Import python venv for stability

2026-02-15 21:24:16 -08:00
parent 1343e93a59
commit 7d784705c9
4997 changed files with 1628270 additions and 0 deletions
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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+#
+# yfinance - market data downloader
+# https://github.com/ranaroussi/yfinance
+#
+# Copyright 2017-2019 Ran Aroussi
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+from __future__ import print_function
+
+from collections import namedtuple as _namedtuple
+
+import pandas as _pd
+
+from .base import TickerBase
+from .const import _BASE_URL_
+from .scrapers.funds import FundsData
+
+
+class Ticker(TickerBase):
+    def __init__(self, ticker, session=None):
+        super(Ticker, self).__init__(ticker, session=session)
+        self._expirations = {}
+        self._underlying  = {}
+
+    def __repr__(self):
+        return f'yfinance.Ticker object <{self.ticker}>'
+
+    def _download_options(self, date=None):
+        if date is None:
+            url = f"{_BASE_URL_}/v7/finance/options/{self.ticker}"
+        else:
+            url = f"{_BASE_URL_}/v7/finance/options/{self.ticker}?date={date}"
+
+        r = self._data.get(url=url).json()
+        if len(r.get('optionChain', {}).get('result', [])) > 0:
+            for exp in r['optionChain']['result'][0]['expirationDates']:
+                self._expirations[_pd.Timestamp(exp, unit='s').strftime('%Y-%m-%d')] = exp
+
+            self._underlying = r['optionChain']['result'][0].get('quote', {})
+
+            opt = r['optionChain']['result'][0].get('options', [])
+
+            return dict(**opt[0],underlying=self._underlying) if len(opt) > 0 else {}
+        return {}
+
+    def _options2df(self, opt, tz=None):
+        data = _pd.DataFrame(opt).reindex(columns=[
+            'contractSymbol',
+            'lastTradeDate',
+            'strike',
+            'lastPrice',
+            'bid',
+            'ask',
+            'change',
+            'percentChange',
+            'volume',
+            'openInterest',
+            'impliedVolatility',
+            'inTheMoney',
+            'contractSize',
+            'currency'])
+
+        data['lastTradeDate'] = _pd.to_datetime(
+            data['lastTradeDate'], unit='s', utc=True)
+        if tz is not None:
+            data['lastTradeDate'] = data['lastTradeDate'].dt.tz_convert(tz)
+        return data
+
+    def option_chain(self, date=None, tz=None):
+        if date is None:
+            options = self._download_options()
+        else:
+            if not self._expirations:
+                self._download_options()
+            if date not in self._expirations:
+                raise ValueError(
+                    f"Expiration `{date}` cannot be found. "
+                    f"Available expirations are: [{', '.join(self._expirations)}]")
+            date = self._expirations[date]
+            options = self._download_options(date)
+
+        if not options:
+            return _namedtuple('Options', ['calls', 'puts', 'underlying'])(**{
+                "calls": None, "puts": None, "underlying": None
+            })
+
+        return _namedtuple('Options', ['calls', 'puts', 'underlying'])(**{
+            "calls": self._options2df(options['calls'], tz=tz),
+            "puts": self._options2df(options['puts'], tz=tz),
+            "underlying": options['underlying']
+        })
+
+    # ------------------------
+
+    @property
+    def isin(self):
+        return self.get_isin()
+
+    @property
+    def major_holders(self) -> _pd.DataFrame:
+        return self.get_major_holders()
+
+    @property
+    def institutional_holders(self) -> _pd.DataFrame:
+        return self.get_institutional_holders()
+
+    @property
+    def mutualfund_holders(self) -> _pd.DataFrame:
+        return self.get_mutualfund_holders()
+
+    @property
+    def insider_purchases(self) -> _pd.DataFrame:
+        return self.get_insider_purchases()
+
+    @property
+    def insider_transactions(self) -> _pd.DataFrame:
+        return self.get_insider_transactions()
+
+    @property
+    def insider_roster_holders(self) -> _pd.DataFrame:
+        return self.get_insider_roster_holders()
+
+    @property
+    def dividends(self) -> _pd.Series:
+        return self.get_dividends()
+
+    @property
+    def capital_gains(self) -> _pd.Series:
+        return self.get_capital_gains()
+
+    @property
+    def splits(self) -> _pd.Series:
+        return self.get_splits()
+
+    @property
+    def actions(self) -> _pd.DataFrame:
+        return self.get_actions()
+
+    @property
+    def shares(self) -> _pd.DataFrame:
+        return self.get_shares()
+
+    @property
+    def info(self) -> dict:
+        return self.get_info()
+
+    @property
+    def fast_info(self):
+        return self.get_fast_info()
+
+    @property
+    def calendar(self) -> dict:
+        """
+        Returns a dictionary of events, earnings, and dividends for the ticker
+        """
+        return self.get_calendar()
+
+    @property
+    def sec_filings(self) -> dict:
+        return self.get_sec_filings()
+
+    @property
+    def recommendations(self):
+        return self.get_recommendations()
+
+    @property
+    def recommendations_summary(self):
+        return self.get_recommendations_summary()
+
+    @property
+    def upgrades_downgrades(self):
+        return self.get_upgrades_downgrades()
+
+    @property
+    def earnings(self) -> _pd.DataFrame:
+        return self.get_earnings()
+
+    @property
+    def quarterly_earnings(self) -> _pd.DataFrame:
+        return self.get_earnings(freq='quarterly')
+
+    @property
+    def income_stmt(self) -> _pd.DataFrame:
+        return self.get_income_stmt(pretty=True)
+
+    @property
+    def quarterly_income_stmt(self) -> _pd.DataFrame:
+        return self.get_income_stmt(pretty=True, freq='quarterly')
+
+    @property
+    def ttm_income_stmt(self) -> _pd.DataFrame:
+        return self.get_income_stmt(pretty=True, freq='trailing')
+
+    @property
+    def incomestmt(self) -> _pd.DataFrame:
+        return self.income_stmt
+
+    @property
+    def quarterly_incomestmt(self) -> _pd.DataFrame:
+        return self.quarterly_income_stmt
+
+    @property
+    def ttm_incomestmt(self) -> _pd.DataFrame:
+        return self.ttm_income_stmt
+
+    @property
+    def financials(self) -> _pd.DataFrame:
+        return self.income_stmt
+
+    @property
+    def quarterly_financials(self) -> _pd.DataFrame:
+        return self.quarterly_income_stmt
+
+    @property
+    def ttm_financials(self) -> _pd.DataFrame:
+        return self.ttm_income_stmt
+
+    @property
+    def balance_sheet(self) -> _pd.DataFrame:
+        return self.get_balance_sheet(pretty=True)
+
+    @property
+    def quarterly_balance_sheet(self) -> _pd.DataFrame:
+        return self.get_balance_sheet(pretty=True, freq='quarterly')
+
+    @property
+    def balancesheet(self) -> _pd.DataFrame:
+        return self.balance_sheet
+
+    @property
+    def quarterly_balancesheet(self) -> _pd.DataFrame:
+        return self.quarterly_balance_sheet
+
+    @property
+    def cash_flow(self) -> _pd.DataFrame:
+        return self.get_cash_flow(pretty=True, freq="yearly")
+
+    @property
+    def quarterly_cash_flow(self) -> _pd.DataFrame:
+        return self.get_cash_flow(pretty=True, freq='quarterly')
+
+    @property
+    def ttm_cash_flow(self) -> _pd.DataFrame:
+        return self.get_cash_flow(pretty=True, freq='trailing')
+
+    @property
+    def cashflow(self) -> _pd.DataFrame:
+        return self.cash_flow
+
+    @property
+    def quarterly_cashflow(self) -> _pd.DataFrame:
+        return self.quarterly_cash_flow
+
+    @property
+    def ttm_cashflow(self) -> _pd.DataFrame:
+        return self.ttm_cash_flow
+
+    @property
+    def analyst_price_targets(self) -> dict:
+        return self.get_analyst_price_targets()
+
+    @property
+    def earnings_estimate(self) -> _pd.DataFrame:
+        return self.get_earnings_estimate()
+
+    @property
+    def revenue_estimate(self) -> _pd.DataFrame:
+        return self.get_revenue_estimate()
+
+    @property
+    def earnings_history(self) -> _pd.DataFrame:
+        return self.get_earnings_history()
+
+    @property
+    def eps_trend(self) -> _pd.DataFrame:
+        return self.get_eps_trend()
+
+    @property
+    def eps_revisions(self) -> _pd.DataFrame:
+        return self.get_eps_revisions()
+
+    @property
+    def growth_estimates(self) -> _pd.DataFrame:
+        return self.get_growth_estimates()
+
+    @property
+    def sustainability(self) -> _pd.DataFrame:
+        return self.get_sustainability()
+
+    @property
+    def options(self) -> tuple:
+        if not self._expirations:
+            self._download_options()
+        return tuple(self._expirations.keys())
+
+    @property
+    def news(self) -> list:
+        return self.get_news()
+
+    @property
+    def earnings_dates(self) -> _pd.DataFrame:
+        return self.get_earnings_dates()
+
+    @property
+    def history_metadata(self) -> dict:
+        return self.get_history_metadata()
+
+    @property
+    def funds_data(self) -> FundsData:
+        return self.get_funds_data()