Even bad code can function. But if code isn't clean, it can bring a development organization to its knees.
Code is clean if it can be understood easily – by everyone on the team. Clean code can be read and enhanced by a developer other than its original author. With understandability comes readability, changeability, extensibility and maintainability.
- Follow standard conventions.
- Keep it simple stupid. Simpler is always better. Reduce complexity as much as possible.
- Boy scout rule. Leave the campground cleaner than you found it.
- Always find root cause. Always look for the root cause of a problem.
Item 1: View C++ as a federation of languages
- Rules for effective C++ programming vary, depending on the part of C++ you are using.
Item 2: Prefer consts, enums, and inlines to #defines
- For simple constants, prefer const objects or enums to #defines.
- For function-like macros, prefer inline functions to #defines.
Code is clean if it can be understood easily – by everyone on the team. Clean code can be read and enhanced by a developer other than its original author. With understandability comes readability, changeability, extensibility and maintainability.
- Follow standard conventions.
- Keep it simple stupid. Simpler is always better. Reduce complexity as much as possible.
- Boy scout rule. Leave the campground cleaner than you found it.
- Always find root cause. Always look for the root cause of a problem.
http://www.oreilly.com/data/free/files/2014-data-science-salary-survey.pdf | |
http://www.oreilly.com/data/free/files/2015-data-science-salary-survey.pdf | |
http://www.oreilly.com/data/free/files/Data_Analytics_in_Sports.pdf | |
http://www.oreilly.com/data/free/files/advancing-procurement-analytics.pdf | |
http://www.oreilly.com/data/free/files/ai-and-medicine.pdf | |
http://www.oreilly.com/data/free/files/analyzing-data-in-the-internet-of-things.pdf | |
http://www.oreilly.com/data/free/files/analyzing-the-analyzers.pdf | |
http://www.oreilly.com/data/free/files/architecting-data-lakes.pdf | |
http://www.oreilly.com/data/free/files/being-a-data-skeptic.pdf | |
http://www.oreilly.com/data/free/files/big-data-analytics-emerging-architecture.pdf |
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Add Graal JIT Compilation to Your JVM Language in 5 Steps, A Tutorial http://stefan-marr.de/2015/11/add-graal-jit-compilation-to-your-jvm-language-in-5-easy-steps-step-1/
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The SimpleLanguage, an example of using Truffle with great JavaDocs. It is the officle getting-started project: https://github.com/graalvm/simplelanguage
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Truffle Tutorial, Christan Wimmer, PLDI 2016, 3h recording https://youtu.be/FJY96_6Y3a4 Slides
by xero updated 10.29.24
Magic numbers are the first bits of a file which uniquely identify the type of file. This makes programming easier because complicated file structures need not be searched in order to identify the file type.
For example, a jpeg file starts with ffd8 ffe0 0010 4a46 4946 0001 0101 0047 ......JFIF.....G ffd8 shows that it's a JPEG file, and ffe0 identify a JFIF type structure. There is an ascii encoding of "JFIF" which comes after a length code, but that is not necessary in order to identify the file. The first 4 bytes do that uniquely.
This gives an ongoing list of file-type magic numbers.
(function(){ | |
var SCROLL_WIDTH = 24; | |
var btn_popup = document.getElementById("btn_popup"); | |
var popup = document.getElementById("popup"); | |
var popup_bar = document.getElementById("popup_bar"); | |
var btn_close = document.getElementById("btn_close"); | |
var smoke = document.getElementById("smoke"); |
#!/usr/bin/env python | |
import sys, os, time, platform | |
sample_ansi = '\x1b[31mRED' + '\x1b[33mYELLOW' + '\x1b[32mGREEN' + '\x1b[35mPINK' + '\x1b[0m' + '\n' | |
for handle in [sys.stdout, sys.stderr]: | |
if (hasattr(handle, "isatty") and handle.isatty()) or \ | |
('TERM' in os.environ and os.environ['TERM']=='ANSI'): | |
if platform.system()=='Windows' and not ('TERM' in os.environ and os.environ['TERM']=='ANSI'): |