Yuval Greenfield ubershmekel

## decision_tree_code_gen.py
"""
How to use:
1. Place a "Python Script" node on your canvas
2. Hook your "Classification Tree" node out into the "Python Script" input
3. Paste this gist in the python script and hit "Execute"

The output should be similar to this:

    # slope (<32.000, 34.000>)
    if slope <=1.008: return False #(<7.000, 0.000>)

## distribute_and_pip.py
"""
This gist is a one-click pip setup for windows:

 1. installs distribute if needed
 2. installs pip
 3. (On windows) sets the path environment variable so "pip" is always runnable from cmd.

Tested on Windows 7 with python2.7
"""

## remove_rows.py
import Orange
bad_list = [
  'abc',
  'bcd',
  ]

id_index = in_data.domain.index('the_col_id')
out_data = Orange.data.Table(in_data)
# reversed so that the indexing is consistent after deletion
for i, row in reversed(list(enumerate(in_data))):

## startup_times.py
#!/usr/bin/python2.7
"""
Outputs on my PC:

"python2.7 startup_times.py nop" min run 0.019732 seconds
"python3.3 startup_times.py nop" min run 0.026251 seconds

"""
import subprocess
import time

## h1b.py
"""
Analyze USA h1b salaries

data from http://www.foreignlaborcert.doleta.gov/quarterlydata.cfm

specifically:
http://www.foreignlaborcert.doleta.gov/pdf/quarter_2_2012/PW_FY2012_Q2.csv
"""

import math

## shapeTrig.html
<!DOCTYPE html>
<html manifest="main.appcache">
<meta charset="utf-8">
<style>

.circle, .wave {
  fill: none;
  stroke: steelblue;
  stroke-width: 1.5px;
}

## censor_ascii.py
import pprint
import os
from collections import Counter


ascii_markers = "|\\/_\" ()n"

def ascii_prob(line):
    line = line.strip()

## SimpleHTTPServerSSL.py
'''
SimpleHTTPServerSSL.py - simple HTTP server supporting SSL/TLS. I.e. HTTPS. For python 3.3

- replace CERT and KEY with the location of your .pem server file.
- the default port is 443.

usage: python SimpleHTTPServerSSL.py

based on http://code.activestate.com/recipes/442473-simple-http-server-supporting-ssl-secure-communica/
'''

## json_history_to_kml.py
"""
Convert LocationHistory.json from Google takeout of location history (latitude)
to a usable KML file for viewing in Google Earth.


Usage:

    python json_history_to_kml.py LocationHistory.json


## 8086_socket_count.py
"""

Data from
http://en.wikipedia.org/wiki/CPU_socket#List_of_80x86_sockets_and_slots

copy pasted html to excel, copy pasted excel to python
ran python
pasted output to excel, drew a graph

There's probably a simpler way to do a pivot table but I don't know how.
	"""
	How to use:
	1. Place a "Python Script" node on your canvas
	2. Hook your "Classification Tree" node out into the "Python Script" input
	3. Paste this gist in the python script and hit "Execute"

	The output should be similar to this:

	# slope (<32.000, 34.000>)
	if slope <=1.008: return False #(<7.000, 0.000>)
	"""
	This gist is a one-click pip setup for windows:

	1. installs distribute if needed
	2. installs pip
	3. (On windows) sets the path environment variable so "pip" is always runnable from cmd.

	Tested on Windows 7 with python2.7
	"""
	import Orange
	bad_list = [
	'abc',
	'bcd',
	]

	id_index = in_data.domain.index('the_col_id')
	out_data = Orange.data.Table(in_data)
	# reversed so that the indexing is consistent after deletion
	for i, row in reversed(list(enumerate(in_data))):
	#!/usr/bin/python2.7
	"""
	Outputs on my PC:

	"python2.7 startup_times.py nop" min run 0.019732 seconds
	"python3.3 startup_times.py nop" min run 0.026251 seconds

	"""
	import subprocess
	import time
	"""
	Analyze USA h1b salaries

	data from http://www.foreignlaborcert.doleta.gov/quarterlydata.cfm

	specifically:
	http://www.foreignlaborcert.doleta.gov/pdf/quarter_2_2012/PW_FY2012_Q2.csv
	"""

	import math
	<!DOCTYPE html>
	<html manifest="main.appcache">
	<meta charset="utf-8">
	<style>

	.circle, .wave {
	fill: none;
	stroke: steelblue;
	stroke-width: 1.5px;
	}
	import pprint
	import os
	from collections import Counter



	ascii_markers = "\|\\/_\" ()n"

	def ascii_prob(line):
	line = line.strip()
	'''
	SimpleHTTPServerSSL.py - simple HTTP server supporting SSL/TLS. I.e. HTTPS. For python 3.3

	- replace CERT and KEY with the location of your .pem server file.
	- the default port is 443.

	usage: python SimpleHTTPServerSSL.py

	based on http://code.activestate.com/recipes/442473-simple-http-server-supporting-ssl-secure-communica/
	'''
	"""
	Convert LocationHistory.json from Google takeout of location history (latitude)
	to a usable KML file for viewing in Google Earth.


	Usage:

	python json_history_to_kml.py LocationHistory.json
	"""

	Data from
	http://en.wikipedia.org/wiki/CPU_socket#List_of_80x86_sockets_and_slots

	copy pasted html to excel, copy pasted excel to python
	ran python
	pasted output to excel, drew a graph

	There's probably a simpler way to do a pivot table but I don't know how.