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Federico Ceratto 2015-04-06 17:57:01 +01:00
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Nim-for-Python-Programmers.md
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@ -29,7 +29,7 @@ Types | Dynamic | Static
Dependent types | - | Partial support Dependent types | - | Partial support
Generics | Duck typing | Yes Generics | Duck typing | Yes
int8/16/32/64 types | No | Yes int8/16/32/64 types | No | Yes
Bigints | Yes (transparently) | Yes (via nimble package) Bigints (arbitrary size) | Yes (transparently) | Yes (via nimble package)
Arrays | Yes | Yes Arrays | Yes | Yes
Bounds-checking | Yes | Yes Bounds-checking | Yes | Yes
Type inference | Duck typing | Yes (extensive support) Type inference | Duck typing | Yes (extensive support)
@ -107,8 +107,7 @@ That will return a compilation error, because the objects have different sizes.
So, when using inheritance, be sure to inherit using refs, unless you know what you are doing. Also, check out Nim's generic programming capabilities as an alternative to OOP and inheritance. So, when using inheritance, be sure to inherit using refs, unless you know what you are doing. Also, check out Nim's generic programming capabilities as an alternative to OOP and inheritance.
## From Python to Nim
## Data structures
### Python tuples ### Python tuples
@ -124,3 +123,8 @@ The Nim set type is faster and memory-efficient.
### Dictionaries ### Dictionaries
Use [HashSet](http://nim-lang.org/sets.html) Use [HashSet](http://nim-lang.org/sets.html)
### ABC
See[this](http://rosettacode.org/wiki/Abstract_type#Nim)