camillol

#include <unistd.h>
#include <CoreServices/CoreServices.h>
#include <ApplicationServices/ApplicationServices.h>

typedef int CGSConnection;
extern OSStatus CGSGetWorkspace(const CGSConnection cid, int *workspace);
extern OSStatus CGSSetWorkspace(const CGSConnection cid, int workspace);
extern CGSConnection _CGSDefaultConnection(void);

int get_space_id(void);

rwilcox

tell application "BBEdit" to set theFile to file of document 1
tell application "Finder" to set theFolder to (container of file theFile) as alias
set theUnixPath to POSIX path of theFolder

tell application "iTerm"
	tell current session of current terminal
		write text "pushd  \"" & theUnixPath & "\""
	end tell
	activate
end tell

netaustin

from fabric.api import *
from fabric.contrib.console import confirm
from local_settings import remote_user
from time import time
import subprocess, shlex, atexit, time
from settings import DATABASES
from os import remove

env.use_ssh_config = True
env.context = 'local'

charleslparker

#!/bin/bash

# Set credentials for BigML and for the US Census
BIGML_USERNAME=bigml
BIGML_API_KEY=****
CENSUS_API_KEY=****
BIGML_AUTH="username=$BIGML_USERNAME;api_key=$BIGML_API_KEY"

# Download demographic data into files.  Have to do it this way
# because the census API doesn't seem to allow returns of more

wutali

module Vagrant
  module Provisioners
    class Fabric < Base
      class Config < Vagrant::Config::Base
        attr_accessor :fabfile_path
        attr_accessor :fabric_path
        attr_accessor :python_path
        attr_writer :tasks

        def _default_fabfile_path

andrewcstewart

-- Find the note in omnifocus for the current project / folder
-- (or create a new one) and display it.

-- Created by Mark Fowler (mark@twoshortplanks.com)
-- Help from http://veritrope.com/code/search-evernote-for-notes-containing-link-to-selected-omnifocus-item/
-- on getting the name / url for the current omnifocus item


tell front window of application "OmniFocus"
	try

larsmans

>>> from pandas import DataFrame
>>> from sklearn.feature_extraction.text import CountVectorizer
>>> docs = ["You can catch more flies with honey than you can with vinegar.",
...         "You can lead a horse to water, but you can't make him drink."]
>>> vect = CountVectorizer(min_df=0., max_df=1.0)
>>> X = vect.fit_transform(docs)
>>> print(DataFrame(X.A, columns=vect.get_feature_names()).to_string())
   but  can  catch  drink  flies  him  honey  horse  lead  make  more  than  to  vinegar  water  with  you
0    0    2      1      0      1    0      1      0     0     0     1     1   0        1      0     2    2
1    1    2      0      1      0    1      0      1     1     1     0     0   1        0      1     0    2

yoavram

python ../nbconvert/nbconvert.py -f reveal reveal-test.ipynb
reveal-test_slides.html

kellrott

#!/usr/bin/env python
"""

Sample call:
python synapse_galaxy_sync.py <api_key> <api_url> syn12345

NOTE:  The upload method used requires the data library filesystem upload allow_library_path_paste
"""
import os
import shutil

dgraham

xcode-select --install

if [ ! -x /opt/homebrew/bin/brew ]; then
  /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
fi

brew tap 'homebrew/bundle'
brew tap 'homebrew/services'

brew install automake clang-format cmake icu4c libressl libxml2 openssl pkg-config readline sqlite yajl