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Revision 13 (Nicolas Aunai, 06/09/2016 07:57 AM) → Revision 14/19 (Andrea Ciardi, 26/09/2016 12:05 PM)

# LPP dev guide 


 ## Kick Starter for efficient scientific coding 

 You will find here material to help you get started with your coding. Depending on whether you mostly do data analysis or numerical modeling, you'll need slightly different tools and methods. the advice we give you will help to be efficient, rigorous and to write code than you'll be able to use, maintain and share in the long run. Now remember, **If you're a PhD or a post-doc**, following these advice will not only help you improving the quality and reproducibility of your science, but also will make all your coding efforts **reusable** by people in the lab once you're gone, and more importantly will give you the basic knowledge you need to legitimately claim for a data science / computing science position in the private sector. 


 * [[kickstartercommandments| The commandments of programming]] 
 * [[kickstartercommon| Common tools and methodology]] you'll need to get started. 

 Now, what are **you** doing? 

 * You're mostly coding for [[dataanalysiskickstarter| data analysis]] 
 * You're mostly coding for [[numericalmodelingkickstarter| numerical modeling]] 

 ## Code review and analysis 
 ### Code review 

 * [Code Review for Teams Too Busy to Review Code] (https://www.youtube.com/watch?v=1m3eRFeCInY) (youtube video) 
 * [Nice tutorial on code review with Rhodecode](https://docs.rhodecode.com/RhodeCode-Enterprise/code-review/code-review.html) 

 ### Code analysis 

 * [CPP Check](http://cppcheck.sourceforge.net) 

 ### Performance 

 Videos 

 * [Modern C++](https://www.youtube.com/watch?v=TJHgp1ugKGM) 



 Optimizations 

 * [Instruction tables](http://www.agner.org/optimize/instruction_tables.pdf) 

 ## Setting up a clean Python environment 

 * [[Python_and_virtualenv| Python and virtualenv]] 


 ## C++ development 

 *    [[cpplanguage| The C++ language]] 
 * [[designpatterns| Design Pattern]] in general and in C++ 
 * [[CppGurus| C++ Gurus]] 


 ## Code Design and Architecture 

 * [[solidprinciples| The S.O.L.I.D. principles]] 


 ## Writing code 

 * [[codereview| Code review]] 
 * [[Useful_resources| Useful resources]] 


 ## Documentation 

 * [[hyb-par: Documentationtools| Documentation Tools]] 
 *