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@codediodeio
codediodeio / database.rules.json
Last active January 10, 2025 22:28
Common Database Rules for Firebase
// No Security
{
"rules": {
".read": true,
".write": true
}
}
@sameerkumar18
sameerkumar18 / example_flask_googlecaptcha.py
Created May 20, 2017 07:04
A Simple Python Flask Example for Google Recaptcha (implemented on http://ipusearch.herokuapp.com)
RECAPTCHA_PUBLIC_KEY = '<public key>'
RECAPTCHA_PRIVATE_KEY = '<private key>'
def checkRecaptcha(response, secretkey):
url = 'https://www.google.com/recaptcha/api/siteverify?'
url = url + 'secret=' + str(secretkey)
url = url + '&response=' +str(response)
@justincbagley
justincbagley / How_to_Convert_Markdown_to_PDF.md
Last active March 27, 2025 03:38
How To Convert Markdown to PDF

How to convert markdown to PDF:

This post reviews several methods for converting a Markdown (.md) formatted file to PDF, from UNIX or Linux machines.

Using Pandoc:

$ pandoc How_I_got_svg-resizer_working_on_Mac_OSX.md -s -o test1.pdf
import pytesseract
import sys
import argparse
try:
import Image
except ImportError:
from PIL import Image
from subprocess import check_output
@scrapehero
scrapehero / linkedin_scraper.py
Last active February 11, 2025 09:34
Python script to scrape a company details from a public company page on LinkedIn.com. Written as part of How to Scrape educational post - https://www.scrapehero.com/tutorial-scraping-linkedin-for-public-company-data/
from lxml import html
import csv, os, json
import requests
from exceptions import ValueError
from time import sleep
def linkedin_companies_parser(url):
for i in range(5):
try:
@AshikNesin
AshikNesin / react-file-upload.js
Created February 2, 2017 06:46
Simple React File Upload
import React from 'react'
import axios, { post } from 'axios';
class SimpleReactFileUpload extends React.Component {
constructor(props) {
super(props);
this.state ={
file:null
}
@shanealynn
shanealynn / python batch geocoding.py
Last active September 10, 2024 19:44
Geocode as many addresses as you'd like with a powerful Python and Google Geocoding API combination
"""
Python script for batch geocoding of addresses using the Google Geocoding API.
This script allows for massive lists of addresses to be geocoded for free by pausing when the
geocoder hits the free rate limit set by Google (2500 per day). If you have an API key for paid
geocoding from Google, set it in the API key section.
Addresses for geocoding can be specified in a list of strings "addresses". In this script, addresses
come from a csv file with a column "Address". Adjust the code to your own requirements as needed.
After every 500 successul geocode operations, a temporary file with results is recorded in case of
script failure / loss of connection later.
Addresses and data are held in memory, so this script may need to be adjusted to process files line
@noelboss
noelboss / git-deployment.md
Last active April 1, 2025 16:56
Simple automated GIT Deployment using Hooks

Simple automated GIT Deployment using GIT Hooks

Here are the simple steps needed to create a deployment from your local GIT repository to a server based on this in-depth tutorial.

How it works

You are developing in a working-copy on your local machine, lets say on the master branch. Most of the time, people would push code to a remote server like github.com or gitlab.com and pull or export it to a production server. Or you use a service like deepl.io to act upon a Web-Hook that's triggered that service.

@fchollet
fchollet / classifier_from_little_data_script_3.py
Last active February 26, 2025 01:37
Fine-tuning a Keras model. Updated to the Keras 2.0 API.
'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats
@fchollet
fchollet / classifier_from_little_data_script_1.py
Last active February 26, 2025 01:37
Updated to the Keras 2.0 API.
'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats