mirror of
https://github.com/wassname/pandas-ta.git
synced 2026-08-14 12:40:48 +08:00
STY double quote consistency
This commit is contained in:
Kevin Johnson
@@ -113,7 +113,7 @@ $ pip install pandas_ta
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Latest Version
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--------------
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Best choice! Version: *0.3.36b*
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Best choice! Version: *0.3.37b*
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* Includes all fixes and updates between **pypi** and what is covered in this README.
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```sh
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$ pip install -U git+https://github.com/twopirllc/pandas-ta
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@@ -57,28 +57,28 @@ def polygon_api(ticker: str, **kwargs):
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verbose = kwargs.pop("verbose", False)
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kind = kwargs.pop("kind", "nothing").lower()
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show = kwargs.pop("show", None)
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desc = kwargs.pop('desc', False)
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desc = kwargs.pop("desc", False)
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df = DataFrame()
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api_key = kwargs.pop('api_key', None)
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api_key = kwargs.pop("api_key", None)
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if api_key is None:
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raise ValueError('Please make sure you pass your polygon api key through kwarg api_key')
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if not Imports['polygon']:
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raise ValueError('Please install package polygon to use this function (pip install polygon)')
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raise ValueError("Please make sure you pass your polygon api key through kwarg api_key")
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if not Imports["polygon"]:
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raise ValueError("Please install package polygon to use this function (pip install polygon)")
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if ticker is not None and isinstance(ticker, str):
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ticker = ticker.upper()
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else:
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raise ValueError('Ticker symbol name must be a valid name string. Eg: \'AMD\'')
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raise ValueError("Ticker symbol name must be a valid name string. Eg: \'AMD\'")
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start_date = kwargs.pop('start_date', (datetime.date.today() - datetime.timedelta(days=525)))
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end_date = kwargs.pop('end_date', datetime.date.today())
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limit = kwargs.pop('limit', 50000)
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multiplier = kwargs.pop('multiplier', 1)
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timespan = kwargs.pop('timespan', 'day')
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start_date = kwargs.pop("start_date", (datetime.date.today() - datetime.timedelta(days=525)))
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end_date = kwargs.pop("end_date", datetime.date.today())
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limit = kwargs.pop("limit", 50000)
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multiplier = kwargs.pop("multiplier", 1)
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timespan = kwargs.pop("timespan", "day")
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LOGGER.info(f'start date: {start_date} || end date: {end_date} || limit: {limit} || '
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f'multiplier: {multiplier} || timespan: {timespan}')
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LOGGER.info(f"start date: {start_date} || end date: {end_date} || limit: {limit} || "
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f"multiplier: {multiplier} || timespan: {timespan}")
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_all, div = ["all"], "=" * 53 # Max div width is 80
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@@ -91,13 +91,13 @@ def polygon_api(ticker: str, **kwargs):
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resp = polygon_client.get_aggregate_bars(ticker, start_date, end_date, limit=limit,
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multiplier=multiplier, timespan=timespan)
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if 'results' in resp.keys():
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df = pd.DataFrame.from_dict(resp['results'])
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if "results" in resp.keys():
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df = pd.DataFrame.from_dict(resp["results"])
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if len(df) > 0:
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index = 't'
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index = "t"
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df = df.set_index(pd.DatetimeIndex(unix_convert(df[index])))
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df = df[['v', 'o', 'c', 'h', 'l', 't']]
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df.columns = ['Volume', 'Open', 'Close', 'High', 'Low', 'Date']
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df = df[["v", "o", "c", "h", "l", "t"]]
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df.columns = ["Volume", "Open", "Close", "High", "Low", "Date"]
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df.name = ticker
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else:
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@@ -106,74 +106,74 @@ def polygon_api(ticker: str, **kwargs):
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if show is not None and isinstance(show, int) and show > 0:
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print(f"\n{df.name}\n{df.tail(show)}\n")
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if kind in ['nothing', None]: # no additional data requested
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if kind in ["nothing", None]: # no additional data requested
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return df
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# ADDITIONAL DATA FLOW
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ref_client, stock_client = polygon.ReferenceClient(api_key), polygon.StocksClient(api_key)
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# ALL THE INFORMATION
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if kind in ['all', 'info'] or verbose:
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if kind in ["all", "info"] or verbose:
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print("\n==== Company Information " + div)
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details = ref_client.get_ticker_details(ticker)
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details_vx = ref_client.get_ticker_details_vx(ticker)['results']
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details_vx = ref_client.get_ticker_details_vx(ticker)["results"]
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print(f'{details["name"]} [{details["symbol"]}]\n')
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print(f"{details['name']} [{details['symbol']}]\n")
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if desc: # company description
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print(f'{details["description"]}\n')
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print(f"{details['description']}\n")
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# TODO: polygon returns hell lotta data for market info across a few endpoints. I don't know which ones to
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# include here lol. I wrote the ones i felt were important. Feel free to suggest more.
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# Common details + Market info
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print(f'{details["hq_address"]}. {details["hq_country"]}\nPhone: {details_vx["phone_number"]}\n'
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f'Website: {details["url"]} || Employees: {details["employees"]}\nSector: {details["sector"]} || '
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f'Industry: {details["industry"]}\n\n==== Market Information {div}\n'
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f'Market: {details_vx["market"].upper()} || locale: {details_vx["locale"].upper()} || '
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f'Exchange: {details["exchange"]} || Symbol: {details["symbol"]}\nMarket Shares: '
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f'{details_vx["market_cap"]} || Outstanding Shares: {details_vx["outstanding_shares"]}\n')
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print(f"{details['hq_address']}. {details['hq_country']}\nPhone: {details_vx['phone_number']}\n"
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f"Website: {details['url']} || Employees: {details['employees']}\nSector: {details['sector']} || "
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f"Industry: {details['industry']}\n\n==== Market Information {div}\n"
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f"Market: {details_vx['market'].upper()} || locale: {details_vx['locale'].upper()} || "
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f"Exchange: {details['exchange']} || Symbol: {details['symbol']}\nMarket Shares: "
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f"{details_vx['market_cap']} || Outstanding Shares: {details_vx['outstanding_shares']}\n")
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# Price Info
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print(f"\n==== Price Information {div}")
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snap_res = stock_client.get_snapshot(ticker)
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try:
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snap = snap_res['ticker']
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snap = snap_res["ticker"]
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print(f'\nCurrent Price: {snap["lastTrade"]["p"]} || Today\'s Change: ${snap_res["todaysChange"]} - '
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f'{snap_res["todaysChangePerc"]}%\nBid: {snap["lastQuote"]["p"]} x {snap["lastQuote"]["s"]} || Ask: '
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f'{snap["lastQuote"]["P"]} x {snap["lastQuote"]["S"]} || Spread: '
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f'{round(snap["lastQuote"]["P"] - snap["lastQuote"]["p"], 4)}\nOpen: {snap["day"]["o"]} || High: '
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f'{snap["day"]["h"]} || Low: {snap["day"]["l"]} || Close: {snap["day"]["c"]} || Volume: '
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f'{snap["day"]["v"]} || VWA: {snap["day"]["vw"]}')
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print(f"\nCurrent Price: {snap['lastTrade']['p']} || Today\'s Change: ${snap_res['todaysChange']} - "
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f"{snap_res['todaysChangePerc']}%\nBid: {snap['lastQuote']['p']} x {snap['lastQuote']['s']} || Ask: "
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f"{snap['lastQuote']['P']} x {snap['lastQuote']['S']} || Spread: "
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f"{round(snap['lastQuote']['P'] - snap['lastQuote']['p'], 4)}\nOpen: {snap['day']['o']} || High: "
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f"{snap['day']['h']} || Low: {snap['day']['l']} || Close: {snap['day']['c']} || Volume: "
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f"{snap['day']['v']} || VWA: {snap['day']['vw']}")
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except KeyError:
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print(f'Snapshot not found for {ticker}. Can Not print price information. Snapshot will be be back '
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f'available after pre market session opens\n')
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print(f"Snapshot not found for {ticker}. Can Not print price information. Snapshot will be be back "
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f"available after pre market session opens\n")
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# Splits and Dividends
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divs, splits = ref_client.get_stock_dividends(ticker), ref_client.get_stock_splits(ticker)
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# TODO: spits and dividends endpoints from polygon return a huge list. not sure if that entire list is useful
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print(f'\nNumber of dividends: {divs["count"]} || Number of splits: {splits["count"]}\n')
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print(f"\nNumber of dividends: {divs['count']} || Number of splits: {splits['count']}\n")
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# TODO: financials endpoint on polygon returns a huge response. I doubt if that's useful to be displayed.
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# Option Chains
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if kind in ['option_chains', 'oc']:
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contract_type = kwargs.pop('contract_type', 'all')
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contract_limit = kwargs.pop('contract_limit', 10)
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if kind in ["option_chains", "oc"]:
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contract_type = kwargs.pop("contract_type", "all")
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contract_limit = kwargs.pop("contract_limit", 10)
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chains = ref_client.get_option_contracts(ticker, limit=contract_limit,
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contract_type=None if contract_type == 'all' else contract_type)
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contract_type=None if contract_type == "all" else contract_type)
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if len(chains['results']) > 0:
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print(f'\n==== Option chains {div}\n\n')
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for contract in chains['results']:
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print(f'Symbol: {contract["ticker"]} || Type: {contract["contract_type"]}'
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f' || Expiry: {contract["expiration_date"]} || Strike Price: ${contract["strike_price"]}'
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f' || Shares Per Contract: {contract["shares_per_contract"]}\n')
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if len(chains["results"]) > 0:
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print(f"\n==== Option chains {div}\n\n")
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for contract in chains["results"]:
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print(f"Symbol: {contract['ticker']} || Type: {contract['contract_type']}"
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f" || Expiry: {contract['expiration_date']} || Strike Price: ${contract['strike_price']}"
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f" || Shares Per Contract: {contract['shares_per_contract']}\n")
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else:
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print(f'\nNo option chains data found for {ticker}.')
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print(f"\nNo option chains data found for {ticker}.")
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return df
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@@ -185,4 +185,4 @@ def unix_convert(ts: Union[int, pd.Series]) -> Union[datetime.datetime, str]:
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:param ts: The timestamp(s). An integer posix timestamp or a pd.Series of timestamps
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:return: The converted datetime string
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"""
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return pd.to_datetime(ts, unit='ms')
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return pd.to_datetime(ts, unit="ms")
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