Quickstart

Installing the Datamonster library:

pip install datamonster_api

Working with companies:

from datamonster_api import DataMonster
dm = DataMonster(<key_id>, <secret_key>)

# Prints all companies whose name or ticker matches 'hd'
print(list(dm.get_companies(query='hd')))

# Creates a company object for apple
apple = dm.get_company_by_ticker('aapl')

# prints the first 5 quarter end dates
print(apple.quarters[:5])

# prints the first 5 data sources that cover apple
print(list(apple.datasources)[:5])

Working with data sources:

# Prints all data sources whose name or provider matches 'fake'
print(list(dm.get_datasources(query='fake')))

# Prints all data sources whose name or provider matches 'fake'
# AND also cover apple
print(list(dm.get_datasources(query='fake', company=apple)))


# Prints first 5 companies covered by `Fake Data Source`
datasource = list(
        dm.get_datasources(query='Fake Data Source')
        )[0]

print(list(datasource.companies)[:5])

Getting data:

import datetime
from datamonster_api import Aggregation

# Gets a datasource object
apple = dm.get_company_by_ticker('aapl')
datasource = next(apple.datasources)

# Gets all data for the data source filtering on apple
datasource.get_data(apple)

agg = Aggregation(period='fiscalQuarter', company=apple)

# Gets all data for the given data source filtered by apple,
# aggregated by apple's fiscal quarter, and starting on
# January 1, 2017 (inclusive)
datasource.get_data(
    apple,
    agg,
    start_date=datetime.date(2017, 1, 1)
)