dissertation-dataset / scripts /test_form4_pipeline.py
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# test_form4_pipeline.py
# Quick smoke-test for the Form 4 collection pipeline.
# Runs the full pipeline (metadata fetch → XML download → parse) on
# 5 well-known S&P 500 companies for 2024 only (~2-5 minutes).
#
# Checks:
# 1. EDGAR submissions API is reachable and returns Form 4 metadata
# 2. XML download and parsing produces valid transaction rows
# 3. All expected columns are present
# 4. Values are sensible (dates, numeric fields, A/D codes)
#
# Run: python scripts/test_form4_pipeline.py
import time
import threading
import requests
import pandas as pd
from xml.etree import ElementTree as ET
# ── Test config ────────────────────────────────────────────────────────────────
TEST_CIKS = {
320193: 'AAPL', # Apple
789019: 'MSFT', # Microsoft
1045810: 'NVDA', # NVIDIA
1018724: 'AMZN', # Amazon
1652044: 'GOOGL', # Alphabet
}
DATE_START = '2024-01-01'
DATE_END = '2024-12-31'
MAX_XML_PER_CIK = 3 # only parse first 3 XMLs per company — keeps test fast
HEADERS = {'User-Agent': 'S2880814 University of Edinburgh s.g.vishnu@sms.ed.ac.uk'}
TIMEOUT = 15
EXPECTED_INDEX_COLS = {'cik', 'ticker', 'filing_date', 'accession', 'primary_doc'}
EXPECTED_TXN_COLS = {
'cik', 'ticker', 'filing_date', 'accession',
'owner_name', 'is_director', 'is_officer', 'is_ten_pct_owner', 'officer_title',
'security_title', 'transaction_date', 'transaction_code',
'acquired_disposed', 'shares', 'price_per_share', 'shares_after_txn',
}
PASS = ' [PASS]'
FAIL = ' [FAIL]'
INFO = ' [INFO]'
# ── Rate limiter (same as main script) ────────────────────────────────────────
class RateLimiter:
def __init__(self, rate):
self._lock = threading.Lock()
self._min_gap = 1.0 / rate
self._last = 0.0
def wait(self):
with self._lock:
gap = self._min_gap - (time.monotonic() - self._last)
if gap > 0:
time.sleep(gap)
self._last = time.monotonic()
limiter = RateLimiter(8.0)
def safe_get(url, retries=3):
for attempt in range(retries):
limiter.wait()
try:
r = requests.get(url, headers=HEADERS, timeout=TIMEOUT)
if r.status_code == 200:
return r
elif r.status_code == 429:
print(f" [429] Rate limited, sleeping 10s...")
time.sleep(10)
except requests.RequestException as e:
print(f" [WARN] Request error (attempt {attempt+1}): {e}")
time.sleep(2)
return None
# ── Test 1: EDGAR API reachability ─────────────────────────────────────────────
print("=" * 60)
print("TEST 1 — EDGAR API reachability")
print("=" * 60)
r = safe_get("https://data.sec.gov/submissions/CIK0000320193.json") # Apple
if r:
data = r.json()
company_name = data.get('name', 'unknown')
print(f"{PASS} EDGAR submissions API reachable")
print(f"{INFO} Response: {company_name} (CIK 320193 = Apple)")
else:
print(f"{FAIL} Could not reach EDGAR API — check internet connection")
exit(1)
# ── Test 2: Form 4 metadata fetch ──────────────────────────────────────────────
print()
print("=" * 60)
print("TEST 2 — Form 4 metadata fetch (5 companies, 2024 only)")
print("=" * 60)
def get_form4_meta(cik):
r = safe_get(f"https://data.sec.gov/submissions/CIK{cik:010d}.json")
if not r:
return []
data = r.json()
recent = data.get('filings', {}).get('recent', {})
forms = recent.get('form', [])
accs = recent.get('accessionNumber', [])
dates = recent.get('filingDate', [])
docs = recent.get('primaryDocument', [])
result = []
for form, acc, date, doc in zip(forms, accs, dates, docs):
if form == '4' and DATE_START <= date <= DATE_END:
result.append({'accession': acc, 'filing_date': date, 'primary_doc': doc})
return result
index_rows = []
all_test_filings = []
for cik, ticker in TEST_CIKS.items():
filings = get_form4_meta(cik)
print(f"{INFO} {ticker:6s} (CIK {cik}): {len(filings):3d} Form 4 filings in 2024")
if filings:
print(f"{PASS} Metadata fetch OK — sample accession: {filings[0]['accession']}")
else:
print(f"{FAIL} No Form 4 filings found for {ticker} in 2024")
for f in filings:
index_rows.append({
'cik': cik, 'ticker': ticker,
'filing_date': f['filing_date'],
'accession': f['accession'],
'primary_doc': f['primary_doc'],
})
all_test_filings.append((cik, ticker, f))
print(f"\n{INFO} Total filings collected across 5 companies: {len(index_rows)}")
# Column check on index
index_df = pd.DataFrame(index_rows)
missing_cols = EXPECTED_INDEX_COLS - set(index_df.columns)
if not missing_cols:
print(f"{PASS} Index columns all present: {sorted(index_df.columns.tolist())}")
else:
print(f"{FAIL} Missing index columns: {missing_cols}")
# ── Test 3: XML download and parsing ──────────────────────────────────────────
print()
print("=" * 60)
print(f"TEST 3 — XML download + parse (first {MAX_XML_PER_CIK} filings per company)")
print("=" * 60)
def find_xml_in_filing(cik, accession):
"""Fetch filing directory and return the XML data filename."""
import re
acc_clean = accession.replace('-', '')
r = safe_get(f"https://www.sec.gov/Archives/edgar/data/{cik}/{acc_clean}/")
if not r:
return None
matches = re.findall(r'href="([^"]+\.xml)"', r.text, re.IGNORECASE)
for m in matches:
fname = m.split('/')[-1]
if fname and 'index' not in fname.lower():
return fname
return None
def parse_form4(cik, ticker, accession, primary_doc, filing_date):
"""
Download Form 4 XML and extract non-derivative transactions.
Resolution order (no extra API calls in the common case):
1. If primaryDoc is .htm, try swapping extension to .xml first
2. If that fails, fall back to directory listing (1 extra call)
3. If all else fails, return error
"""
acc_clean = accession.replace('-', '')
candidates = [primary_doc]
if primary_doc.lower().endswith(('.htm', '.html')):
xml_variant = primary_doc.rsplit('.', 1)[0] + '.xml'
candidates = [xml_variant, primary_doc]
print(f" [INFO] HTML primaryDoc — trying XML variant first: {xml_variant}")
root = None
tried = []
for doc in candidates:
url = f"https://www.sec.gov/Archives/edgar/data/{cik}/{acc_clean}/{doc}"
r = safe_get(url)
tried.append(doc)
if not r:
print(f" [WARN] HTTP failed for {doc}")
continue
try:
root = ET.fromstring(r.content)
print(f" [INFO] Parsed successfully: {doc}")
break
except ET.ParseError as e:
print(f" [WARN] XML parse error on {doc}: {e}")
continue
# Last resort: directory listing
if root is None:
print(f" [INFO] Trying directory listing fallback...")
xml_fname = find_xml_in_filing(cik, accession)
if xml_fname and xml_fname not in tried:
url = f"https://www.sec.gov/Archives/edgar/data/{cik}/{acc_clean}/{xml_fname}"
r = safe_get(url)
if r:
try:
root = ET.fromstring(r.content)
print(f" [INFO] Directory fallback succeeded: {xml_fname}")
except ET.ParseError as e:
return None, f"All fallbacks exhausted. Last error: {e}"
else:
return None, "HTTP failed on directory fallback"
elif xml_fname in tried:
return None, "Directory fallback returned same filename already tried"
else:
return None, "No XML found in filing directory"
if root is None:
return None, "Could not obtain valid XML root"
owner_name = ''
is_dir = is_off = is_10pct = '0'
officer_title = ''
for rpt in root.findall('.//reportingOwner'):
owner_name = rpt.findtext('.//rptOwnerName', '').strip()
rel = rpt.find('.//reportingOwnerRelationship')
if rel is not None:
is_dir = rel.findtext('isDirector', '0').strip()
is_off = rel.findtext('isOfficer', '0').strip()
is_10pct = rel.findtext('isTenPercentOwner', '0').strip()
officer_title = rel.findtext('officerTitle', '').strip()
records = []
for txn in root.findall('.//nonDerivativeTransaction'):
records.append({
'cik': cik,
'ticker': ticker,
'filing_date': filing_date,
'accession': accession,
'owner_name': owner_name,
'is_director': is_dir,
'is_officer': is_off,
'is_ten_pct_owner': is_10pct,
'officer_title': officer_title,
'security_title': txn.findtext('.//securityTitle/value', '').strip(),
'transaction_date': txn.findtext('.//transactionDate/value', '').strip(),
'transaction_code': txn.findtext('.//transactionCoding/transactionCode', '').strip(),
'acquired_disposed': txn.findtext(
'.//transactionAmounts/transactionAcquiredDisposedCode/value', '').strip(),
'shares': txn.findtext(
'.//transactionAmounts/transactionShares/value', ''),
'price_per_share': txn.findtext(
'.//transactionAmounts/transactionPricePerShare/value', ''),
'shares_after_txn': txn.findtext(
'.//postTransactionAmounts/sharesOwnedFollowingTransaction/value', ''),
})
return records, None
txn_rows = []
xml_ok = 0
xml_fail = 0
xml_empty = 0
# Group by CIK and limit to MAX_XML_PER_CIK each
from collections import defaultdict
by_cik = defaultdict(list)
for cik, ticker, f in all_test_filings:
by_cik[cik].append((ticker, f))
for cik, items in by_cik.items():
ticker = items[0][0]
sample = items[:MAX_XML_PER_CIK]
print(f"\n {ticker} — parsing {len(sample)} XML(s):")
for _, f in sample:
records, err = parse_form4(cik, ticker, f['accession'], f['primary_doc'], f['filing_date'])
if err:
print(f" {FAIL} {f['accession']}: {err}")
xml_fail += 1
elif records is None:
print(f" {FAIL} {f['accession']}: no result returned")
xml_fail += 1
elif len(records) == 0:
print(f" {INFO} {f['accession']}: parsed OK but 0 non-derivative transactions (options only filing)")
xml_empty += 1
xml_ok += 1
else:
r0 = records[0]
print(f" {PASS} {f['accession']}: {len(records)} transaction(s)")
print(f" Insider : {r0['owner_name']} | Title: {r0['officer_title']}")
print(f" Date : {r0['transaction_date']} | Code: {r0['transaction_code']} | A/D: {r0['acquired_disposed']}")
print(f" Shares : {r0['shares']} @ ${r0['price_per_share']}")
xml_ok += 1
txn_rows.extend(records)
# ── Test 4: Output validation ──────────────────────────────────────────────────
print()
print("=" * 60)
print("TEST 4 — Output validation")
print("=" * 60)
if txn_rows:
txn_df = pd.DataFrame(txn_rows)
# Column check
missing = EXPECTED_TXN_COLS - set(txn_df.columns)
if not missing:
print(f"{PASS} All expected transaction columns present")
else:
print(f"{FAIL} Missing columns: {missing}")
# A/D code check
valid_ad = txn_df['acquired_disposed'].isin(['A', 'D', ''])
if valid_ad.all():
print(f"{PASS} acquired_disposed values all valid (A/D/blank)")
else:
bad = txn_df[~valid_ad]['acquired_disposed'].unique()
print(f"{FAIL} Unexpected acquired_disposed values: {bad}")
# Transaction code check
known_codes = {'P', 'S', 'A', 'D', 'F', 'M', 'G', 'C', 'E', 'H', 'I', 'J', 'L', 'O', 'U', 'W', 'X', 'Z', ''}
bad_codes = set(txn_df['transaction_code'].unique()) - known_codes
if not bad_codes:
print(f"{PASS} Transaction codes all recognised: {sorted(txn_df['transaction_code'].unique())}")
else:
print(f"{FAIL} Unknown transaction codes: {bad_codes}")
# Date format check
try:
pd.to_datetime(txn_df['transaction_date'])
print(f"{PASS} transaction_date parses as dates OK")
except Exception:
print(f"{FAIL} transaction_date has unparseable values")
# Sample rows
print(f"\n{INFO} Sample transactions (first 5 rows):")
print(txn_df[['ticker', 'owner_name', 'officer_title',
'transaction_date', 'transaction_code',
'acquired_disposed', 'shares', 'price_per_share']].head().to_string(index=False))
else:
print(f"{INFO} No non-derivative transactions found in sampled filings (may be options-only batch)")
# ── Summary ────────────────────────────────────────────────────────────────────
print()
print("=" * 60)
print("SUMMARY")
print("=" * 60)
print(f" XMLs parsed successfully : {xml_ok}")
print(f" XMLs failed : {xml_fail}")
print(f" Filings with 0 non-deriv : {xml_empty}")
print(f" Transaction rows parsed : {len(txn_rows)}")
print()
if xml_fail == 0:
print(" ALL TESTS PASSED — pipeline is working correctly.")
print(" Safe to run the full collect_form4.py overnight.")
else:
print(f" {xml_fail} XML(s) failed — check errors above before full run.")
print("=" * 60)