Skip to content

Instantly share code, notes, and snippets.

import progressbar
i = 0
with progressbar.ProgressBar(max_value=len(entities)) as bar:
for entity in entities:
compute_metrics(entity)
i += 1
bar.update(i)

Keybase proof

I hereby claim:

  • I am mazieres on github.
  • I am mazieres (https://keybase.io/mazieres) on keybase.
  • I have a public key ASDzCRM2QkTnZ8Im0Yw210zPZZ54GykPj9xwJ6gw6bki0Qo

To claim this, I am signing this object:

import json
from json.decoder import WHITESPACE
def iterload(string, cls=json.JSONDecoder, **kwargs):
decoder = cls(**kwargs)
idx = WHITESPACE.match(string, 0).end()
while idx < len(string):
try:
obj, end = decoder.raw_decode(string, idx)
idx = WHITESPACE.match(string, end).end()
@mazieres
mazieres / zb-data_collect.js
Created October 29, 2016 12:55
Zeitgeist Borders - Data Collection
function mkAllQueries(query) {
var allRes = {}
var promises = []
for (var i = 0; i < nb_hls; i++){
promises.push($.getJSON(apiUrl, {
"client": "firefox",
"hl": hls[i],
"q": query
})
.done(function (hl, q) {
@mazieres
mazieres / ip2location.go
Created September 29, 2016 07:19
Lookup the location attributed to an IP by IP2Location Lite Country DB (https://lite.ip2location.com/database/ip-country)
package main
import (
"bufio"
"encoding/csv"
"errors"
"fmt"
"io"
"log"
"os"
# dict of conversion of google's charset to python codec name
enc_google_to_python = {
"windows-1257": "cp1257",
"GB2312 ": "gb2312",
"windows-874": "cp874",
"EUC-KR": "euc_kr",
"Shift_JIS": "shift_jis",
"UTF-8": "utf_8",
"ISO-8859-2": "iso8859_2",
"ISO-8859-9": "iso8859_9",
import re
def get_imports(script):
res = []
patt = re.compile('^(?:import|from).*$', re.MULTILINE)
raw_imports = re.findall(patt, script)
if raw_imports == []:
return None
for imp in raw_imports:
if '#' in imp:
#!/usr/bin/env python
# by @mazieres
from itertools import permutations
from collections import defaultdict
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
min_freq = 1
min_weight = 3
min_degree = 2
G.remove_edges_from([(u, v, d) for u, v, d in G.edges(data=True)
if d['weight'] <= min_weight])
G.remove_nodes_from([n for n, d in G.nodes(data=True)
if d['freq'] <= min_freq or
len(G[n]) <= min_degree])
xmllint --xpath '//*[@PostTypeId="1"]/@Tags' Posts.xml | sed 's/" Tags="/\n/g' | grep 'machine-learning' | sed 's/&lt;\|&gt;/;/g'