jmandel

Proposal: Triggered Notifications

Use case: subscribing to specific lab observations

FHIR offers a REST API that lets clients search for resources on demand. Separately, there is a Messaging API that allows notifications to be "pushed" from one place to another. But neither API provides a clean solution to a common set of real-world "triggering" or notification-type requirements.

For example, let's say Mt. Auburn Hospital's Mother and Infant Unit wants to

milkbottlelough

...
...

{%- assign percentageDiscount = product.compare_at_price_max | minus: product.price | times: 100.0 | divided_by: product.compare_at_price_max | money_without_currency | times: 100 | remove: '.0' -%}

{% if product.compare_at_price_max > product.price %}
  <div class="sale-banner"><span>{{ 'collections.general.sale' | t }}</span><p>{{percentageDiscount}}%<span>OFF!</span></div>
{% endif %}

...

mnot

#!/usr/bin/env python

"""
Regex for URIs

These regex are directly derived from the collected ABNF in RFC3986
(except for DIGIT, ALPHA and HEXDIG, defined by RFC2234).

Additional regex are defined to validate the following schemes according to
their respective specifications:

mrf345

#!/bin/bash
pyinstaller -F -w \
--hidden-import='email.mime.multipart' \
--hidden-import='email.mime.message' \
--hidden-import='email.mime.text' \
--hidden-import='email.mime.image' \
--hidden-import='email.mime.audio' \
--hidden-import='sqlalchemy.sql.default_comparator' \
--hidden-import='jinja2' \
main.py

carlosplanchon

#!/usr/bin/env python3

from inspect import _empty, signature


def get_multiparameter_callback(callback, **parameters):
    callback_sig_p = signature(callback).parameters
    # If some provider parameter does not belong to callback parameters.
    unexpected_parameters = list(parameters.keys() - callback_sig_p.keys())
    if len(unexpected_parameters) > 0:

fabtho

#!/usr/bin/python
from selenium import webdriver
from PIL import Image
from cStringIO import StringIO

verbose = 1

browser = webdriver.Firefox()
browser.get('http://stackoverflow.com/questions/37906704/taking-a-whole-page-screenshot-with-selenium-marionette-in-python')

seanh

def format_filename(s):
    """Take a string and return a valid filename constructed from the string.
Uses a whitelist approach: any characters not present in valid_chars are
removed. Also spaces are replaced with underscores.
 
Note: this method may produce invalid filenames such as ``, `.` or `..`
When I use this method I prepend a date string like '2009_01_15_19_46_32_'
and append a file extension like '.txt', so I avoid the potential of using
an invalid filename.
 

acdha

#!/usr/bin/env python
# encoding: utf-8

from pprint import pformat, pprint
import logging


class PasswordMaskingFilter(logging.Filter):
    """Demonstrate how to filter sensitive data:"""

bitsgalore

#! /usr/bin/env python
import time
import threading
import logging
try:
    import tkinter as tk # Python 3.x
    import tkinter.scrolledtext as ScrolledText
except ImportError:
    import Tkinter as tk # Python 2.x
    import ScrolledText

dannguyen

Using Python 3 + Google Cloud Vision API's OCR to extract text from photos and scanned documents

Just a quickie test in Python 3 (using Requests) to see if Google Cloud Vision can be used to effectively OCR a scanned data table and preserve its structure, in the way that products such as ABBYY FineReader can OCR an image and provide Excel-ready output.

The short answer: No. While Cloud Vision provides bounding polygon coordinates in its output, it doesn't provide it at the word or region level, which would be needed to then calculate the data delimiters.

On the other hand, the OCR quality is pretty good, if you just need to identify text anywhere in an image, without regards to its physical coordinates. I've included two examples:

####### 1. A low-resolution photo of road signs