Beautiful Python Idioms

Wrap Up of Ned Batchelder's and Raymond Hettinger's conferences at PYCON US 2013 for the first Paris.py meeting, holding in Paris June, 12th 2013.

Transcript

1. BEAUTIFUL PYTHON IDIOMS PARIS.PY MEETUP - 2013/06/12
2. WHO AM I? olivier hervieu software python developer at tinyclues my twitter (junk) account: @ _ o l i v i e r _
3. WHY THIS PRESENTATION? inspired by Raymond Hettinger's conference at Pycon inspired by Ned Batchelder's conference at Pycon 90 minutes of conferences in 10!
4. PART 1: THE GOOD
5. LOOPING OVER NUMBERS bad: even worse: better: f o r i i n r a n g e ( 6 ) : p r i n t i * * 2 f o r i i n [ 0 , 1 , 2 , 3 , 4 , 5 ] : p r i n t i * * 2 f o r i i n x r a n g e ( 6 ) : p r i n t i * * 2
6. LOOPING OVER COLLECTIONS evil things: f o r i i n x r a n g e ( l e n ( c o l o r s ) ) : p r i n t c o l o r s [ i ] f o r i i n x r a n g e ( l e n ( c o l o r s ) - 1 , - 1 , - 1 ) : p r i n t c o l o r s [ i ] c o l o r s = [ ' b l u e ' , ' r e d ' , ' y e l l o w ' , ' p u r p l e ' ] f o r i i n x r a n g e ( l e n ( c o l o r s ) ) : p r i n t i , c o l o r s [ i ]
8. please consider (and use!) the following: f o r c o l o r i n c o l o r s : p r i n t c o l o r f o r c o l o r i n r e v e r s e d ( c o l o r s ) : p r i n t c o l o r c o l o r s = [ ' b l u e ' , ' r e d ' , ' y e l l o w ' , ' p u r p l e ' ] f o r i , c o l o r i n e n u m e r a t e ( c o l o r s ) : p r i n t i , c o l o r
9. LOOPING OVER TWO (OR MORE) COLLECTIONS dumb version: and what you really want to do: the generator way: see also: i z i p _ l o n g e s t in i t e r t o o l s f i r s t n a m e s = [ ' A l i c e ' , ' B o b ' , ' J o h n ' ] l a s t n a m e s = [ ' D u p o n t ' , ' S l e i g h ' , ' D o e ' ] a g e s = [ 2 4 , 6 3 , 3 3 ] z i p p e d _ d a t a = [ ] n = m i n ( l e n ( f i r s t n a m e s ) , l e n ( l a s t n a m e s ) , l e n ( a g e s ) ) f o r i i n r a n g e ( n ) : z i p p e d _ d a t a . a p p e n d ( ( f i r s t n a m e s [ i ] , l a s t n a m e s [ i ] , a g e s [ i ] ) ) z i p ( f i r s t n a m e s , l a s t n a m e s , a g e s ) i z i p ( f i s t n a m e s , l a s t n a m e s , a g e s )
10. CREATING DICTIONARIES FROM PAIRS f i r s t n a m e s = [ ' A l i c e ' , ' B o b ' , ' J o h n ' ] a g e s = [ 2 4 , 6 3 , 3 3 ] d = d i c t ( i z i p ( f i r s t n a m e s , a g e s ) ) # { ' A l i c e ' : 2 4 , ' B o b ' : 6 3 , ' J o h n ' : 3 3 } d = d i c t ( e n u m e r a t e ( f i r s t n a m e s ) ) # { 0 : ' A l i c e ' , 1 : ' B o b ' , 2 : ' J o h n ' }
11. MASTERING LIST/SET/DICT COMPREHENSION or is equivalent to: s u m = 0 f o r i i n x r a n g e ( 1 0 ) : s u m + = i * * 2 p r i n t s u m p o w _ 2 = [ ] f o r i i n x r a n g e ( 1 0 ) : p o w _ 2 . a p p e n d ( i * * 2 ) p r i n t s u m ( p o w _ 2 ) p r i n t s u m ( [ i * * 2 f o r i i n x r a n g e ( 1 0 ) ] ) p r i n t s u m ( i * * 2 f o r i i n x r a n g e ( 1 0 ) )
12. c o l o r s = [ ' b ' , ' r ' , ' g ' , ' g ' , ' r ' , ' r ' , ' r ' , N o n e ] u n i q u e _ c o l o r s = { c o l o r f o r c o l o r i n c o l o r s i f c o l o r } p o w _ 2 _ m a p = { k : k * * 2 f o r k i n x r a n g e ( 1 0 0 0 0 ) }
13. READING FILES the < 2 . 6 way: you should use: f = o p e n ( ' d a t a . t x t ' ) t r y : d a t a = f . r e a d ( ) f i n a l l y : f . c l o s e ( ) w i t h o p e n ( ' d a t a . t x t ' ) a s f : d a t a = f . r e a d ( )
14. PART 2: THE BEAUTIFUL
15. CONTEXT MANAGER probably my favorite use case scenario: avoiding the t r y / e x c e p t / p a s s pattern t r y : o s . r e m o v e ( ' s o m e f i l e . t m p ' ) e x c e p t O S E r r o r : p a s s f r o m c o n t e x t l i b i m p o r t c o n t e x t m a n a g e r @ c o n t e x t m a n a g e r d e f i g n o r e d ( * e x c e p t i o n s ) : t r y : y i e l d e x c e p t e x c e p t i o n s : p a s s w i t h i g n o r e d ( O S E r r o r ) : o s . r e m o v e ( ' s o m e f i l e . t m p ' )
16. I M P O R T I N F I N I T Y i t e r t o o l s . c o u n t ( ) i t e r t o o l s . c y c l e ( )
17. POWERFUL METHODS common methods come with handful parameters: t a l l _ b u i l d i n g s = { " E m p i r e S t a t e " : 3 8 1 , " S e a r s T o w e r " : 4 4 2 , " B u r j K h a l i f a " : 8 2 8 , " T a i p e i 1 0 1 " : 5 0 9 , } p r i n t m a x ( t a l l _ b u i l d i n g s . v a l u e s ( ) ) p r i n t m a x ( t a l l _ b u i l d i n g s . i t e m s ( ) , k e y = l a m b d a b : b [ 1 ] ) # ( ' B u r j K h a l i f a ' , 8 2 8 ) p r i n t m a x ( t a l l _ b u i l d i n g s , k e y = t a l l _ b u i l d i n g s . g e t ) # ' B u r j K h a l i f a '
18. c o l o r s = [ ' r e d ' , ' g r e e n ' , ' b l u e ' , ' y e l l o w ' ] f o r c o l o r i n s o r t e d ( c o l o r s ) : p r i n t c o l o r f o r c o l o r i n s o r t e d ( c o l o r s , r e v e r s e = T r u e ) : p r i n t c o l o r d e f c o m p a r e _ l e n g t h ( c 1 , c 2 ) : i f l e n ( c 1 ) < l e n ( c 2 ) : r e t u r n - 1 i f l e n ( c 1 ) > l e n ( c 2 ) : r e t u r n 1 r e t u r n 0 p r i n t s o r t e d ( c o l o r s , c m p = c o m p a r e _ l e n g t h ) p r i n t s o r t e d ( c o l o r s , k e y = l e n )
19. FOR/ELSE STATEMENTS use the e l s e statement to detect if a b r e a k has been encountered: d e f f i n d ( s e q , t a r g e t ) : f o u n d = F a l s e f o r i , v a l u e i n e n u m e r a t e ( s e q ) : i f v a l u e = = t g t : f o u n d = T r u e b r e a k i f n o t f o u n d : r e t u r n - 1 r e t u r n i d e f f i n d ( s e q , t a r g e t ) : f o r i , v a l u e i n e n u m e r a t e ( s e q ) : i f v a l u e = = t g t : b r e a k e l s e : r e t u r n - 1 r e t u r n i
20. COUNTING WITH DICTIONNARIES (OR KNOW YOUR STANDARD LIBRARY)
21. naive implementation: c o l o r s = [ ' r e d ' , ' g r e e n ' , ' r e d ' , ' b l u e ' , ' g r e e n ' , ' r e d ' ] d = { } f o r c o l o r i n c o l o r s : i f c o l o r n o t i n d : d [ c o l o r ] = 0 d [ c o l o r ] + = 1
22. slightly better: d = { } f o r c o l o r i n c o l o r s : d [ c o l o r ] = d . g e t ( c o l o r , 0 ) + 1
23. in limbo: f r o m c o l l e c t i o n s i m p o r t d e f a u l t d i c t d = d e f a u l t d i c t ( i n t ) f o r c o l o r i n c o l o r s : d [ c o l o r ] + = 1
24. python guru: f r o m c o l l e c t i o n s i m p o r t C o u n t e r C o u n t e r ( c o l o r s )
25. GENERATORS d e f e v e n s ( s t r e a m ) : f o r n i n s t r e a m : i f n % 2 = = 0 : y i e l d n f o r n i n e v e n s ( x r a n g e ( 1 0 0 0 0 ) ) : d o _ s o m e t h i n g ( n )
26. NAMEDTUPLE c l a s s B o o k O r d e r ( o b j e c t ) d e f _ _ i n i t _ _ ( s e l f , n a m e , q u a n t i t y ) : s e l f . n a m e = n a m e s e l f . q u a n t i t y = q u a n t i t y f r o m c o l l e c t i o n i m p o r t n a m e d t u p l e B o o k O r d e r = n a m e d t u p l e ( ' B o o k O r d e r ' , [ ' n a m e ' , ' q u a n t i t y ' ] )
27. PART 3: THE AWESOME
28. POWERFUL ITERATION CONTINUE A FUNCTION UNTIL A SENTINEL VALUE IS REACHED everybody write this: write this instead: b l o c k s = [ ] w h i l e T r u e : b l o c k = f . r e a d ( 3 2 ) i f b l o c k = = ' ' : b r e a k b l o c k s . a p p e n d ( b l o c k ) b l o c k s = [ ] f o r b l o c k i n i t e r ( p a r t i a l ( f . r e a d , 3 2 ) , ' ' ) : b l o c k s . a p p e n d ( b l o c k )
29. FIND ELEMENTS n e x t ( ( i f o r i i n x r a n g e ( 1 0 0 0 ) i f i > 1 0 a n d i % 2 ) , 0 )
30. ABSTRACTING ITERATION thanks to generators, simplify your code: f = o p e n ( " m y _ c o n f i g . i n i " ) f o r l i n e i n f : l i n e = l i n e . s t r i p ( ) i f l i n e . s t a r t s w i t h ( ' # ' ) : # A c o m m e n t l i n e , s k i p i t . c o n t i n u e i f n o t l i n e : # A b l a n k l i n e , s k i p i t . c o n t i n u e # A n i n t e r e s t i n g l i n e . d o _ s o m e t h i n g ( l i n e )
31. d e f i n t e r e s t i n g _ l i n e s ( f ) : f o r l i n e i n f : l i n e = l i n e . s t r i p ( ) i f l i n e . s t a r t s w i t h ( ' # ' ) : c o n t i n u e i f n o t l i n e : c o n t i n u e y i e l d l i n e w i t h o p e n ( " m y _ c o n f i g . i n i " ) a s f : f o r l i n e i n i n t e r e s t i n g _ l i n e s ( f ) : d o _ s o m e t h i n g ( l i n e )
32. USING DECORATORS the web cache example: powered re-usability with decorators! d e f w e b _ l o o k u p ( u r l , s a v e d = { } ) : i f u r l i n s a v e d : r e t u r n s a v e d [ u r l ] p a g e = u r l l i b . u r l o p e n ( u r l ) . r e a d ( ) s a v e d [ u r l ] = p a g e r e t u r n p a g e @ c a c h e d e f w e b _ l o o k u p ( u r l ) : r e t u r n u r l l i b . u r l o p e n ( u r l ) . r e a d ( ) d e f c a c h e ( f u n c ) : s a v e d = { } @ w r a p s ( f u n c ) d e f n e w f u n c ( * a r g s ) : i f a r g s i n s a v e d : r e t u r n n e w f u n c ( * a r g s ) r e s u l t = f u n c ( * a r g s ) s a v e d [ a r g s ] = r e s u l t r e t u r n r e s u l t r e t u r n n e w f u n c
33. PART 4: GOODIES AND ADVICE
34. EXPLICIT IS BETTER THAN IMPLICIT is better than: and: is better than: f i r s n a m e , l a s t n a m e , a g e = [ " J o h n " , " D o e " , 3 3 ] w h o a m i = [ " J o h n " , " D o e " , 3 3 ] f i r s t a n a m e = w h o m a i [ 0 ] l a s t n a m e = w h o a m i [ 1 ] a g e = w h o a m i [ 2 ] t w i t t e r _ s e a r c h ( ' @ o b a m a ' , r e t w e e t s = F a l s e , n u m t w e e t s = 2 0 , p o p u l a r = T r u e ) t w i t t e r _ s e a r c h ( ' @ o b a m a ' , F a l s e , 2 0 , T r u e )
35. UNLIMITED DEFAULT DICT i n f i n i t e _ d e f a u l t d i c t = l a m b d a : d e f a u l t d i c t ( i n f i n i t e _ d e f a u l t d i c t )
36. MATRIX TRANSPOSITION WITH ZIP a = [ [ 1 , 2 , 3 ] , [ 4 , 5 , 6 ] , [ 7 , 8 , 9 ] ] t r _ a = [ l i s t ( i ) f o r i i n z i p ( * a ) ]
37. THANK YOU!