I no longer mantain this list. There are lots of other very comprehensive JavaScript link lists out there. Please see those, instead (Google "awesome JavaScript" for a start).
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{% extends 'base.html' %} | |
{% import 'macros.html' as macros %} | |
{% block content %} | |
<div class="row"> | |
<div class="col-xs-12 col-md-3 col-sm-4 col-sm-offset-4 col-md-offset-4 col-lg-3 col-lg-offset-4"> | |
<div class="login-message"> | |
Login to AwesomeService! | |
</div> | |
{% call macros.render_form(form, action_url=url_for('login_view'), action_text='Login', | |
class_='login-form') %} |
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(function (ko, handlers, unwrap, extend) { | |
"use strict"; | |
extend(handlers, { | |
href: { | |
update: function (element, valueAccessor) { | |
handlers.attr.update(element, function () { | |
return { href: valueAccessor() }; | |
}); | |
} | |
}, |
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import asyncio | |
import tornado.concurrent | |
import tornado.ioloop | |
import tornado.web | |
import tornado.platform.asyncio | |
import tornado.httpclient | |
class ReqHandler(tornado.web.RequestHandler): | |
async def get(self): |
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#!/bin/bash | |
WATCH_FILE="abc.123" | |
while read oldrev newrev refname; do | |
if [ "$refname" = "refs/heads/master" ]; then | |
if git diff-tree --name-only -r -z $oldrev $newrev | grep --quiet $WATCH_FILE ; then | |
# WATCH_FILE changed... | |
fi | |
fi | |
done |
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// returns first element selected - $('input[name="food"]') | |
var $ = document.querySelector.bind(document); | |
// return array of selected elements - $$('img.dog') | |
var $$ = document.querySelectorAll.bind(document); | |
// Credit: https://twitter.com/wesbos/status/608341616173182977 |
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sudo apt-get install tor | |
# check tor service running on port 9050 (ss -aln | grep 9050) | |
# change ip after every 10 sec | |
edit vi /etc/tor/torrc and add MaxCircuitDirtiness 10 | |
# use tor proxy in python request | |
install requests==2.10.0 (pip install requests==2.10.0) (currently 2.11 giving error) |
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import multiprocessing | |
import pandas as pd | |
import numpy as np | |
def _apply_df(args): | |
df, func, num, kwargs = args | |
return num, df.apply(func, **kwargs) | |
def apply_by_multiprocessing(df,func,**kwargs): | |
workers=kwargs.pop('workers') |
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