Python client library to download data from finam.ru
- Contracts lookup by market categories, id, code, name or their combinations using a rich set of mathching options
- Downloads data of any timeframe available on finam.ru ranging from ticks to monthly resolution
- Allows to download data for arbitrarily long intervals
pip install finam-export
- Google Chrome must be installed
samples/listing.py- simply lists some contracts from every supported marketsamples/download.py- downloads some data and prints it outsamples/lookups.py- shows how you can leverage lookup capabilities
scripts/finam-download.py- feature-rich standalone script to download finam's datascripts/finam-lookup.py- to quickly check what's availble on finam
Here's the output
*** Current Russian ruble exchange rates ***
INFO:finam.export:Fetching https://www.finam.ru/profile/moex-akcii/gazprom/export/
INFO:finam.export:Meta data fetching started
INFO:finam.export:Fetching https://www.finam.ru/cache/N72Hgd54/icharts/icharts.js
INFO:finam.export:Meta data fetching finished
INFO:finam.export:Processing chunk 1 of 2
INFO:finam.export:Fetching http://export.finam.ru/table.csv?d=d&f=table&e=.csv&dtf=1&tmf=3&MSOR=0&mstime=on&mstimever=1&sep=3&sep2=1&at=1&p=8&em=182456&market=45&df=1&mf=0&yf=2007&dt=28&mt=11&yt=2016&cn=USD000000TOD&code=USD000000TOD&datf=5&fsp=0
INFO:finam.export:Processing chunk 2 of 2
INFO:finam.export:Sleeping for 1 second(s)
INFO:finam.export:Fetching http://export.finam.ru/table.csv?d=d&f=table&e=.csv&dtf=1&tmf=3&MSOR=0&mstime=on&mstimever=1&sep=3&sep2=1&at=1&p=8&em=182456&market=45&df=29&mf=11&yf=2016&dt=26&mt=2&yt=2023&cn=USD000000TOD&code=USD000000TOD&datf=5&fsp=0
<DATE> <TIME> <OPEN> <HIGH> <LOW> <CLOSE> <VOL>
1473 20230324 00:00:00 76.175 76.8 76.0025 76.695 460424000
*** Current Brent Oil price ***
INFO:finam.export:Processing chunk 1 of 2
INFO:finam.export:Fetching http://export.finam.ru/table.csv?d=d&f=table&e=.csv&dtf=1&tmf=3&MSOR=0&mstime=on&mstimever=1&sep=3&sep2=1&at=1&p=8&em=19473&market=24&df=1&mf=0&yf=2007&dt=28&mt=11&yt=2016&cn=BZ&code=BZ&datf=5&fsp=0
INFO:finam.export:Processing chunk 2 of 2
INFO:finam.export:Sleeping for 1 second(s)
INFO:finam.export:Fetching http://export.finam.ru/table.csv?d=d&f=table&e=.csv&dtf=1&tmf=3&MSOR=0&mstime=on&mstimever=1&sep=3&sep2=1&at=1&p=8&em=19473&market=24&df=29&mf=11&yf=2016&dt=26&mt=2&yt=2023&cn=BZ&code=BZ&datf=5&fsp=0
<DATE> <TIME> <OPEN> <HIGH> <LOW> <CLOSE> <VOL>
1934 20230324 00:00:00 75.53 76.32 72.68 75.0 92082
and here's the code producing this output:
import logging
from finam import Exporter, Market, LookupComparator
"""
Full-on example displaying up-to-date values of some important indicators
"""
def main():
exporter = Exporter()
print('*** Current Russian ruble exchange rates ***')
rub = exporter.lookup(name='USDRUB_TOD', market=Market.CURRENCIES)
assert len(rub) == 1
data = exporter.download(rub.index[0], market=Market.CURRENCIES)
print(data.tail(1))
print('*** Current Brent Oil price ***')
oil = exporter.lookup(name='Brent', market=Market.COMMODITIES,
name_comparator=LookupComparator.EQUALS)
assert len(oil) == 1
data = exporter.download(oil.index[0], market=Market.COMMODITIES)
print(data.tail(1))
if __name__ == '__main__':
logging.basicConfig(level=logging.INFO)
main()
If you have cloned it from github:
pip install -r ./requirements.txt
PYTHONPATH=. ./samples/listing.py- Targeted to Linux/Mac
- Uses pandas inside, all data returned is pandas DataFrames
- Tested with python 3.7, python 3.8, python 3.9, python 3.10, python 3.11
- Good tests coverage
- Detailed logging of what's going on
- clone the repo
pip install -r ./requirements.txt- run tests to ensure all is fine
nosetests- go ahead and enhance it!
- don't forget to cover your changes with tests
- Check Dockerfile in the root folder if you are looking for docker-based example