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moex.py
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moex.py
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import datetime as dt
import pandas as pd
from pandas_datareader.base import _DailyBaseReader
from pandas_datareader.compat import StringIO, binary_type, concat, is_list_like
class MoexReader(_DailyBaseReader):
"""
Returns a DataFrame of historical stock prices from symbols from Moex
Parameters
----------
symbols : str, an array-like object (list, tuple, Series), or a DataFrame
A single stock symbol (secid), an array-like object of symbols or
a DataFrame with an index containing stock symbols.
start : string, int, date, datetime, Timestamp
Starting date. Parses many different kind of date
representations (e.g., 'JAN-01-2010', '1/1/10', 'Jan, 1, 1980'). Defaults to
20 years before current date.
end : string, int, date, datetime, Timestamp
Ending date
retry_count : int, default 3
The number of times to retry query request.
pause : int, default 0.1
Time, in seconds, to pause between consecutive queries of chunks. If
single value given for symbol, represents the pause between retries.
chunksize : int, default 25
The number of symbols to download consecutively before intiating pause.
session : Session, default None
requests.sessions.Session instance to be used
Notes
-----
To avoid being penalized by Moex servers, pauses more than 0.1s between
downloading 'chunks' of symbols can be specified.
"""
def __init__(self, *args, **kwargs):
super(MoexReader, self).__init__(*args, **kwargs)
self.start = self.start.date()
self.end_dt = self.end
self.end = self.end.date()
if isinstance(self.symbols, pd.DataFrame):
self.symbols = self.symbols.index.tolist()
elif not is_list_like(self.symbols):
self.symbols = [self.symbols]
self.__engines, self.__markets = {}, {} # dicts for engines and markets
__url_metadata = "https://iss.moex.com/iss/securities/{symbol}.csv"
__url_data = (
"https://iss.moex.com/iss/history/engines/{engine}/"
"markets/{market}/securities/{symbol}.csv"
)
@property
def url(self):
"""Return a list of API URLs per symbol"""
if not self.__engines or not self.__markets:
raise Exception(
"Accessing url property before invocation "
"of read() or _get_metadata() methods"
)
return [
self.__url_data.format(
engine=self.__engines[s], market=self.__markets[s], symbol=s
)
for s in self.symbols
]
def _get_params(self, start):
"""Return a dict for REST API GET request parameters"""
params = {
"iss.only": "history",
"iss.dp": "point",
"iss.df": "%Y-%m-%d",
"iss.tf": "%H:%M:%S",
"iss.dft": "%Y-%m-%d %H:%M:%S",
"iss.json": "extended",
"callback": "JSON_CALLBACK",
"from": start,
"till": self.end_dt.strftime("%Y-%m-%d"),
"limit": 100,
"start": 1,
"sort_order": "TRADEDATE",
"sort_order_desc": "asc",
}
return params
def _get_metadata(self):
"""Get markets and engines for the given symbols"""
markets, engines = {}, {}
for symbol in self.symbols:
response = self._get_response(self.__url_metadata.format(symbol=symbol))
text = self._sanitize_response(response)
if len(text) == 0:
service = self.__class__.__name__
raise IOError(
"{} request returned no data; check URL for invalid "
"inputs: {}".format(service, self.__url_metadata)
)
if isinstance(text, binary_type):
text = text.decode("windows-1251")
header_str = "secid;boardid;"
get_data = False
for s in text.splitlines():
if s.startswith(header_str):
get_data = True
continue
if get_data and s != "":
fields = s.split(";")
markets[symbol], engines[symbol] = fields[5], fields[7]
break
if symbol not in markets or symbol not in engines:
raise IOError(
"{} request returned no metadata: {}\n"
"Typo in the security symbol `{}`?".format(
self.__class__.__name__,
self.__url_metadata.format(symbol=symbol),
symbol,
)
)
return markets, engines
def read(self):
"""Read data"""
try:
self.__markets, self.__engines = self._get_metadata()
urls = self.url # generate urls per symbols
dfs = [] # an array of pandas dataframes per symbol to concatenate
for i in range(len(self.symbols)):
out_list = []
date_column = None
while True: # read in a loop with small date intervals
if len(out_list) > 0:
if date_column is None:
date_column = out_list[0].split(";").index("TRADEDATE")
# get the last downloaded date
start_str = out_list[-1].split(";", 4)[date_column]
start = dt.datetime.strptime(start_str, "%Y-%m-%d").date()
else:
start_str = self.start.strftime("%Y-%m-%d")
start = self.start
if start >= self.end or start >= dt.date.today():
break
params = self._get_params(start_str)
strings_out = self._read_url_as_String(
urls[i], params
).splitlines()[2:]
strings_out = list(filter(lambda x: x.strip(), strings_out))
if len(out_list) == 0:
out_list = strings_out
if len(strings_out) < 101: # all data received - break
break
else:
out_list += strings_out[1:] # remove a CSV head line
if len(strings_out) < 100: # all data recevied - break
break
str_io = StringIO("\r\n".join(out_list))
dfs.append(self._read_lines(str_io)) # add a new DataFrame
finally:
self.close()
if len(dfs) > 1:
return concat(dfs, axis=0, join="outer", sort=True)
else:
return dfs[0]
def _read_url_as_String(self, url, params=None):
"""Open an url (and retry)"""
response = self._get_response(url, params=params)
text = self._sanitize_response(response)
if len(text) == 0:
service = self.__class__.__name__
raise IOError(
"{} request returned no data; check URL for invalid "
"inputs: {}".format(service, self.url)
)
if isinstance(text, binary_type):
text = text.decode("windows-1251")
return text
def _read_lines(self, input):
"""Return a pandas DataFrame from input"""
return pd.read_csv(
input,
index_col="TRADEDATE",
parse_dates=True,
sep=";",
na_values=("-", "null"),
)