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Author: coderatul

css.py

@@ -0,0 +1,158 @@
+import re
+import pandas as pd
+import networkx as nx
+import matplotlib.pyplot as plt
+import argparse
+
+def main(file_path, verbose=False):  # Add verbose as a parameter with a default value
+    try:
+        df = pd.read_excel(file_path)
+    except FileNotFoundError:
+        print(f"Error: The file '{file_path}' was not found. Please ensure it exists in the specified directory.")
+        exit()
+    except ValueError as e:
+        print(f"Error: Unable to read the file. Make sure it's a valid Excel file. Details: {e}")
+        exit()
+
+    # Check if the DataFrame is empty
+    if df.empty:
+        print("Error: The provided Excel file is empty.")
+        exit()
+
+    if df.isnull().all().all():
+        print("Error: The Excel file contains no valid data.")
+        exit()
+
+    # Ensure columns have valid names
+    if df.columns.duplicated().any():
+        print("Error: The Excel file contains duplicate transaction names in columns.")
+        exit()
+
+    if any(col == '' for col in df.columns):
+        print("Error: One or more column names in the Excel file are empty.")
+        exit()
+
+    index = 0
+    temp = 0
+
+    # transaction : other transactions
+    other = dict()
+    transactions = [trnsc_name for trnsc_name in df]
+    n_transactions = len(transactions)
+
+    for transaction in transactions:
+        other[transaction] = []
+
+    for transaction in transactions:
+        for othr in range(n_transactions - 1):
+            other[transaction].append(transactions[((temp + 1) % n_transactions)])
+            temp += 1
+        index += 1
+        temp = index
+
+    # Serial schedule corresponding to each transaction
+    column_wise_tnrcs = {}
+    for l in range(0, n_transactions):
+        column_wise_tnrcs[transactions[l]] = []
+
+    temp = 0
+    for l in range(0, n_transactions):
+        column_wise_tnrcs[transactions[l]].extend(list(filter(lambda x: x != '', df[transactions[temp]].dropna().tolist())))
+        temp += 1
+
+    # Nodes of dependency graph
+    nodes = []
+    # Pairs of transactions having conflict
+    conflicting_nodes = []
+    conflicting_pairs = {'r': ['w'],
+                         'w': ['w', 'r']}
+
+    # Finding conflicting pairs
+    for index, row in df.iterrows():
+        for col_name, operation in row.items():
+            if pd.notna(operation):
+                match = re.match(r'([rw])\((\w+)\)', operation)
+                if not match:
+                    print(f"Error: Invalid operation format '{operation}' in column '{col_name}'. Expected 'r(var)' or 'w(var)'.")
+                    exit()
+                op = match.group(1)  # operation
+                var = match.group(2)  # variable
+                if op == 'r':
+                    conflict_rw = conflicting_pairs[op][0] + '(' + var + ')'
+                    if verbose:  # Use the verbose flag to control output
+                        print(f"Transaction {col_name}'s conflicting pair for operation {operation} is {conflict_rw}")
+                    for other_transactions in range(n_transactions - 1):
+                        if conflict_rw in column_wise_tnrcs[other[col_name][other_transactions]]:
+                            nodes.append(col_name)
+                            conflicting_nodes.append(tuple([col_name, other[col_name][other_transactions]]))
+                    column_wise_tnrcs[col_name].remove(operation)
+                else:
+                    conflict_ww = conflicting_pairs[op][0] + '(' + var + ')'
+                    conflict_wr = conflicting_pairs[op][1] + '(' + var + ')'
+                    if verbose:  # Use the verbose flag to control output
+                        print(f"Transaction {col_name}'s conflicting pair for operation {operation} is {conflict_ww} and {conflict_wr}")
+
+                    for other_transactions in range(n_transactions - 1):
+                        if conflict_ww in column_wise_tnrcs[other[col_name][other_transactions]]:
+                            nodes.append(col_name)
+                            conflicting_nodes.append(tuple([col_name, other[col_name][other_transactions]]))
+                    column_wise_tnrcs[col_name].remove(operation)
+
+                    for other_transactions in range(n_transactions - 1):
+                        if conflict_wr in column_wise_tnrcs[other[col_name][other_transactions]]:
+                            nodes.append(col_name)
+                            conflicting_nodes.append(tuple([col_name, other[col_name][other_transactions]]))
+
+    # Building dependency graph
+    G = nx.DiGraph()
+    G.add_nodes_from(nodes)
+    G.add_edges_from(conflicting_nodes)
+
+    # Detect if the graph has cycles
+    try:
+        cycles = list(nx.simple_cycles(G))
+        if cycles:
+            print("Detected cycles:", cycles)
+            print("Therefore, the given schedule is not conflict serializable.")
+        else:
+            print("No cycles detected. The given schedule is conflict serializable.")
+            try:
+                topological_order = list(nx.topological_sort(G))
+                print("Order of serializability:", topological_order)
+            except nx.NetworkXUnfeasible:
+                print("Error: Topological sorting failed despite no cycles detected.")
+    except Exception as e:
+        print(f"Unexpected error during cycle detection or topological sorting: {e}")
+
+    # Draw the graph
+    if not G.nodes or not G.edges:
+        print("Warning: The dependency graph is empty; nothing to plot.")
+    else:
+        pos = nx.spring_layout(G)  # positions for all nodes
+        nx.draw(G, pos, with_labels=True, node_size=3000, node_color='lightblue', font_size=12, font_weight='bold', arrowsize=20)
+
+        # Add text on the plot to indicate if a cycle exists
+        cycle_text = "Cycle Exists, NOT CSS" if cycles else "No Cycle, CSS"
+        text_color = 'red' if cycles else 'green'
+
+        # Determine the center of the graph to place the text dynamically
+        x_center = sum(p[0] for p in pos.values()) / len(pos)
+        y_center = sum(p[1] for p in pos.values()) / len(pos)
+
+        plt.text(x_center, y_center - 0.1, cycle_text, horizontalalignment='center',
+                 fontsize=14, color=text_color, bbox=dict(facecolor='white', alpha=0.7))
+
+        plt.title('Dependency Graph')
+        plt.show()
+
+if __name__ == "__main__":
+    # Set up argument parsing
+    parser = argparse.ArgumentParser(description="Check if a schedule is conflict serializable.")
+    parser.add_argument("file", type=str, help="Path to the Excel file containing the schedule.")
+    parser.add_argument("--verbose", action="store_true", help="Enable verbose output for debugging.")  # Add verbose flag
+    
+    # Parse arguments
+    args = parser.parse_args()
+    
+    # Call the main function with the file path and verbose flag
+    main(args.file, args.verbose)

requirements.txt

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+contourpy==1.3.1
+cycler==0.12.1
+et_xmlfile==2.0.0
+fonttools==4.55.8
+kiwisolver==1.4.8
+matplotlib==3.10.0
+networkx==3.4.2
+numpy==2.2.2
+openpyxl==3.1.5
+packaging==24.2
+pandas==2.2.3
+pillow==11.1.0
+pyparsing==3.2.1
+python-dateutil==2.9.0.post0
+pytz==2025.1
+six==1.17.0
+tzdata==2025.1