ecal 1.0.2

Getting the earnings announcements for a single date

To get the earnings announcements for a single date simply import ecal and call get():

import ecal

cal_df = ecal.get('2017-03-30')

The results will be an earnings calendar in a pandas DataFrame:

           ticker when
date
2017-03-30   AEHR  amc
2017-03-30   ANGO  bmo
2017-03-30   BSET   --
2017-03-30     FC  amc
2017-03-30    LNN  bmo
2017-03-30   SAIC  bmo
2017-03-30   TITN  bmo

The returned DataFrame has the following columns:

ticker

is the ticker symbol on NYSE or NASDAQ.

when

can be bmo which means before market open, amc which means after market close or -- which means no time reported.

If there were no announcements for this day, an empty DataFrame will be returned.

Getting the earnings announcements for a date range

It is equally easy to get the earnings announcements for a date range:

import ecal

cal_df = ecal.get('2018-01-01', '2018-01-05')

Once again the results will be an earnings calendar in a pandas DataFrame:

           ticker when
date
2018-01-04    CMC  bmo
2018-01-04   LNDC  amc
2018-01-04   NEOG  bmo
2018-01-04    RAD  amc
2018-01-04   RECN  amc
2018-01-04    UNF  bmo
2018-01-05   AEHR  amc
2018-01-05   ANGO  bmo
2018-01-05     FC  amc
2018-01-05     LW  bmo
2018-01-05    PKE  bmo
2018-01-05   PSMT  amc
2018-01-05    RPM  bmo
2018-01-05   SONC  amc
2018-01-05    WBA  bmo

Days with no earnings announcements will have no rows in the DataFrame. In the example above, there were no announcements on Jan first, second and third.

It should be noted that ecal fetches earnings announcements from api.earningscalendar.net by default. This source limits us to 1 call per second. However you don’t have to worry about this because the ecal.ECNFetcher throttles calls to the API to prevent rate limiting. That said, please note that this fetcher gets announcements one day at a time which means if you want 30 days, it’s going to take 30 seconds to get that data. Yikes. Fear not… that’s why ecal comes with caching.

Caching

ecal supports caching so that repeated calls to ecal.get() don’t actually make calls to the server. Runtime caching is enabled by default which means calls during your program’s execution will be cached. However, the ecal.RuntimeCache is only temporary and the next time your program runs it will call the API again.

Persistent on disk caching is provided via ecal.SqliteCache and can be easily enabled by setting ecal.default_cache once before calls to ecal.get():

import ecal
ecal.default_cache = ecal.SqliteCache('ecal.db')

cal_df = ecal.get('2017-03-30')

Extension

ecal is very easy to extend in case you want to support another caching system or even create an earnings announcement fetcher. For more documentation, please see http://ecal.readthedocs.io.