<jupyter_start><jupyter_text>Account AllocationBefore we can trade, we must allocate the strategy to one or more accounts. Open [quantrocket.zipline.allocations.yml](quantrocket.zipline.allocations.yml), edit the account number to match your live or paper brokerage account, and edit the capital base as desired.> Note: The capital base is mainly relevant for determining the number of shares to order when using `order_target_percent()`, which is not used in this strategy. However, a value must still must be set.Then install the file by moving it into the `/codeload` directory (i.e. top level of the Jupyter file browser).<jupyter_code># move file over unless it already exists
![ -e /codeload/quantrocket.zipline.allocations.y*ml ] && echo 'oops, the file already exists!' || mv quantrocket.zipline.allocations.yml /codeload/<jupyter_output><empty_output><jupyter_text>SchedulingThe last step is to schedule data to be collected and Zipline to run at the appropriate times. The commands to run are provided in [quantrocket.countdown.crontab.sh](quantrocket.countdown.crontab.sh). We collect updated data for the 1-minute US stock bundle each morning at 7:30 AM, and we start up the Zipline strategy at 9:29 AM. All the commands on the provided crontab are intended to be run in New York time. By default, the countdown timezone is UTC:<jupyter_code>from quantrocket.countdown import get_timezone, set_timezone
get_timezone()<jupyter_output><empty_output><jupyter_text>So first, set the countdown timezone to New York time:<jupyter_code>from quantrocket.countdown import set_timezone
set_timezone("America/New_York")<jupyter_output><empty_output><jupyter_text>Install the crontab by moving it to the /codeload directory. (First open a flightlog terminal so you can see if it loads successfully.)<jupyter_code># move file over unless it already exists
![ -e /codeload/quantrocket.countdown.crontab* ] && echo 'oops, the file already exists!' || mv quantrocket.countdown.crontab.sh /codeload/<jupyter_output><empty_output>
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