Client utilities for fetching market data from Barchart
Project description
barchartFetcher
Client utilities for fetching quotes, options data and fundamental metrics from Barchart.
Requirements & Installation:
- Dependencies:
httpx,nest_asyncio,pandas,beautifulsoup4 - To install, run:
pip install barchartFetcher==1.0.0
Example:
The package exposes several classes—Quotes, Options, Company, Financials, Analysts, Technicals, OptionsStrategies and a convenience wrapper Symbol to access multiple endpoints at once.
quotes = barchartFetcher.Quotes()
q = quotes.quote("AAPL")
print("Keys:\n")
print(q.keys())
print("\nMeta:\n")
pprint(q['meta'])
print("\nData:\n")
pprint(q['data'])
Output:
Keys:
dict_keys(['count', 'total', 'data', 'meta', 'errors'])
Meta:
{'field': {'description': {'averageVolume20d': 'The average number of shares '
'or contracts traded over the '
'last 20 days.',
'highPrice': 'The highest trade price for the day.',
'highPrice1y': 'The highest price over the last '
'52-weeks.',
'lastPrice': 'The last trade price.',
'lowPrice': 'The lowest trade price for the day.',
'lowPrice1y': 'The lowest price over the last '
'52-weeks.',
'openPrice': 'Opening price for the day.',
'percentChange5d': '5-Day Percent Change: The '
'percent difference between the '
'current price and the '
'settlement price from 5 days '
'ago.',
'priceChange5d': '5-Day Price Change: The '
'difference between the current '
'price, and the settlement price '
'from 5 days ago.',
'rangePercent1y': 'The current price range over a '
'52-week period, expressed as a '
'percent. ((last price - 52W low) '
'/ (52W high - 52W low)) * 100.0',
'stochasticK14d': 'Shows (within a range of '
'0%-100%) where the price closed '
'in relation to its price range '
'over the last 14-Days with a '
'3-period exponential moving '
'average applied.',
'symbol': '',
'volume': 'The total number of shares or contracts '
'traded for the day.',
'weightedAlpha': 'A measure of how much a stock has '
'risen or fallen over a one-year '
'period with a higher weighting '
'for recent price activity.'},
'shortName': {'averageVolume20d': '20D Avg Vol',
'highPrice': 'High',
'highPrice1y': '52W High',
'lastPrice': 'Last',
'lowPrice': 'Low',
'lowPrice1y': '52W Low',
'openPrice': 'Open',
'percentChange5d': '5D %Chg',
'priceChange5d': '5D Chg',
'rangePercent1y': '52W Range%',
'stochasticK14d': '14D Stoch %K',
'symbol': 'Symbol',
'volume': 'Volume',
'weightedAlpha': 'Wtd Alpha'},
'type': {'averageVolume20d': 'integer',
'highPrice': 'price',
'highPrice1y': 'price',
'lastPrice': 'price',
'lowPrice': 'price',
'lowPrice1y': 'price',
'openPrice': 'price',
'percentChange5d': 'percentChange',
'priceChange5d': 'priceChange',
'rangePercent1y': 'percent',
'stochasticK14d': 'percent',
'symbol': 'string',
'volume': 'integer',
'weightedAlpha': 'change'}}}
Data:
[{'averageVolume20d': '58,270,727',
'highPrice': '213.34',
'highPrice1y': '260.10',
'lastPrice': '212.44',
'lowPrice': '208.14',
'lowPrice1y': '169.21',
'openPrice': '208.91',
'percentChange5d': '+5.40%',
'priceChange5d': '+10.88',
'rangePercent1y': '47.56%',
'raw': {'averageVolume20d': 58270727,
'highPrice': 213.34,
'highPrice1y': 260.1,
'lastPrice': 212.44,
'lowPrice': 208.14,
'lowPrice1y': 169.21,
'openPrice': 208.91,
'percentChange5d': 0.054,
'priceChange5d': 10.88,
'rangePercent1y': 47.56,
'stochasticK14d': 87.13,
'symbol': 'AAPL',
'volume': 67941805,
'weightedAlpha': -7.38},
'stochasticK14d': '87.13%',
'symbol': 'AAPL',
'volume': '67,941,805',
'weightedAlpha': '-7.38'}]
The Symbol class aggregates calls to different endpoints:
aapl = barchartFetcher.Symbol("AAPL")
quotes_data = aapl.quotes()
print("Keys:\n")
print(quotes_data.keys())
print("\nOptions Overview Keys:\n")
print(quotes_data['options_overview'].keys())
print("\nOptions Overview Data:\n")
pprint(quotes_data['options_overview']['data'])
Output:
Keys:
dict_keys(['performance_past5d', 'performance_past5m', 'performance_past5w', 'price_performance', 'technical_opinion', 'options_overview', 'analysts_rating', 'fundamentals', 'lows_highs', 'quote'])
Options Overview Keys:
dict_keys(['count', 'total', 'data', 'meta', 'errors'])
Options Overview Data:
[{'historicVolatility30d': '21.31%',
'optionsImpliedVolatilityPercentile1y': '75%',
'optionsImpliedVolatilityRank1y': '26.00%',
'optionsPutCallOpenInterestRatio': '0.72',
'optionsPutCallVolumeRatio': '0.41',
'optionsTotalOpenInterest': '5,330,140',
'optionsTotalOpenInterest1m': '5,366,503',
'optionsTotalVolume': '1,827,658',
'optionsTotalVolume1m': '1,106,224',
'optionsWeightedImpliedVolatility': '28.77%',
'optionsWeightedImpliedVolatilityChange': '-0.31%',
'optionsWeightedImpliedVolatilityHigh1y': '65.20%',
'optionsWeightedImpliedVolatilityHighDate1y': '04/08/25',
'optionsWeightedImpliedVolatilityLow1y': '15.97%',
'optionsWeightedImpliedVolatilityLowDate1y': '12/04/24',
'raw': {'historicVolatility30d': 21.31,
'optionsImpliedVolatilityPercentile1y': 0.752,
'optionsImpliedVolatilityRank1y': 25.999041095916,
'optionsPutCallOpenInterestRatio': 0.71798737102943,
'optionsPutCallVolumeRatio': 0.40845524119686,
'optionsTotalOpenInterest': 5330140,
'optionsTotalOpenInterest1m': 5366503,
'optionsTotalVolume': 1827658,
'optionsTotalVolume1m': 1106224,
'optionsWeightedImpliedVolatility': 0.2876826080111,
'optionsWeightedImpliedVolatilityChange': -0.0030605360889064,
'optionsWeightedImpliedVolatilityHigh1y': 0.65202232651026,
'optionsWeightedImpliedVolatilityHighDate1y': '2025-04-08T00:00:00Z',
'optionsWeightedImpliedVolatilityLow1y': 0.15967773544705,
'optionsWeightedImpliedVolatilityLowDate1y': '2024-12-04T00:00:00Z',
'symbol': 'AAPL'},
'symbol': 'AAPL'}]
Working directly with options data:
options = barchartFetcher.Options()
exp = options.options_expirations("AAPL")
pprint(exp)
Output (truncated):
{'count': 21,
'data': [{'callOpenInterest': '254,300',
'callVolume': '675,585',
'expirationDate': '07/03/25',
'expirationType': 'weekly',
'putCallOpenInterestRatio': '0.47',
'putCallVolumeRatio': '0.45',
'putOpenInterest': '120,098',
'putVolume': '302,301',
'raw': {'callOpenInterest': 254300,
'callVolume': 675585,
'expirationDate': '2025-07-03',
'expirationType': 'weekly',
'putCallOpenInterestRatio': 0.4723,
'putCallVolumeRatio': 0.4475,
'putOpenInterest': 120098,
'putVolume': 302301,
'symbol': 'AAPL|20250703|212.50C'},
... # Truncated
'symbol': 'AAPL|20270617|210.00C'},
{'callOpenInterest': '44,751',
'callVolume': '2,369',
'expirationDate': '12/17/27',
'expirationType': 'monthly',
'putCallOpenInterestRatio': '0.46',
'putCallVolumeRatio': '0.22',
'putOpenInterest': '20,692',
'putVolume': '527',
'raw': {'callOpenInterest': 44751,
'callVolume': 2369,
'expirationDate': '2027-12-17',
'expirationType': 'monthly',
'putCallOpenInterestRatio': 0.4624,
'putCallVolumeRatio': 0.2225,
'putOpenInterest': 20692,
'putVolume': 527,
'symbol': 'AAPL|20271217|210.00C'},
'symbol': 'AAPL|20271217|210.00C'}],
'meta': {'field': {'description': {'callOpenInterest': 'The call open '
'interest for the '
'current trading '
'session.',
'callVolume': 'The total call volume for '
'the current trading session '
'for the underlying asset.',
'expirationDate': 'The option expiration '
'date.',
'expirationType': 'The type of option '
'expiration: monthly or '
'weekly.',
'putCallOpenInterestRatio': 'The put/call '
'open interest '
'ratio based '
'on 1-day '
'average open '
'interest for '
'the '
'underlying '
'asset.',
'putCallVolumeRatio': 'The underlying '
"asset's total "
'Put/Call volume '
'ratio for the '
'current trading '
'session.',
'putOpenInterest': 'The put open interest '
'for the current '
'trading session.',
'putVolume': 'The total put volume for the '
'current trading session for '
'the underlying asset.',
'symbol': ''},
'shortName': {'callOpenInterest': 'Call OI',
'callVolume': 'Call Volume',
'expirationDate': 'Exp Date',
'expirationType': 'Exp Type',
'putCallOpenInterestRatio': 'P/C OI',
'putCallVolumeRatio': 'P/C Vol',
'putOpenInterest': 'Put OI',
'putVolume': 'Put Volume',
'symbol': 'Symbol'},
'type': {'callOpenInterest': 'integer',
'callVolume': 'integer',
'expirationDate': 'date',
'expirationType': 'string',
'putCallOpenInterestRatio': 'float',
'putCallVolumeRatio': 'float',
'putOpenInterest': 'integer',
'putVolume': 'integer',
'symbol': 'string'}}},
'total': 21}
Additional examples:
company = barchartFetcher.Company().company_informations("AAPL")
print(list(company["meta"]["field"]["shortName"].items())[:5])
print(list(company["data"][0].items())[:3])
analysts = barchartFetcher.Analysts().earnings_estimates("AAPL")
print(list(analysts["data"][0].items())[:3])
financials = barchartFetcher.Financials().financial_summary_quarterly("AAPL")
print(list(financials["data"][0].items())[:3])
technicals = barchartFetcher.Technicals().moving_averages("AAPL")
print(list(technicals["data"][0].keys())[:3])
strategies = barchartFetcher.OptionsStrategies().covered_calls(baseSymbol="AAPL")
print(len(strategies["data"]))
Outputs (truncated):
[('symbol', 'Symbol'), ('symbolShortName', 'Name'), ('address', 'Address'), ('country', 'Country'), ('website', 'Website')]
[('symbol', 'AAPL'), ('symbolShortName', 'Apple Inc'), ('address', ['ONE APPLE PARK WAY', 'CUPERTINO CA 95014 USA'])]
[('symbol', 'AAPL'), ('estimatedEarnings', '$1.42'), ('estimatedEarnings1qAgo', '$1.61')]
[('symbol', 'AAPL'), ('revenueLastQuarter', '95,359,000'), ('revenue1qAgo', '124,300,000')]
['symbol', 'movingAverage5d', 'priceChange5d']
0
Available helper classes and their main use-cases are summarized below.
| Class | Description | Customizable query parameters |
|---|---|---|
Quotes |
Retrieve quotes, fundamentals and performance statistics | True |
Options |
Access options chains, expirations and volatility metrics | True |
OptionsStrategies |
Screener utilities for common options strategies | True |
Financials |
Income statement, balance sheet and cash flow statements | True |
Analysts |
Analyst ratings and earnings estimates | True |
Company |
Company profile, ratios and insider transactions | True |
Technicals |
Moving averages, stochastics and other indicators | True |
Symbol |
Convenience wrapper combining the above for a single symbol | False (Uses Barchart Default parameters (Recommendend)) |
Results are typically returned as parsed JSON objects or DataFrames (for tables scraped from HTML). The package uses httpx with an internal cookie/session manager to query Barchart endpoints.
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