append(char1)
+    return ''.join(differences)
+
+
+# Input word
+input_word = input()
+most_similar_word = find_most_similar_word(input_word, df['words'])
+
+if most_similar_word:
+    # Find different letters
+    different_letters = find_different_letters(input_word, most_similar_word)
+    print("User Input:", input_word)
+    print("Most Match:", most_similar_word)
+
+else:
+    print("No similar word found in the dataset.")
+
+
+user_input = input_word
+candidate_words = [most_similar_word]
+
+
+# Function to find differing letters
+def find_differing_letters(input_word, candidate_word):
+    differing_letters = list(difflib.ndiff(input_word, candidate_word))
+    differing_letters = [char[2] for char in differing_letters if char[0] != ' ']
+    return ''.join(differing_letters)
+
+# Initialize variables to track the most matching word and its differing letters
+most_matching_word = None
+differing_letters = None
+
+for candidate_word in candidate_words:
+    candidate_differing_letters = find_differing_letters(user_input, candidate_word)
+    if differing_letters is None or len(candidate_differing_letters) < len(differing_letters):
+        differing_letters = candidate_differing_letters
+        most_matching_word = candidate_word
+
+if differing_letters:
+    print(f"Differing Letters: {differing_letters}")
+    # Differentiating stage here
+else:
+    print("No differing letters found.")
+
+
+#--------------xxxxx
+# Input word and letter
+input_word = most_similar_word
+input_letter = differing_letters
+
+# Find the first row
+row = df[df['words'] == input_word].iloc[0]
+
+initial_position = None
+middle_position = None
+end_position = None
+
+if input_letter in row['initial']:
+    initial_position = row['initial'].index(input_letter)
+
+if input_letter in row['middle']:
+    middle_position = row['middle'].index(input_letter)
+
+if input_letter in row['end']:
+    end_position = row['end'].index(input_letter)
+
+# Print
+if initial_position is not None:
+    print("Position: initial")
+if middle_position is not None:
+    print("Position: middle")
+if end_position is not None:
+    print("Position: end")
+
+# Check if differing_letter is not None before getting its length
+if differing_letters is not None:
+    differing_letter_count = len(differing_letters)
+    print(f"Number of Different Letters: {differing_letter_count}")
+else:
+    print("No differing letter found.")

FlutterAPI_Word.py

+from flask import Flask, request, jsonify
+from flask_cors import CORS
+import pandas as pd
+import difflib
+
+# Read data
+df = pd.read_excel('DataSet.xlsx')
+
+app = Flask(__name__)
+CORS(app)
+
+def find_most_similar_word(input_word, word_list):
+    similarities = difflib.get_close_matches(input_word, word_list)
+    return similarities[0] if similarities else None
+
+def find_different_letters(input_word, similar_word):
+    differences = []
+    for char1, char2 in zip(input_word, similar_word):
+        if char1 != char2:
+            differences.append(char1)
+    return ''.join(differences)
+
+@app.route('/API_Word', methods=['POST'])
+def compare_words():
+    try:
+        data = request.get_json()
+        input_word = data['input_word']
+
+        user_input = input_word
+        most_similar_word = find_most_similar_word(input_word, df['words'])
+
+        if most_similar_word:
+            different_letters = find_different_letters(input_word, most_similar_word)
+            user_input = input_word
+            candidate_words = [most_similar_word]
+
+            def find_differing_letters(input_word, candidate_word):
+                differing_letters = list(difflib.ndiff(input_word, candidate_word))
+                differing_letters = [char[2] for char in differing_letters if char[0] != ' ']
+                return ''.join(differing_letters)
+
+            most_matching_word = None
+            differing_letters = None
+
+            for candidate_word in candidate_words:
+                candidate_differing_letters = find_differing_letters(user_input, candidate_word)
+                if differing_letters is None or len(candidate_differing_letters) < len(differing_letters):
+                    differing_letters = candidate_differing_letters
+                    most_matching_word = candidate_word
+
+            if differing_letters:
+                position_info = []
+                input_word = most_matching_word
+                input_letter = differing_letters
+                row = df[df['words'] == input_word].iloc[0]
+
+                if input_letter in row['initial']:
+                    position_info.append("Position: initial")
+                if input_letter in row['middle']:
+                    position_info.append("Position: middle")
+                if input_letter in row['end']:
+                    position_info.append("Position: end")
+
+                differing_letter_count = len(differing_letters)
+                position_info.append(f"Number of Different Letters: {differing_letter_count}")
+
+                return jsonify({
+                    "User Input": user_input,
+                    "Most Match": most_matching_word,
+                    "Differing Letters": differing_letters,
+                    "Position Info": position_info
+                })
+
+        return jsonify({"message": "No similar word found in the dataset."})
+
+    except Exception as e:
+        return jsonify({"error": str(e)}), 400
+
+if __name__ == '__main__':
+    app.run(host='0.0.0.0', debug=True)