A python module that returns stock, cryptocurrency, forex, mutual fund, commodity futures, ETF, and US Treasury financial data from Yahoo Finance.
Current Version: v1.20
Version Released: 12/17/2023
Report any bugs by opening an issue here: https://github.com/JECSand/yahoofinancials/issues
A powerful financial data module used for pulling both fundamental and technical data from Yahoo Finance.
- New analytic methods in v1.20:
- get_insights()
- returns data for:
- 'instrumentInfo'
- 'companySnapshot'
- 'recommendation'
- 'sigDevs'
- 'secReports'
- get_recommendations()
- Example:
print(YahooFinancials('C').get_recommendations())- Example Output:
{
"C": [
{
"recommendedSymbols": [
{
"score": 0.239602,
"symbol": "BAC"
},
{
"score": 0.225134,
"symbol": "JPM"
},
{
"score": 0.167669,
"symbol": "WFC"
},
{
"score": 0.145864,
"symbol": "GS"
},
{
"score": 0.134071,
"symbol": "F"
}
],
"symbol": "C"
}
]
}- As of Version 1.20, YahooFinancials supports a new optional parameter called flat_format.
- When YahooFinancials(flat_format=True), financial statement data will return in a dict instead of a list. The keys of the dict will be the reporting dates.
- Default is False, to ensure backwards compatibility.
- As of Version 1.9, YahooFinancials supports optional parameters for asynchronous execution, proxies, and international requests.
from yahoofinancials import YahooFinancials
tickers = ['AAPL', 'GOOG', 'C']
yahoo_financials = YahooFinancials(tickers, concurrent=True, max_workers=8, country="US")
balance_sheet_data_qt = yahoo_financials.get_financial_stmts('quarterly', 'balance')
print(balance_sheet_data_qt)
proxy_addresses = [ "mysuperproxy.com:5000", "mysuperproxy.com:5001"]
yahoo_financials = YahooFinancials(tickers, concurrent=True, proxies=proxy_addresses)
balance_sheet_data_qt = yahoo_financials.get_financial_stmts('quarterly', 'balance')
print(balance_sheet_data_qt)- yahoofinancials runs on Python 3.7, 3.8, 3.9, 3.10, 3.11, and 3.12
- Installation using pip:
- Linux/Mac:
$ pip install yahoofinancials- Windows (If python doesn't work for you in cmd, try running the following command with just py):
> python -m pip install yahoofinancials
- Installation using github (Mac/Linux):
$ git clone https://github.com/JECSand/yahoofinancials.git
$ cd yahoofinancials
$ python setup.py install- Demo using the included demo script:
$ cd yahoofinancials
$ python demo.py -h
$ python demo.py
$ python demo.py WFC C BAC- Test using the included unit testing script:
$ cd yahoofinancials
$ python test/test_yahoofinancials.py- The financial data from all methods is returned as JSON.
- You can run multiple symbols at once using an inputted array or run an individual symbol using an inputted string.
- YahooFinancials works with Python 3.7, 3.8, 3.9, 3.10, 3.11 and 3.12 and runs on all operating systems. (Windows, Mac, Linux).
- get_financial_stmts(frequency, statement_type, reformat=True)
- frequency can be either 'annual' or 'quarterly'.
- statement_type can be 'income', 'balance', 'cash' or a list of several.
- reformat optional value defaulted to true. Enter False for unprocessed raw data from Yahoo Finance.
- get_stock_price_data(reformat=True)
- get_stock_earnings_data()
- reformat optional value defaulted to true. Enter False for unprocessed raw data from Yahoo Finance.
- get_summary_data(reformat=True)
- Returns financial summary data for cryptocurrencies, stocks, currencies, ETFs, mutual funds, U.S. Treasuries, commodity futures, and indexes.
- reformat optional value defaulted to true. Enter False for unprocessed raw data from Yahoo Finance.
- get_stock_quote_type_data()
- get_historical_price_data(start_date, end_date, time_interval)
- This method will pull historical pricing data for stocks, currencies, ETFs, mutual funds, U.S. Treasuries, cryptocurrencies, commodities, and indexes.
- start_date should be entered in the 'YYYY-MM-DD' format and is the first day that data will be pulled for.
- end_date should be entered in the 'YYYY-MM-DD' format and is the last day that data will be pulled for.
- time_interval can be either 'daily', 'weekly', or 'monthly'. This variable determines the time period interval for your pull.
- Data response includes relevant pricing event data such as dividends and stock splits.
- get_num_shares_outstanding(price_type='current')
- price_type can also be set to 'average' to calculate the shares outstanding with the daily average price.
- get_daily_dividend_data(start_date, end_date)
- get_stock_profile_data()
- get_financial_data()
- get_interest_expense()
- get_operating_income()
- get_total_operating_expense()
- get_total_revenue()
- get_cost_of_revenue()
- get_income_before_tax()
- get_income_tax_expense()
- get_esg_score_data()
- get_gross_profit()
- get_net_income_from_continuing_ops()
- get_research_and_development()
- get_current_price()
- get_current_change()
- get_current_percent_change()
- get_current_volume()
- get_prev_close_price()
- get_open_price()
- get_ten_day_avg_daily_volume()
- get_stock_exchange()
- get_market_cap()
- get_daily_low()
- get_daily_high()
- get_currency()
- get_yearly_high()
- get_yearly_low()
- get_dividend_yield()
- get_annual_avg_div_yield()
- get_five_yr_avg_div_yield()
- get_dividend_rate()
- get_annual_avg_div_rate()
- get_50day_moving_avg()
- get_200day_moving_avg()
- get_beta()
- get_payout_ratio()
- get_pe_ratio()
- get_price_to_sales()
- get_exdividend_date()
- get_book_value()
- get_ebit()
- get_net_income()
- get_earnings_per_share()
- get_key_statistics_data()
- get_stock_profile_data()
- get_financial_data()
- The class constructor can take either a single ticker or a list of tickers as it's parameter.
- This makes it easy to initiate multiple classes for different groupings of financial assets.
- Quarterly statement data returns the last 4 periods of data, while annual returns the last 3.
from yahoofinancials import YahooFinancials
ticker = 'AAPL'
yahoo_financials = YahooFinancials(ticker)
balance_sheet_data_qt = yahoo_financials.get_financial_stmts('quarterly', 'balance')
income_statement_data_qt = yahoo_financials.get_financial_stmts('quarterly', 'income')
all_statement_data_qt = yahoo_financials.get_financial_stmts('quarterly', ['income', 'cash', 'balance'])
apple_earnings_data = yahoo_financials.get_stock_earnings_data()
apple_net_income = yahoo_financials.get_net_income()
historical_stock_prices = yahoo_financials.get_historical_price_data('2008-09-15', '2018-09-15', 'weekly')from yahoofinancials import YahooFinancials
tech_stocks = ['AAPL', 'MSFT', 'INTC']
bank_stocks = ['WFC', 'BAC', 'C']
commodity_futures = ['GC=F', 'SI=F', 'CL=F']
cryptocurrencies = ['BTC-USD', 'ETH-USD', 'XRP-USD']
currencies = ['EURUSD=X', 'JPY=X', 'GBPUSD=X']
mutual_funds = ['PRLAX', 'QASGX', 'HISFX']
us_treasuries = ['^TNX', '^IRX', '^TYX']
yahoo_financials_tech = YahooFinancials(tech_stocks)
yahoo_financials_banks = YahooFinancials(bank_stocks)
yahoo_financials_commodities = YahooFinancials(commodity_futures)
yahoo_financials_cryptocurrencies = YahooFinancials(cryptocurrencies)
yahoo_financials_currencies = YahooFinancials(currencies)
yahoo_financials_mutualfunds = YahooFinancials(mutual_funds)
yahoo_financials_treasuries = YahooFinancials(us_treasuries)
tech_cash_flow_data_an = yahoo_financials_tech.get_financial_stmts('annual', 'cash')
bank_cash_flow_data_an = yahoo_financials_banks.get_financial_stmts('annual', 'cash')
banks_net_ebit = yahoo_financials_banks.get_ebit()
tech_stock_price_data = yahoo_financials_tech.get_stock_price_data()
daily_bank_stock_prices = yahoo_financials_banks.get_historical_price_data('2008-09-15', '2018-09-15', 'daily')
daily_commodity_prices = yahoo_financials_commodities.get_historical_price_data('2008-09-15', '2018-09-15', 'daily')
daily_crypto_prices = yahoo_financials_cryptocurrencies.get_historical_price_data('2008-09-15', '2018-09-15', 'daily')
daily_currency_prices = yahoo_financials_currencies.get_historical_price_data('2008-09-15', '2018-09-15', 'daily')
daily_mutualfund_prices = yahoo_financials_mutualfunds.get_historical_price_data('2008-09-15', '2018-09-15', 'daily')
daily_treasury_prices = yahoo_financials_treasuries.get_historical_price_data('2008-09-15', '2018-09-15', 'daily')- Annual Income Statement Data for Apple:
yahoo_financials = YahooFinancials('AAPL')
print(yahoo_financials.get_financial_stmts('annual', 'income')){
"incomeStatementHistory": {
"AAPL": [
{
"2016-09-24": {
"minorityInterest": null,
"otherOperatingExpenses": null,
"netIncomeFromContinuingOps": 45687000000,
"totalRevenue": 215639000000,
"totalOtherIncomeExpenseNet": 1348000000,
"discontinuedOperations": null,
"incomeTaxExpense": 15685000000,
"extraordinaryItems": null,
"grossProfit": 84263000000,
"netIncome": 45687000000,
"sellingGeneralAdministrative": 14194000000,
"interestExpense": null,
"costOfRevenue": 131376000000,
"researchDevelopment": 10045000000,
"netIncomeApplicableToCommonShares": 45687000000,
"effectOfAccountingCharges": null,
"incomeBeforeTax": 61372000000,
"otherItems": null,
"operatingIncome": 60024000000,
"ebit": 61372000000,
"nonRecurring": null,
"totalOperatingExpenses": 0
}
}
]
}
}- Annual Balance Sheet Data for Apple:
yahoo_financials = YahooFinancials('AAPL')
print(yahoo_financials.get_financial_stmts('annual', 'balance')){
"balanceSheetHistory": {
"AAPL": [
{
"2016-09-24": {
"otherCurrentLiab": 8080000000,
"otherCurrentAssets": 8283000000,
"goodWill": 5414000000,
"shortTermInvestments": 46671000000,
"longTermInvestments": 170430000000,
"cash": 20484000000,
"netTangibleAssets": 119629000000,
"totalAssets": 321686000000,
"otherLiab": 36074000000,
"totalStockholderEquity": 128249000000,
"inventory": 2132000000,
"retainedEarnings": 96364000000,
"intangibleAssets": 3206000000,
"totalCurrentAssets": 106869000000,
"otherStockholderEquity": 634000000,
"shortLongTermDebt": 11605000000,
"propertyPlantEquipment": 27010000000,
"deferredLongTermLiab": 2930000000,
"netReceivables": 29299000000,
"otherAssets": 8757000000,
"longTermDebt": 75427000000,
"totalLiab": 193437000000,
"commonStock": 31251000000,
"accountsPayable": 59321000000,
"totalCurrentLiabilities": 79006000000
}
}
]
}
}- Quarterly Cash Flow Statement Data for Citigroup:
yahoo_financials = YahooFinancials('C')
print(yahoo_financials.get_financial_stmts('quarterly', 'cash')){
"cashflowStatementHistoryQuarterly": {
"C": [
{
"2017-06-30": {
"totalCashFromOperatingActivities": -18505000000,
"effectOfExchangeRate": -117000000,
"totalCashFromFinancingActivities": 39798000000,
"netIncome": 3872000000,
"dividendsPaid": -760000000,
"salePurchaseOfStock": -1781000000,
"capitalExpenditures": -861000000,
"changeToLiabilities": -7626000000,
"otherCashflowsFromInvestingActivities": 82000000,
"totalCashflowsFromInvestingActivities": -22508000000,
"netBorrowings": 33586000000,
"depreciation": 901000000,
"changeInCash": -1332000000,
"changeToNetincome": 1444000000,
"otherCashflowsFromFinancingActivities": 8753000000,
"changeToOperatingActivities": -17096000000,
"investments": -23224000000
}
}
]
}
}- Monthly Historical Stock Price Data for Wells Fargo:
yahoo_financials = YahooFinancials('WFC')
print(yahoo_financials.get_historical_price_data("2018-07-10", "2018-08-10", "monthly")){
"WFC": {
"currency": "USD",
"eventsData": {
"dividends": {
"2018-08-01": {
"amount": 0.43,
"date": 1533821400,
"formatted_date": "2018-08-09"
}
}
},
"firstTradeDate": {
"date": 76233600,
"formatted_date": "1972-06-01"
},
"instrumentType": "EQUITY",
"prices": [
{
"adjclose": 57.19147872924805,
"close": 57.61000061035156,
"date": 1533096000,
"formatted_date": "2018-08-01",
"high": 59.5,
"low": 57.08000183105469,
"open": 57.959999084472656,
"volume": 138922900
}
],
"timeZone": {
"gmtOffset": -14400
}
}
}- Monthly Historical Price Data for EURUSD:
yahoo_financials = YahooFinancials('EURUSD=X')
print(yahoo_financials.get_historical_price_data("2018-07-10", "2018-08-10", "monthly")){
"EURUSD=X": {
"currency": "USD",
"eventsData": {},
"firstTradeDate": {
"date": 1070236800,
"formatted_date": "2003-12-01"
},
"instrumentType": "CURRENCY",
"prices": [
{
"adjclose": 1.1394712924957275,
"close": 1.1394712924957275,
"date": 1533078000,
"formatted_date": "2018-07-31",
"high": 1.169864296913147,
"low": 1.1365960836410522,
"open": 1.168961763381958,
"volume": 0
}
],
"timeZone": {
"gmtOffset": 3600
}
}
}- Monthly Historical Price Data for BTC-USD:
yahoo_financials = YahooFinancials('BTC-USD')
print(yahoo_financials.get_historical_price_data("2018-07-10", "2018-08-10", "monthly")){
"BTC-USD": {
"currency": "USD",
"eventsData": {},
"firstTradeDate": {
"date": 1279321200,
"formatted_date": "2010-07-16"
},
"instrumentType": "CRYPTOCURRENCY",
"prices": [
{
"adjclose": 6285.02001953125,
"close": 6285.02001953125,
"date": 1533078000,
"formatted_date": "2018-07-31",
"high": 7760.740234375,
"low": 6133.02978515625,
"open": 7736.25,
"volume": 4334347882
}
],
"timeZone": {
"gmtOffset": 3600
}
}
}- Weekly Historical Price Data for Crude Oil Futures:
yahoo_financials = YahooFinancials('CL=F')
print(yahoo_financials.get_historical_price_data("2018-08-01", "2018-08-10", "weekly")){
"CL=F": {
"currency": "USD",
"eventsData": {},
"firstTradeDate": {
"date": 1522555200,
"formatted_date": "2018-04-01"
},
"instrumentType": "FUTURE",
"prices": [
{
"adjclose": 68.58999633789062,
"close": 68.58999633789062,
"date": 1532923200,
"formatted_date": "2018-07-30",
"high": 69.3499984741211,
"low": 66.91999816894531,
"open": 68.37000274658203,
"volume": 683048039
},
{
"adjclose": 67.75,
"close": 67.75,
"date": 1533528000,
"formatted_date": "2018-08-06",
"high": 69.91999816894531,
"low": 66.13999938964844,
"open": 68.76000213623047,
"volume": 1102357981
}
],
"timeZone": {
"gmtOffset": -14400
}
}
}- Apple Stock Quote Data:
yahoo_financials = YahooFinancials('AAPL')
print(yahoo_financials.get_stock_quote_type_data()){
"AAPL": {
"underlyingExchangeSymbol": null,
"exchangeTimezoneName": "America/New_York",
"underlyingSymbol": null,
"headSymbol": null,
"shortName": "Apple Inc.",
"symbol": "AAPL",
"uuid": "8b10e4ae-9eeb-3684-921a-9ab27e4d87aa",
"gmtOffSetMilliseconds": "-14400000",
"exchange": "NMS",
"exchangeTimezoneShortName": "EDT",
"messageBoardId": "finmb_24937",
"longName": "Apple Inc.",
"market": "us_market",
"quoteType": "EQUITY"
}
}- U.S. Treasury Current Pricing Data:
yahoo_financials = YahooFinancials(['^TNX', '^IRX', '^TYX'])
print(yahoo_financials.get_current_price()){
"^IRX": 2.033,
"^TNX": 2.895,
"^TYX": 3.062
}- BTC-USD Summary Data:
yahoo_financials = YahooFinancials('BTC-USD')
print(yahoo_financials.get_summary_data()){
"BTC-USD": {
"algorithm": "SHA256",
"ask": null,
"askSize": null,
"averageDailyVolume10Day": 545573809,
"averageVolume": 496761640,
"averageVolume10days": 545573809,
"beta": null,
"bid": null,
"bidSize": null,
"circulatingSupply": 17209812,
"currency": "USD",
"dayHigh": 6266.5,
"dayLow": 5891.87,
"dividendRate": null,
"dividendYield": null,
"exDividendDate": "-",
"expireDate": "-",
"fiftyDayAverage": 6989.074,
"fiftyTwoWeekHigh": 19870.62,
"fiftyTwoWeekLow": 2979.88,
"fiveYearAvgDividendYield": null,
"forwardPE": null,
"fromCurrency": "BTC",
"lastMarket": "CCCAGG",
"marketCap": 106325663744,
"maxAge": 1,
"maxSupply": 21000000,
"navPrice": null,
"open": 6263.2,
"openInterest": null,
"payoutRatio": null,
"previousClose": 6263.2,
"priceHint": 2,
"priceToSalesTrailing12Months": null,
"regularMarketDayHigh": 6266.5,
"regularMarketDayLow": 5891.87,
"regularMarketOpen": 6263.2,
"regularMarketPreviousClose": 6263.2,
"regularMarketVolume": 755834368,
"startDate": "2009-01-03",
"strikePrice": null,
"totalAssets": null,
"tradeable": false,
"trailingAnnualDividendRate": null,
"trailingAnnualDividendYield": null,
"twoHundredDayAverage": 8165.154,
"volume": 755834368,
"volume24Hr": 750196480,
"volumeAllCurrencies": 2673437184,
"yield": null,
"ytdReturn": null
}
}- Apple Key Statistics Data:
yahoo_financials = YahooFinancials('AAPL')
print(yahoo_financials.get_key_statistics_data()){
"AAPL": {
"annualHoldingsTurnover": null,
"enterpriseToRevenue": 2.973,
"beta3Year": null,
"profitMargins": 0.22413999,
"enterpriseToEbitda": 9.652,
"52WeekChange": -0.12707871,
"morningStarRiskRating": null,
"forwardEps": 13.49,
"revenueQuarterlyGrowth": null,
"sharesOutstanding": 4729800192,
"fundInceptionDate": "-",
"annualReportExpenseRatio": null,
"totalAssets": null,
"bookValue": 22.534,
"sharesShort": 44915125,
"sharesPercentSharesOut": 0.0095,
"fundFamily": null,
"lastFiscalYearEnd": 1538179200,
"heldPercentInstitutions": 0.61208,
"netIncomeToCommon": 59531001856,
"trailingEps": 11.91,
"lastDividendValue": null,
"SandP52WeekChange": -0.06475246,
"priceToBook": 6.7582316,
"heldPercentInsiders": 0.00072999997,
"nextFiscalYearEnd": 1601337600,
"yield": null,
"mostRecentQuarter": 1538179200,
"shortRatio": 1,
"sharesShortPreviousMonthDate": "2018-10-31",
"floatShares": 4489763410,
"beta": 1.127094,
"enterpriseValue": 789555511296,
"priceHint": 2,
"threeYearAverageReturn": null,
"lastSplitDate": "2014-06-09",
"lastSplitFactor": "1/7",
"legalType": null,
"morningStarOverallRating": null,
"earningsQuarterlyGrowth": 0.318,
"priceToSalesTrailing12Months": null,
"dateShortInterest": 1543536000,
"pegRatio": 0.98,
"ytdReturn": null,
"forwardPE": 11.289103,
"maxAge": 1,
"lastCapGain": null,
"shortPercentOfFloat": 0.0088,
"sharesShortPriorMonth": 36469092,
"category": null,
"fiveYearAverageReturn": null
}
}- Apple and Wells Fargo Daily Dividend Data:
start_date = '1987-09-15'
end_date = '1988-09-15'
yahoo_financials = YahooFinancials(['AAPL', 'WFC'])
print(yahoo_financials.get_daily_dividend_data(start_date, end_date)){
"AAPL": [
{
"date": 564157800,
"formatted_date": "1987-11-17",
"amount": 0.08
},
{
"date": 571674600,
"formatted_date": "1988-02-12",
"amount": 0.08
},
{
"date": 579792600,
"formatted_date": "1988-05-16",
"amount": 0.08
},
{
"date": 587655000,
"formatted_date": "1988-08-15",
"amount": 0.08
}
],
"WFC": [
{
"date": 562861800,
"formatted_date": "1987-11-02",
"amount": 0.3008
},
{
"date": 570724200,
"formatted_date": "1988-02-01",
"amount": 0.3008
},
{
"date": 578583000,
"formatted_date": "1988-05-02",
"amount": 0.3344
},
{
"date": 586445400,
"formatted_date": "1988-08-01",
"amount": 0.3344
}
]
}- Apple key Financial Data:
yahoo_financials = YahooFinancials("AAPL")
print(yahoo_financials.get_financial_data()){
'AAPL': {
'ebitdaMargins': 0.29395,
'profitMargins': 0.21238,
'grossMargins': 0.37818,
'operatingCashflow': 69390999552,
'revenueGrowth': 0.018,
'operatingMargins': 0.24572,
'ebitda': 76476997632,
'targetLowPrice': 150,
'recommendationKey': 'buy',
'grossProfits': 98392000000,
'freeCashflow': 42914250752,
'targetMedianPrice': 270,
'currentPrice': 261.78,
'earningsGrowth': 0.039,
'currentRatio': 1.54,
'returnOnAssets': 0.11347,
'numberOfAnalystOpinions': 40,
'targetMeanPrice': 255.51,
'debtToEquity': 119.405,
'returnOnEquity': 0.55917,
'targetHighPrice': 300,
'totalCash': 100556996608,
'totalDebt': 108046999552,
'totalRevenue': 260174004224,
'totalCashPerShare': 22.631,
'financialCurrency': 'USD',
'maxAge': 86400,
'revenuePerShare': 56.341,
'quickRatio': 1.384,
'recommendationMean': 2.2
}
}