Emre Aladağ aladagemre

## sehirler.html
<select name="Sehir">
    <option value="0">------</option>
    <option value="1">Adana</option>
    <option value="2">Adıyaman</option>
    <option value="3">Afyonkarahisar</option>
    <option value="4">Ağrı</option>
    <option value="5">Amasya</option>
    <option value="6">Ankara</option>
    <option value="7">Antalya</option>
    <option value="8">Artvin</option>

## n11cat.py
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")]

## polen_crawler.py
"""
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

## skulpt-reveal.html
<!doctype html>
<html lang="en">

<head>
    <meta charset="utf-8">

    <title>reveal.js - The HTML Presentation Framework</title>

    <meta name="description" content="A framework for easily creating beautiful presentations using HTML">
    <meta name="author" content="Hakim El Hattab">

## tweetfetcher.go
package controllers

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

## pandas_dataframe_intersection.py
# 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)

## bordro.py
#encoding: utf-8
import math

ay = 1

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

SM = {}

## build_after_dropbox_sync.sh
#!/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

## heroku-bootup.py
import os

REGION = raw_input("Region? [US/eu] ").strip().lower() != "eu"
if REGION:
    REGION = "us"
else:
    REGION = "eu"
PROJECT_NAME = raw_input("Project name: ")
APP_NAME = raw_input("Initial app name: ")
USE_PGSQL = raw_input("Use PostgreSQL app? [Y/n] ").strip().lower() != "n"

## HBaseEdgeInputFormat.java
/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
	<select name="Sehir">
	<option value="0">------</option>
	<option value="1">Adana</option>
	<option value="2">Adıyaman</option>
	<option value="3">Afyonkarahisar</option>
	<option value="4">Ağrı</option>
	<option value="5">Amasya</option>
	<option value="6">Ankara</option>
	<option value="7">Antalya</option>
	<option value="8">Artvin</option>
	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")]
	"""
	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
	<!doctype html>
	<html lang="en">

	<head>
	<meta charset="utf-8">

	<title>reveal.js - The HTML Presentation Framework</title>

	<meta name="description" content="A framework for easily creating beautiful presentations using HTML">
	<meta name="author" content="Hakim El Hattab">
	package controllers

	import (
	"github.com/revel/revel"
	"fmt"
	"time"
	"gopkg.in/mgo.v2/bson"
	"net/url"
	"github.com/ChimeraCoder/anaconda"
	"strconv"
	# 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)
	#encoding: utf-8
	import math

	ay = 1

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

	SM = {}
	#!/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
	import os

	REGION = raw_input("Region? [US/eu] ").strip().lower() != "eu"
	if REGION:
	REGION = "us"
	else:
	REGION = "eu"
	PROJECT_NAME = raw_input("Project name: ")
	APP_NAME = raw_input("Initial app name: ")
	USE_PGSQL = raw_input("Use PostgreSQL app? [Y/n] ").strip().lower() != "n"
	/*
	* Licensed to the Apache Software Foundation (ASF) under one
	* or more contributor license agreements. See the NOTICE file
	* distributed with this work for additional information
	* regarding copyright ownership. The ASF licenses this file
	* to you under the Apache License, Version 2.0 (the
	* "License"); you may not use this file except in compliance
	* with the License. You may obtain a copy of the License at
	*
	* http://www.apache.org/licenses/LICENSE-2.0