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use framework "AppKit" | |
property ca : current application | |
on run {input, parameters} | |
-- calculate screen size | |
set activeScreenVisibleFrame to ca's NSScreen's mainScreen()'s visibleFrame() | |
set activeScreenSize to {ca's NSWidth(activeScreenVisibleFrame) as integer, ca's NSHeight(activeScreenVisibleFrame) as integer} | |
set screenWidth to item 1 of activeScreenSize | |
set screenHeight to item 2 of activeScreenSize | |
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#!/usr/bin/python | |
from datetime import datetime, timedelta | |
houses = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J'] | |
# start from house number x + 1 | |
start_index = 2 | |
num_houses = len(houses) | |
start_of_year = datetime(2015, 12, 28) |
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var fs = require('fs'); | |
var _ = require('lodash'); | |
var originalWords = []; | |
fs.readFile('alastalon_salissa.txt', 'utf8', function (err,data) { | |
if (err) { | |
return console.log(err); | |
} | |
process(data); |
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#!/usr/bin/python | |
# -*- coding: UTF-8 -*- | |
import codecs | |
from datetime import datetime | |
import feedparser | |
import sys | |
import re | |
sys.stdout = codecs.getwriter('utf-8')(sys.stdout) |
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{ | |
'FI1660012345678901': 'AABAFI22', | |
'FI8771312345678901': 'CITIFIHX', | |
'FI7980012345678901': 'DABAFIHH', | |
'FI0234012345678901': 'DABAFIHX', | |
'FI2637012345678901': 'DNBAFIHX', | |
'FI9133012345678901': 'ESSEFIHX', | |
'FI7531012345678901': 'HANDFIHH', | |
'FI0410012345678901': 'NDEAFIHH', | |
'FI8420012345678901': 'NDEAFIHH', |
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on do_menu(app_name, menu_name, menu_item) | |
try | |
-- bring the target application to the front | |
tell application app_name | |
activate | |
end tell | |
tell application "System Events" | |
tell process app_name | |
tell menu bar 1 | |
tell menu bar item menu_name |
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on do_menu(app_name, menu_name, menu_item) | |
try | |
-- bring the target application to the front | |
tell application app_name | |
activate | |
end tell | |
tell application "System Events" | |
tell process app_name | |
tell menu bar 1 | |
tell menu bar item menu_name |
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""" | |
Find scanned images or PDFs in directory, run Tesseract OCR on them. | |
Generate PDF, import the text content into the PDF's metadata. | |
""" | |
#!/usr/bin/env python | |
import codecs | |
import os | |
import re | |
from distutils.spawn import find_executable |