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Limitations of Fetcher

Hi all,

I'm currently working on a strategy which I've proto-typed offline and would like to convert it to run on quantopian.

A portion of it runs comparisons against a csv that is about 500MB in size (and has the potential to get much larger). I was wondering if anyone has dealt with using fetcher on files this large and what the bounds would be as to how large a cvs I could import.

4 responses

Ethan,

I've personally worked with CSVs around 80-90mb and risked running into a timeout error. I would say 100mb is getting close to the limit.

But definitely suggest giving it a shot

Seong

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Hi Ethan,

Note that files can also be uploaded to the Q research platform, but to my knowledge, the file size limit is unspecified. Once I tried a huge file (many GB) and got an error. But it may not have been fundamental to the research platform (it seemed like the browser was choking). One way to handle it is to compress the file and then unzip and then re-zip, as chunks of data are needed. Q does support zlib. Hmm? I wonder if it could be leveraged? In MATLAB, there is a way to read from compact binary files, with a file pointer. There's probably something similar in Python.

Grant

You might consider loading it into data.table in R and calling R from python.

Where do I access the platform? I have yet to try it out