Rishi Barve rishibarve
rishibarve
/ Multiprocessing Python With Monitoring
Created
August 30, 2018 06:54
Code for multiprocessing python with feature to save work in middle to skip in case of failure. Helpful for processing large number of small files in a environment where failures are common.
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| import multiprocessing | |
| # split a list into evenly sized chunks | |
| def chunks(l, n): | |
| return [l[i:i+n] for i in range(0, len(l), n)] | |
| def do_job(job_id, data_slice): | |
| processed = [] | |
| for i, item in enumerate(data_slice): |