rebranch

dataset/load_data.py

@@ -0,0 +1,104 @@
+import csv
+import os
+import requests
+import concurrent.futures
+
+# Define the endpoint URL
+endpoint_url = "http://localhost:8080/v1/qrcodetypes/scan"
+
+# Path to the CSV file
+csv_file_path = "hasExecutable.csv"
+
+# Directory to store the split CSV files
+split_files_dir = "split_csv_files"
+os.makedirs(split_files_dir, exist_ok=True)
+
+# File to store failed requests
+failed_requests_file = "failed_requests.csv"
+
+# Final concatenated CSV file
+final_concatenated_file = "concatenated_split_files.csv"
+
+# Function to ensure URL starts with http:// or https://
+def ensure_url_prefix(url):
+    if not (url.startswith("http://") or url.startswith("https://")):
+        return "https://" + url
+    return url
+
+# Read the CSV file and split into 199 files
+def split_csv_file(csv_file_path, split_files_dir, num_splits=199):
+    with open(csv_file_path, newline='') as csvfile:
+        reader = list(csv.DictReader(csvfile))
+        total_rows = len(reader)
+        rows_per_file = total_rows // num_splits
+        
+        for i in range(num_splits):
+            split_file_path = os.path.join(split_files_dir, f"split_file_{i+1}.csv")
+            with open(split_file_path, 'w', newline='') as split_file:
+                writer = csv.DictWriter(split_file, fieldnames=['url', 'type'])
+                writer.writeheader()
+                start_index = i * rows_per_file
+                end_index = (i + 1) * rows_per_file if i != num_splits - 1 else total_rows
+                for row in reader[start_index:end_index]:
+                    row['url'] = ensure_url_prefix(row['url'])
+                    writer.writerow(row)
+
+# Function to process a CSV file and send POST requests
+def process_csv_file(csv_file_path):
+    failed_requests = []
+    with open(csv_file_path, newline='') as csvfile:
+        reader = csv.DictReader(csvfile)
+        for row in reader:
+            url = row['url']  # Column header for URL is 'url'
+            response = requests.post(endpoint_url, json={"data": url})
+            if response.status_code == 200:
+                print(f"Successfully sent data: {url}")
+            else:
+                print(f"Failed to send data: {url}, Status code: {response.status_code}")
+                failed_requests.append({"url": url, "status_code": response.status_code})
+    return failed_requests
+
+# Function to write failed requests to a CSV file
+def write_failed_requests(failed_requests):
+    if not failed_requests:
+        return
+    with open(failed_requests_file, 'w', newline='') as csvfile:
+        fieldnames = ['url', 'status_code']
+        writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
+        writer.writeheader()
+        for request in failed_requests:
+            writer.writerow(request)
+
+# Function to concatenate all split CSV files into one
+def concatenate_csv_files(split_files_dir, output_file):
+    fieldnames = ['url', 'type']
+    with open(output_file, 'w', newline='') as outfile:
+        writer = csv.DictWriter(outfile, fieldnames=fieldnames)
+        writer.writeheader()
+        for file in os.listdir(split_files_dir):
+            if file.endswith('.csv'):
+                with open(os.path.join(split_files_dir, file), newline='') as infile:
+                    reader = csv.DictReader(infile)
+                    for row in reader:
+                        writer.writerow(row)
+
+# Split the original CSV file into 199 parts
+split_csv_file(csv_file_path, split_files_dir)
+
+# Get the list of split CSV files
+split_files = [os.path.join(split_files_dir, file) for file in os.listdir(split_files_dir) if file.endswith('.csv')]
+
+# Execute the requests concurrently with 199 threads
+all_failed_requests = []
+with concurrent.futures.ThreadPoolExecutor(max_workers=199) as executor:
+    futures = [executor.submit(process_csv_file, split_file) for split_file in split_files]
+    for future in concurrent.futures.as_completed(futures):
+        all_failed_requests.extend(future.result())
+
+# Write all failed requests to a file
+write_failed_requests(all_failed_requests)
+
+# Concatenate all split CSV files into one final file
+concatenate_csv_files(split_files_dir, final_concatenated_file)
+
+print("Processing completed.")

dataset/map_type.py

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+import pandas as pd
+
+# Load the CSV files
+file1 = pd.read_csv('concatenated_split_files1.csv')  
+file2 = pd.read_csv('_select_from_safeqr_url_url_left_join_safeqr_qr_code_qr_on_qr_id_202408101634.csv') 
+
+# Function to strip 'http://' or 'https://' from a URL
+def strip_protocol(url):
+    if isinstance(url, str):
+        return url.replace('https://', '').replace('http://', '')
+    return url
+
+# Apply the strip function to both file1 and file2 URLs
+file1['url_stripped'] = file1['url'].apply(strip_protocol)
+file2['contents_stripped'] = file2['contents'].apply(strip_protocol)
+
+# Create a dictionary from the second file for quick lookup of type and qr_code_id
+url_type_qr_dict = dict(zip(file2['contents_stripped'], zip(file2['result_category'], file2['qr_code_id'])))
+
+# Prepare a copy of file2 to modify without affecting the original
+file2_copy = file2.copy()
+
+# Fill in the result_category in file2_copy
+file2_copy['result_category'] = file2_copy['contents_stripped'].map(lambda x: url_type_qr_dict[x][0] if x in url_type_qr_dict else None)
+
+# Drop the id and stripped columns in file2_copy
+file2_copy = file2_copy.drop(columns=['id', 'contents_stripped'])
+
+# Prepare a copy of file1 to modify without affecting the original
+file1_copy = file1.copy()
+
+# Fill in the qr_code_id in file1_copy based on the match from file2
+file1_copy['qr_code_id'] = file1_copy['url_stripped'].map(lambda x: url_type_qr_dict[x][1] if x in url_type_qr_dict else None)
+
+# Drop the stripped column in file1_copy
+file1_copy = file1_copy.drop(columns=['url_stripped'])
+
+# Save the updated copies to new CSV files
+file1_copy.to_csv('file1_updated.csv', index=False)
+file2_copy.to_csv('db_updated.csv', index=False)