Spaces:
Running
Running
File size: 8,221 Bytes
2c72e40 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 |
"""
ISO20022 SWIFT MT564 Documentation Scraper
This script scrapes the SWIFT MT564 (Corporate Action Notification) documentation
from the ISO20022 website and converts it into structured JSON data for model training.
"""
import os
import json
import argparse
import logging
from typing import Dict, List, Any, Optional
import requests
from bs4 import BeautifulSoup
import trafilatura
# Configure logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
# Constants
BASE_URL = "https://www.iso20022.org/15022/uhb/finmt564.htm"
OUTPUT_DIR = "../data/raw"
def parse_args():
parser = argparse.ArgumentParser(description="Scrape SWIFT MT564 documentation from ISO20022 website")
parser.add_argument(
"--url",
type=str,
default=BASE_URL,
help="URL of the ISO20022 SWIFT MT564 documentation"
)
parser.add_argument(
"--output_dir",
type=str,
default=OUTPUT_DIR,
help="Directory to save scraped data"
)
parser.add_argument(
"--format",
type=str,
choices=["json", "txt"],
default="json",
help="Output format (json or txt)"
)
return parser.parse_args()
def fetch_page(url: str) -> Optional[str]:
"""Fetch HTML content from URL"""
try:
logger.info(f"Fetching {url}")
response = requests.get(url, timeout=30)
response.raise_for_status()
return response.text
except requests.RequestException as e:
logger.error(f"Error fetching {url}: {e}")
return None
def extract_text_with_trafilatura(html: str) -> Optional[str]:
"""Extract main text content using trafilatura"""
try:
return trafilatura.extract(html)
except Exception as e:
logger.error(f"Error extracting text with trafilatura: {e}")
return None
def extract_table_structure(soup: BeautifulSoup) -> List[Dict[str, Any]]:
"""Extract structured data from tables in the documentation"""
tables = soup.find_all("table")
results = []
for table_idx, table in enumerate(tables):
logger.info(f"Processing table {table_idx+1} of {len(tables)}")
# Extract table headers
headers = []
header_row = table.find("tr")
if header_row:
for th in header_row.find_all(["th", "td"]):
headers.append(th.text.strip())
# Process rows
rows = []
for row in table.find_all("tr")[1:]: # Skip header row
cell_data = {}
cells = row.find_all(["td", "th"])
for i, cell in enumerate(cells):
if i < len(headers):
header = headers[i]
cell_data[header] = cell.text.strip()
else:
# Handle case where cell doesn't have a matching header
cell_data[f"column_{i}"] = cell.text.strip()
if cell_data:
rows.append(cell_data)
results.append({
"table_id": table_idx + 1,
"headers": headers,
"rows": rows
})
return results
def extract_sequence_information(soup: BeautifulSoup) -> Dict[str, Any]:
"""Extract information about MT564 sequence structure"""
sequences = []
# Look for sequence headers (typically h2 or h3 elements)
sequence_headers = soup.find_all(["h2", "h3", "h4"])
for header in sequence_headers:
text = header.text.strip()
# Check if it's a sequence header (contains "Sequence" and a letter)
if "sequence" in text.lower() and any(f"sequence {letter}" in text.lower() for letter in "abcdef"):
sequence_name = text
# Find details about this sequence
details = []
next_element = header.find_next()
while next_element and next_element.name not in ["h2", "h3", "h4"]:
if next_element.name == "p":
details.append(next_element.text.strip())
next_element = next_element.find_next()
# Find the table immediately following this header
table = header.find_next("table")
fields = []
if table:
rows = table.find_all("tr")[1:] # Skip header row
for row in rows:
cells = row.find_all(["td", "th"])
if len(cells) >= 3:
field = {
"tag": cells[0].text.strip(),
"name": cells[1].text.strip(),
"status": cells[2].text.strip()
}
if len(cells) > 3:
field["format"] = cells[3].text.strip()
fields.append(field)
sequences.append({
"name": sequence_name,
"details": details,
"fields": fields
})
return {"sequences": sequences}
def parse_documentation(html: str) -> Dict[str, Any]:
"""Parse the MT564 documentation and extract structured information"""
soup = BeautifulSoup(html, "html.parser")
# Extract general information
title = soup.title.text.strip() if soup.title else "MT564 Documentation"
# Get all paragraphs
paragraphs = [p.text.strip() for p in soup.find_all("p") if p.text.strip()]
# Extract tables
tables = extract_table_structure(soup)
# Extract sequence information
sequence_info = extract_sequence_information(soup)
# Combine all information
result = {
"title": title,
"general_description": paragraphs[:3] if len(paragraphs) >= 3 else paragraphs,
"tables": tables,
"sequences": sequence_info["sequences"]
}
return result
def save_output(data: Dict[str, Any], output_dir: str, format: str = "json"):
"""Save extracted data to the output directory"""
os.makedirs(output_dir, exist_ok=True)
if format == "json":
output_file = os.path.join(output_dir, "mt564_documentation.json")
with open(output_file, "w", encoding="utf-8") as f:
json.dump(data, f, indent=2, ensure_ascii=False)
logger.info(f"Saved JSON data to {output_file}")
else: # txt format
output_file = os.path.join(output_dir, "mt564_documentation.txt")
with open(output_file, "w", encoding="utf-8") as f:
f.write(f"# {data['title']}\n\n")
f.write("## General Description\n\n")
for para in data["general_description"]:
f.write(f"{para}\n\n")
f.write("## Sequences\n\n")
for seq in data["sequences"]:
f.write(f"### {seq['name']}\n\n")
for detail in seq["details"]:
f.write(f"{detail}\n\n")
f.write("#### Fields\n\n")
for field in seq["fields"]:
f.write(f"- {field['tag']}: {field['name']} ({field['status']})\n")
f.write("\n")
logger.info(f"Saved text data to {output_file}")
def main():
args = parse_args()
# Fetch the HTML content
html_content = fetch_page(args.url)
if not html_content:
logger.error("Failed to fetch the documentation. Exiting.")
return
# Extract and save raw text content
text_content = extract_text_with_trafilatura(html_content)
if text_content:
os.makedirs(args.output_dir, exist_ok=True)
raw_text_file = os.path.join(args.output_dir, "mt564_raw_text.txt")
with open(raw_text_file, "w", encoding="utf-8") as f:
f.write(text_content)
logger.info(f"Saved raw text to {raw_text_file}")
# Parse structured information
structured_data = parse_documentation(html_content)
# Save output in the requested format
save_output(structured_data, args.output_dir, args.format)
logger.info("Scraping complete!")
if __name__ == "__main__":
main() |