60 lines
1.7 KiB
Python
60 lines
1.7 KiB
Python
#!/usr/bin/env python3
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from itertools import islice
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from my.core.cachew import disable_cachew
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disable_cachew()
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import my.location.takeout as LT
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from my.kython.kompress import kopen
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def ilen(it):
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# TODO more_itertools?
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return len(list(it))
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def test_location_perf():
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# 2.80 s for 10 iterations and 10K points
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# TODO try switching to jq and see how it goes? not sure..
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print(ilen(islice(LT.iter_locations(), 0, 10000)))
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def test_parser():
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from my.kython.ktakeout import TakeoutHTMLParser
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from my.takeout import get_last_takeout
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# 4s for parsing with HTMLParser (30K results)
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path = 'Takeout/My Activity/Chrome/MyActivity.html'
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tpath = get_last_takeout(path=path)
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results = []
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def cb(dt, url, title):
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results.append((dt, url, title))
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parser = TakeoutHTMLParser(cb)
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with kopen(tpath, path) as fo:
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dd = fo.read().decode('utf8')
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parser.feed(dd)
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print(len(results))
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def parse_takeout_xmllint(data: str):
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# without xmllint (splitting by '<div class="content-cell' -- 0.68 secs)
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# with xmllint -- 2 seconds
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# using html.parser -- 4 seconds (+ all the parsing etc)
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# not *that* much opportunity to speedup I guess
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# the only downside is that html.parser isn't iterative.. might be able to hack with some iternal hacks?
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# wonder what's the bottleneck..
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#
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from subprocess import Popen, PIPE, run
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from more_itertools import split_before
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res = run(
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['xmllint', '--html', '--xpath', '//div[contains(@class, "content-cell")]', '-'],
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input=data.encode('utf8'),
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check=True,
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stdout=PIPE,
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)
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out = res.stdout.decode('utf8')
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# out = data
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return out.split('<div class="content-cell')
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