#!/opt/anaconda3/envs/fidelity/bin/python3
"""
OpenBB Ticker Lookup Skill
Searches for stock ticker symbols by company name using the OpenBB API.
Usage:
./skills/lookup_ticker.py "company name"
./skills/lookup_ticker.py "Broadcom"
./skills/lookup_ticker.py --query "Apple Inc" --limit 5
Output:
- Prints matching ticker symbols with company names
- Optionally saves results to CSV file
"""
import sys
import argparse
import pandas as pd
from datetime import datetime
import os
from openbb import obb
from dotenv import load_dotenv
def search_ticker(query, provider='cboe', limit=10, pat=None):
"""
Search for ticker symbols using OpenBB Platform.
Args:
query (str): Company name or search string
provider (str): Data provider (default: 'cboe')
limit (int): Maximum number of results to return
pat (str): OpenBB Personal Access Token (optional)
Returns:
list: List of dictionaries with ticker information
"""
try:
# Login with PAT if provided
if pat:
try:
obb.user.credentials.openbb_pat = pat
except Exception as e:
print(f"Warning: Could not login with PAT: {e}")
print(f"Searching for: '{query}' (provider: {provider})")
# Use OpenBB equity search
result = obb.equity.search(query=query, provider=provider)
# Convert result to list of dictionaries
if hasattr(result, 'to_dataframe'):
# Convert OBBject to DataFrame then to records
df = result.to_dataframe()
results = df.to_dict('records')
elif hasattr(result, 'results'):
# Some results have a .results attribute
results = result.results
if not isinstance(results, list):
# If results is not a list, try to convert
try:
df = pd.DataFrame([results])
results = df.to_dict('records')
except:
results = [results]
elif isinstance(result, list):
results = result
else:
print(f"Unexpected result format: {type(result)}")
return []
# Limit results
if limit and len(results) > limit:
results = results[:limit]
return results
except ImportError:
print("ERROR: OpenBB not installed. Install with: pip install openbb")
return []
except Exception as e:
print(f"ERROR: {e}")
import traceback
traceback.print_exc()
return []
def format_results(results):
"""
Format search results for display.
Args:
results (list): List of ticker information dictionaries
Returns:
pd.DataFrame: Formatted results
"""
if not results:
return None
# Convert to DataFrame for nice formatting
df = pd.DataFrame(results)
# Common fields to display (adjust based on actual API response)
# Priority order for columns
priority_cols = ['symbol', 'name', 'exchange', 'dpm_name', 'post_station',
'type', 'market_cap', 'country', 'cik']
display_cols = []
for col in priority_cols:
if col in df.columns:
display_cols.append(col)
# Add any remaining columns not in priority list
for col in df.columns:
if col not in display_cols:
display_cols.append(col)
if display_cols:
df = df[display_cols]
return df
def save_results(df, output_dir='data'):
"""
Save search results to CSV file.
Args:
df (pd.DataFrame): Search results
output_dir (str): Directory to save file
Returns:
str: Path to saved file
"""
if df is None or len(df) == 0:
return None
os.makedirs(output_dir, exist_ok=True)
timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
output_file = os.path.join(output_dir, f'ticker_search_{timestamp}.csv')
df.to_csv(output_file, index=False)
return output_file
def main():
"""Main execution function."""
# Load environment variables from .env file
load_dotenv()
# login using PAT from environment variable
openbb_pat = os.getenv('OPENBB_PAT')
if not openbb_pat:
raise ValueError("OPENBB_PAT environment variable not set")
obb.user.credentials.openbb_pat = openbb_pat
parser = argparse.ArgumentParser(
description='Search for stock ticker symbols by company name using OpenBB API'
)
parser.add_argument(
'query',
nargs='?',
help='Company name or search string (e.g., "Broadcom")'
)
parser.add_argument(
'--query', '-q',
dest='query_flag',
help='Company name or search string (alternative format)'
)
parser.add_argument(
'--provider', '-p',
default='cboe',
help='Data provider (default: cboe, options: cboe, nasdaq, sec)'
)
parser.add_argument(
'--limit', '-l',
type=int,
default=10,
help='Maximum number of results (default: 10)'
)
parser.add_argument(
'--api-key', '-k',
help='OpenBB PAT (or set OPENBB_PAT environment variable)'
)
parser.add_argument(
'--save', '-s',
action='store_true',
help='Save results to CSV file in data/ directory'
)
parser.add_argument(
'--output-dir', '-o',
default='data',
help='Directory to save results (default: data)'
)
args = parser.parse_args()
# Get query from either positional or flag argument
query = args.query or args.query_flag
if not query:
parser.print_help()
print("\nERROR: Please provide a company name to search for")
print("Example: ./skills/lookup_ticker.py \"Broadcom\"")
return 1
# Get PAT from argument or environment
pat = args.api_key or os.environ.get('OPENBB_PAT')
print("=" * 60)
print("OpenBB Ticker Lookup")
print("=" * 60)
if not pat:
print("\nWARNING: No PAT provided. Some providers may require authentication.")
print("Set OPENBB_PAT environment variable or use --api-key flag\n")
# Search for ticker
results = search_ticker(query, args.provider, args.limit, pat)
if not results:
print("\n" + "=" * 60)
print("No results found")
print("=" * 60)
return 0
# Format and display results
df = format_results(results)
print(f"\nFound {len(results)} result(s):\n")
if df is not None:
print(df.to_string(index=False))
else:
# Fallback: print raw results
for i, result in enumerate(results, 1):
print(f"{i}. {result}")
# Save if requested
if args.save and df is not None:
saved_file = save_results(df, args.output_dir)
if saved_file:
print(f"\n✓ Results saved to: {saved_file}")
print("\n" + "=" * 60)
print("SUCCESS: Ticker lookup complete!")
print("=" * 60)
return 0
if __name__ == '__main__':
sys.exit(main())
