<div dir="ltr">I forced it with a <div><br></div><div style>print (json.dumps (data_set))</div><div style><br></div><div style>Roughly...</div><div style><br></div><div style>Python takes 3.8 secs to parse and dump to /dev/null</div> <div style>Python takes 2.5 secs to parse.</div><div style><br></div><div style>On Racket, via module with -tm around a (main), I see ~40 secs.</div><div style>I have a TR version of the Json parser from porting an ol' Planet lib. There I get ~28 secs, with ~4 secs of TR "startup" to type check.</div> <div style><br></div><div style>I'm wondering if it is an ASCII vs UNICODE issue. Looks like Python JSON parser defaults to ASCII.</div></div><div class="gmail_extra"><br><br><div class="gmail_quote">On Mon, Jan 14, 2013 at 11:53 AM, Carl Eastlund <span dir="ltr"><<a href="mailto:cce@ccs.neu.edu" target="_blank">cce@ccs.neu.edu</a>></span> wrote:<br> <blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">Forgive my Python-naïveté, but is Python perhaps constructing a lazy input stream and managing to return quickly by simply not parsing anything yet? Or are you able to actually run some function on the whole file, get a result, and still return nearly immediately while Racket takes something like a minute?<span class="HOEnZb"><font color="#888888"><br> </font></span></div><div class="gmail_extra"><span class="HOEnZb"><font color="#888888"><br clear="all"><div>Carl Eastlund</div></font></span><div><div class="h5"> <br><br><div class="gmail_quote">On Mon, Jan 14, 2013 at 11:12 AM, J G Cho <span dir="ltr"><<a href="mailto:gcho@fundingmatters.com" target="_blank">gcho@fundingmatters.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"> Dear performance experts,<br> <br> With the news of math library in Racket and the goal of improving my<br> data analysis skill, I have started going over the examples in book<br> "Python for Data Anyalysis" by McKinney using both Python and Racket.<br> Too early to tell which is preferable for me. But I do have one<br> "problem" with Racket that I would like to resolve before going on<br> further.<br> <br> Here is the detail.<br> <br> Python:<br> <br> First I load the data<br> <br> # It looks like this at the top level;<br> # structured differently from the example in the book.<br> data_set = {<br> "meta": {},<br> "data": []<br> }<br> <br> import json<br> <br> # read in the json data downloaded from<br> # <a href="https://explore.data.gov/Information-and-Communications/1-USA-gov-Short-Links/wzeq-n5pg" target="_blank">https://explore.data.gov/Information-and-Communications/1-USA-gov-Short-Links/wzeq-n5pg</a><br> with open("usagov_bitly_data.json") as f:<br> data_set = json.load( f )<br> <br> <br> And then I go do the usual slice and dice....<br> <br> My work flow is to edit the file and either run it inside Sublime Text<br> 2 or ipython --pylab. (v 2.7 via EPD package running on Win 7 on<br> fairly new and powerful Dell.) There is a brief pause before I see the<br> output in the screen.<br> <br> <br> <br> I run the following in DrRacket (v5.3):<br> <br> #lang racket<br> <br> (require json)<br> <br> (define data-set<br> (call-with-input-file "usagov_bitly_data.json"<br> (lambda (in)<br> (read-json in))))<br> <br> <br> It takes sometime (more than a few sips of tea) where edit-run cycle<br> is not workable.<br> <br> I initially thought maybe the json library was the cause and tried<br> writing the parsed data out as .sexp and then reading that in. It did<br> not resolve the speed issue for me. I now work with a smaller subset<br> of data when I work with Racket.<br> <br> Any suggestions?<br> <br> jGc<br> ____________________<br> Racket Users list:<br> <a href="http://lists.racket-lang.org/users" target="_blank">http://lists.racket-lang.org/users</a><br> <br> </blockquote></div><br></div></div></div> <br>____________________<br> Racket Users list:<br> <a href="http://lists.racket-lang.org/users" target="_blank">http://lists.racket-lang.org/users</a><br> <br></blockquote></div><br></div>