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import subprocess
from pathlib import Path
import sys
import pandas as pd
from datetime import datetime, timedelta
from dotenv import load_dotenv
DAYS_OLD = 7
MERGED_PATH = Path("data/merged/features/merged_features.parquet")
ARCHIVE_DIR = Path("data/merged/archive")
ARCHIVE_DIR.mkdir(parents=True, exist_ok=True)
def run_script(script, args=None):
cmd = [sys.executable, str(Path(__file__).parent / script)]
if args:
cmd += args
print(f"Running: {' '.join(cmd)}")
result = subprocess.run(cmd, check=True)
return result
def archive_old_records():
feature_files = [
Path("data/merged/features/crypto_features.parquet"),
Path("data/merged/features/stocks_features.parquet")
]
now = datetime.utcnow()
cutoff = int((now - timedelta(days=DAYS_OLD)).timestamp() * 1000)
for feature_path in feature_files:
if not feature_path.exists():
print(f"[WARN] {feature_path} does not exist.")
continue
df = pd.read_parquet(feature_path)
old = df.loc[df['interval_timestamp'] < cutoff].copy()
keep = df.loc[df['interval_timestamp'] >= cutoff].copy()
if old.empty:
print(f"[INFO] No records to archive in {feature_path}.")
continue
# Group by day (UTC) and write each group to a separate parquet file under archive/{day}/
old['archive_date'] = pd.to_datetime(old['interval_timestamp'], unit='ms').dt.strftime('%Y%m%d')
for day, group in old.groupby('archive_date'):
day_dir = ARCHIVE_DIR / day
day_dir.mkdir(parents=True, exist_ok=True)
out_path = day_dir / f"{feature_path.stem}_archived_{day}.parquet"
if out_path.exists():
existing = pd.read_parquet(out_path)
group = pd.concat([existing, group.drop(columns=['archive_date'])], ignore_index=True)
else:
group = group.drop(columns=['archive_date'])
group.to_parquet(out_path, index=False)
print(f"[ARCHIVE] {len(group)} records -> {out_path}")
# Save the remaining (unarchived) records back to the feature file
keep.to_parquet(feature_path, index=False)
print(f"[INFO] Archived {len(old)} records from {feature_path}. {len(keep)} remain.")
def store_in_cloud():
# Import StorageHandler from cloud_utils, ensuring src is in sys.path
import os
import sys
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..', 'src')))
from data_cloud.cloud_utils import StorageHandler
# Filebase credentials from env
load_dotenv()
endpoint_url = os.getenv("FILEBASE_ENDPOINT")
access_key = os.getenv("FILEBASE_ACCESS_KEY")
secret_key = os.getenv("FILEBASE_SECRET_KEY")
bucket_name = os.getenv("FILEBASE_BUCKET")
if not all([endpoint_url, access_key, secret_key, bucket_name]):
print("[ERROR] Filebase credentials not set in environment.")
return
storage = StorageHandler(endpoint_url, access_key, secret_key, bucket_name)
merged_dir = os.path.join("data", "merged")
archive_dir = os.path.join(merged_dir, "archive")
# Upload all files in merged except archive
for root, dirs, files in os.walk(merged_dir):
# Skip archive subdir for now
if os.path.abspath(root) == os.path.abspath(archive_dir):
continue
for fname in files:
local_path = os.path.join(root, fname)
rel_path = os.path.relpath(local_path, "data")
key = rel_path.replace(os.sep, "/")
with open(local_path, "rb") as f:
data = f.read()
storage.upload(key, data)
# Only upload archive files newer than DAYS_OLD days
import time
cutoff = time.time() - DAYS_OLD * 86400
if os.path.exists(archive_dir):
for fname in os.listdir(archive_dir):
local_path = os.path.join(archive_dir, fname)
if not os.path.isfile(local_path):
continue
mtime = os.path.getmtime(local_path)
if mtime >= cutoff:
rel_path = os.path.relpath(local_path, "data")
key = rel_path.replace(os.sep, "/")
with open(local_path, "rb") as f:
data = f.read()
storage.upload(key, data)
# Save stocks and crypto features to data/merged/raw
def save_raw_features():
import shutil
raw_dir = Path('data/merged/raw')
raw_dir.mkdir(parents=True, exist_ok=True)
src_stocks = Path('data/merged/features/stocks_features.parquet')
src_crypto = Path('data/merged/features/crypto_features.parquet')
dst_stocks = raw_dir / 'stocks_features.parquet'
dst_crypto = raw_dir / 'crypto_features.parquet'
if src_stocks.exists():
shutil.copy2(src_stocks, dst_stocks)
print(f"[RAW] Saved stocks features to {dst_stocks}")
else:
print(f"[RAW] Source stocks features not found: {src_stocks}")
if src_crypto.exists():
shutil.copy2(src_crypto, dst_crypto)
print(f"[RAW] Saved crypto features to {dst_crypto}")
else:
print(f"[RAW] Source crypto features not found: {src_crypto}")
def main():
# Run all merge steps
run_script('merge_0.py')
run_script('merge_1.py', [
'--latest', 'data/advisorai-data/features/latest_features.parquet',
'--finnhub', 'data/advisorai-data/features/latest_features.parquet',
'--out', 'data/merged/features/merged_features.parquet'
])
run_script('merge_2.py')
run_script('merge_3.py')
run_script('merge_4.py')
run_script('separator.py')
run_script('merge_5.py')
run_script('merge_6.py')
run_script('merge_7.py')
save_raw_features()
# Extract symbols from exchange symbol data before data fillers
try:
run_script('extract_symbols.py')
except subprocess.CalledProcessError as e:
print(f"[WARNING] Symbol extraction failed: {e}")
# Remove rows with null symbols after symbol extraction
try:
run_script('remove_null_symbols.py')
except subprocess.CalledProcessError as e:
print(f"[WARNING] Null symbol removal failed: {e}")
# # Run normalization scripts with error handling
# run_script('stocks_data_filler.py')
# try:
# run_script('crypto_data_filler.py')
# except subprocess.CalledProcessError as e:
# print(f"[WARNING] Crypto data filler failed: {e}")
# Merge temp files into merged - with error handling
try:
run_script('merge_temp.py')
except subprocess.CalledProcessError as e:
print(f"[WARNING] Merge temp failed: {e}")
try:
run_script('merge_sant.py')
except subprocess.CalledProcessError as e:
print(f"[WARNING] Santiment merge failed: {e}")
try:
run_script('merge_santiment_with_crypto.py')
except subprocess.CalledProcessError as e:
print(f"[WARNING] Santiment-crypto merge failed: {e}")
# # Final comprehensive null value handling - clean up any remaining nulls
# try:
# run_script('run_final_null_handling.py')
# except subprocess.CalledProcessError as e:
# print(f"[WARNING] Final null handling failed: {e}")
# # Normalize features
# run_script('normalize.py')
# # Normalize train files for both crypto and stocks
# run_script('norm/crypto.py', ['--train'])
# run_script('norm/stocks.py', ['--train'])
# Archive old records
archive_old_records()
# Generate and store full report
run_script('full_report.py')
# Store all merged data in cloud
store_in_cloud()
print("[OK] All merge steps, null handling, normalization, and reporting completed successfully.")
if __name__ == "__main__":
main()
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