Hey everyone. If I try to call history with a variable passed to the argument label I get an error telling me bar_count only takes ints. I'm even casting the integers I'm passing to history as ints and it still throws the same error. Any ideas? Have you guys seen that before?
big_wnd = int(1080)
close = history(bar_count = big_wnd, frequency='1m', field='price')[context.stock]
Error : history() parameter "bar_count" must be an int.
Hi Jason,
In its current implementation, the history function requires that its arguments be passed as literals. In this sense, it works a bit more like a C-macro than a proper Python function, which is something we could probably do a better job of conveying in our docs.
If you amend your example to
close = history(bar_count=1080, frequency='1m', field='price')[context.stock]
you should see this error go away.
The reason for the odd limitation of requiring literals is that we need to know at the start of your algorithm what history containers we should maintain behind the scenes.
Hope that helps,
-Scott
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The history dataframe is maintained behind the scenes because dynamically creating new ones on each bar would make backtesting brutally slow. The standard suggestion is to use the largest window you will need, and then downsample that dataframe in your algo.
def initialize(context):
context.window = 100
def handle_data(context, data):
prices = history(bar_count=1000, frequency='1d', field='price').iloc[-context.window:]
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by Quantopian.
In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.
