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# encoding: utf-8
import os
filenames = filter(lambda x: x.endswith(".md"), os.listdir("."))

def parse(filename):
    print filename
    lines = open(filename).read().split("\n")
    tags_i = None
    last_tag_i = None
    tags = []

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# coding: utf-8
# TDK sözlüğünden eş anlamlıları çeker.
# words.txt dosyasında her satırda bir kelime olacak şekilde girdi listelenir.
# meanings.txt dosyasına her kelime için eş anlamlılarını bulur ve satır satır yazar.

import requests
import codecs

from bs4 import BeautifulSoup

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"""
When you have lots of mp4 files in a folder recursively (lots of subfolders and mp4s residing inside),
You can use this script to measure total duration of all mp4 files.

Useful in estimating the total course duration.

Run this script in folder where you want to start counting from.
"""

import subprocess

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@[Link("igraph")]
@[Link("glpk")]
@[Link("stdarg")]
@[Link("c++")]
lib IGraph
  VS_ALL = 0
  VS_ADJ = 1
  VS_NONE = 2
  VS_1 = 3
  VS_VECTORPTR = 4

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#!/bin/sh

uptodate () {
  # returns 1 if up to date, 0 otherwise.
  python /root/dropbox.py status | grep "Up to date" |wc -l
}
build_after_uptodate() {
  while [ "$(uptodate)" != "1" ];  do
    sleep 1
  done

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#encoding: utf-8
import math

ay = 1

BM = {}
EK = {}
AGI = {}

SM = {}

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# We have dataframe A with column name
# We have dataframe B with column name
# I want to see rows in A with name Y such that there exists rows in B with name Y.
# It's like set intersection.
intersected = reduce(lambda x, y: x | (A['name'] == y), [False] + list(B['name']))
intersection = A[intersected]

# other alternatives
intersection = pd.merge(A, B, how='inner', on=['name'])
intersection.dropna(inplace=True)

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package controllers

import (
    "github.com/revel/revel"
    "fmt"
    "time"
    "gopkg.in/mgo.v2/bson"
    "net/url"
    "github.com/ChimeraCoder/anaconda"
    "strconv"

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"""
This is a script for parsing polen levels in Madrid, Spain.
It used to work in 2019 but you may need to make fixes to make it work in the following years.
"""
import re
import locale
import time
import logging

import requests

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import bs4
import csv
import requests

r = requests.get("https://www.n11.com/site-haritasi")
soup = bs4.BeautifulSoup(r.text, features="html.parser")

with open("kategoriler.csv", "w") as csvfile:
    writer = csv.writer(csvfile, delimiter=';', quotechar='"')
    mcs = [(a.text, a.get('href')) for a in soup.find_all("a", class_="main-category")]