fnky

ANSI Escape Sequences

Standard escape codes are prefixed with Escape:

• Ctrl-Key: ^[
• Octal: \033
• Unicode: \u001b
• Hexadecimal: \x1B
• Decimal: 27

dupuy

Markdown and reStructuredText

GitHub supports several lightweight markup languages for documentation; the most popular ones (generally, not just at GitHub) are Markdown and reStructuredText. Markdown is sometimes considered easier to use, and is often preferred when the purpose is simply to generate HTML. On the other hand, reStructuredText is more extensible and powerful, with native support (not just embedded HTML) for tables, as well as things like automatic generation of tables of contents.

akras14

Git Cheat Sheet

Commands

Getting Started

git init

or

hrldcpr

One-line Tree in Python

Using Python's built-in defaultdict we can easily define a tree data structure:

def tree(): return defaultdict(tree)

That's it!

XVilka

THIS GIST WAS MOVED TO TERMSTANDARD/COLORS REPOSITORY.

PLEASE ASK YOUR QUESTIONS OR ADD ANY SUGGESTIONS AS A REPOSITORY ISSUES OR PULL REQUESTS INSTEAD!

seanjensengrey

This is a small demo of how to create a library in Rust and call it from Python (both CPython and PyPy) using the CFFI instead of ctypes.

Based on http://harkablog.com/calling-rust-from-c-and-python.html (dead) which used ctypes

CFFI is nice because:

• Reads C declarations (parses headers)
• Works in both CPython and PyPy (included with PyPy)
• Lower call overhead than ctypes

churro-s

Here's my setup:

• Home server running Ubuntu 14.04.5 LTS (GNU/Linux 3.13.0-93-generic x86_64)
• Plex Media Server debian package running on server
• Netgear Nighthawk R6900 home router
• Dynamic hostname from no-ip.org, which I'll use for this setup

Prep

Complete up to the "Generate the cert" section in this gist

henryiii

MIT License

Copyright (c) 2023 Françoise CONIL

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

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

chris-belcher

Edit 14/09/2016

JoinMarket release 0.2.0 ameliorates this snooping attack. It is a protocol-breaking change so everyone must update which we anticipate may take some time.

https://github.com/JoinMarket-Org/joinmarket/blob/master/doc/release-notes-0.2.0.md

Edit2

Looks like enough people have updated and there's plenty of liquidity now.