Finding attributes in a list

[Ben]

Hi

In a list I have a number of soccer players. Each player has a
different rating for attacking, defending, midfield fitness and
goalkeeping.

I have devised a while loop that goes through this list to find the
best player at defending, attacking, midfield and goalkeeping. However
there is more than one defender per team so I therefore need it to find
the next best player.

Below is the code used to ascertain the best defender:


# STUFF TO FIND THE TOP DEFENDER
defender = 0 # The position of defender is set to the first player
in the knowledge base
topdefender = 0
c = 3 # the defensive rating of the first player in the list
d = (len(squadList)-4) # the defensive rating of the last player in the
list.

while c <= d:
if squadList[c] > topdefender:
topdefender = squadList[c]
defender = squadList[c-3] + " " + squadList[c-2] # The
defender variable is assigned to the forename and surname of the player
c = c + 8 # Move to the defensive rating of the next player in the
list

print defender



any help on this would be greatly appreciated.

thank you

 

[infidel]

You can use the new 'sorted' built-in function and custom "compare"
functions to return lists of players sorted according to any criteria:

players = [

.... {'name' : 'joe', 'defense' : 8, 'attacking' : 5, 'midfield' : 6,
'goalkeeping' : 9},
.... {'name' : 'bob', 'defense' : 5, 'attacking' : 9, 'midfield' : 6,
'goalkeeping' : 3},
.... {'name' : 'sam', 'defense' : 6, 'attacking' : 7, 'midfield' : 10,
'goalkeeping' : 4}
.... ].... return cmp(second['attacking'], first['attacking'])
....

[p['name'] for p in sorted(players, cmp_attacking)] ['bob', 'sam', 'joe']

 

[Steven Bethard]

You can use the new 'sorted' built-in function and custom "compare"
functions to return lists of players sorted according to any criteria:

players = [

... {'name' : 'joe', 'defense' : 8, 'attacking' : 5, 'midfield' : 6,
'goalkeeping' : 9},
... {'name' : 'bob', 'defense' : 5, 'attacking' : 9, 'midfield' : 6,
'goalkeeping' : 3},
... {'name' : 'sam', 'defense' : 6, 'attacking' : 7, 'midfield' : 10,
'goalkeeping' : 4}
... ]

... return cmp(second['attacking'], first['attacking'])
...

[p['name'] for p in sorted(players, cmp_attacking)]

['bob', 'sam', 'joe']

Or more efficiently, use the key= and reverse= parameters:

py> players = [
.... dict(name='joe', defense=8, attacking=5, midfield=6),
.... dict(name='bob', defense=5, attacking=9, midfield=6),
.... dict(name='sam', defense=6, attacking=7, midfield=10)]
py> import operator
py> [p['name'] for p in sorted(players,
.... key=operator.itemgetter('attacking'),
.... reverse=True)]
['bob', 'sam', 'joe']

STeVe

 

[Bengt Richter]

You can use the new 'sorted' built-in function and custom "compare"
functions to return lists of players sorted according to any criteria:

players = [

... {'name' : 'joe', 'defense' : 8, 'attacking' : 5, 'midfield' : 6,
'goalkeeping' : 9},
... {'name' : 'bob', 'defense' : 5, 'attacking' : 9, 'midfield' : 6,
'goalkeeping' : 3},
... {'name' : 'sam', 'defense' : 6, 'attacking' : 7, 'midfield' : 10,
'goalkeeping' : 4}
... ]

def cmp_attacking(first, second):

... return cmp(second['attacking'], first['attacking'])
...

[p['name'] for p in sorted(players, cmp_attacking)]

['bob', 'sam', 'joe']

Or more efficiently, use the key= and reverse= parameters:

py> players = [
... dict(name='joe', defense=8, attacking=5, midfield=6),
... dict(name='bob', defense=5, attacking=9, midfield=6),
... dict(name='sam', defense=6, attacking=7, midfield=10)]
py> import operator
py> [p['name'] for p in sorted(players,
... key=operator.itemgetter('attacking'),
... reverse=True)]
['bob', 'sam', 'joe']

Perhaps the OP doesn't yet realize that Python also provides the ability
to define custom classes to represent players etc. E.g., using instance attribute
dicts instead of raw dicts (to save typing ;-):
... def __init__(self, **kw): self.__dict__.update(kw)

>>> players = [

... Player(name='joe', defense=8, attacking=5, midfield=6),
... Player(name='bob', defense=5, attacking=9, midfield=6),
... Player(name='sam', defense=6, attacking=7, midfield=10)]

>>> players

>>> import operator
>>> [p.name for p in sorted(players, key=operator.attrgetter('attacking'), reverse=True)]

['bob', 'sam', 'joe']

And then he could create a Team class which might have players as an internal list,
and provide methods for modifying the team etc., and generating various reports
or calculating and/or retrieving data. Not to mention properties for dynamically
caclulated attributes etc ;-)

Regards,
Bengt Richter

 

[Marcus Goldfish]

class Player(object):

def __init__(self, **kw): self.__dict__.update(kw)
def __repr__(self): return '<Player %s>'%getattr(self, 'name', '(anonymous)')

import operator
[p.name for p in sorted(players, key=operator.attrgetter('attacking'), reverse=True)]

Just happened to read this thread and wanted to say this is a neat
little example-- thank you! I have a couple of followup questions.

(1) Is there a performance penalty for using key=operator.attrgetter()?
(2) The Player class looks like a nice model for a data table when one
wants to sort by arbitrary column. Would you agree?
(3) Suppose one wished to construct a player list from a collection of
attribute lists, e.g.,

names = ['bob', 'sam', 'linda']
attack = [7, 5, 8]
defense = [6, 8, 6]
# construct players list here

Can you recommend an efficient way to construct the player list?

Thanks!
Marcus

 

[James Stroud]

(2) The Player class looks like a nice model for a data table when one
wants to sort by arbitrary column. Would you agree?

The Player class is (and any class) is absolutely fabulous when you have
heterogenous data (string, int, etc). I would not fall into the trap of LoDs
(Lists of Dictionaries). They get unwieldy because you always have to manage
them with functions. You end up writing a module built around your specific
dictionary and you end up with a duct-taped object oriented design anyway.
Classes are way better--so use them up front, even if you think that your
data structure will never be complicated enough to warrant a class. It
eventually will if it is worth a damn to begin with. Given this is a soccer
team we are talking about, it is definitely worth being a full fledged class.
However, if it were basketball...

(3) Suppose one wished to construct a player list...[snip]

team = [Player(azip[0],azip[1],azip[2]) for azip in zip(names,attack,defense)]


You have to love listcomp.

Better (IMHO) would be

team = [Player(azip) for azip in zip(names,attack,defense)]

where a Player might come to life with

class Player(object):
def __init__(self, atup):
self.name, self.attack, self.defense = atup

BUT, even way better (again, IMHO) would be

ateam = Team(zip(names,attack,defense))

where team could be initialized by a tuple:

class Team(list):
def __init__(self, azip):
for azip in alist:
self.data.append(Player(atup))

James

--
James Stroud, Ph.D.
UCLA-DOE Institute for Genomics and Proteomics
Box 951570
Los Angeles, CA 90095

http://www.jamesstroud.com/

 

[James Stroud]

where team could be initialized by a tuple:

  class Team(list):
    def __init__(self, azip):
      for azip in alist:
        self.data.append(Player(atup))

Sorry, this should read:

where team could be initialized by a list of tuples:

class Team(list):
def __init__(self, azip):
for atup in azip:
self.data.append(Player(atup))

--
James Stroud, Ph.D.
UCLA-DOE Institute for Genomics and Proteomics
Box 951570
Los Angeles, CA 90095

http://www.jamesstroud.com/

 

[Bengt Richter]

class Player(object):
def __init__(self, **kw): self.__dict__.update(kw)
def __repr__(self): return '<Player %s>'%getattr(self, 'name', '(anonymous)')

import operator
[p.name for p in sorted(players, key=operator.attrgetter('attacking'), reverse=True)]

Just happened to read this thread and wanted to say this is a neat
little example-- thank you! I have a couple of followup questions.

(1) Is there a performance penalty for using key=operator.attrgetter()?

I would think sorted would make it as efficient as possible, but possibly.

(2) The Player class looks like a nice model for a data table when one
wants to sort by arbitrary column. Would you agree?

Depends on scale, and what else use you have for a custom object representation. E.g.,
(using below lists available from interactive session below) a plain dict by names (unique required)
with (attack, defense) tuples as values is probably pretty efficient and fast.
{'linda': (8, 6), 'bob': (7, 6), 'sam': (5, 8)}

But if objects are going to be complex and have methods or properties, OO makes it easy.

(3) Suppose one wished to construct a player list from a collection of
attribute lists, e.g.,

names = ['bob', 'sam', 'linda']
attack = [7, 5, 8]
defense = [6, 8, 6]
# construct players list here

Can you recommend an efficient way to construct the player list?

I wouldn't worry about efficiency unless you are dealing with a database of
all the worlds teams ;-) (And in that case, you probably want to look into
interfacing with the database your data is already in, to let it do things
for you natively e.g. via SQL).

If you know the "columns" as matching attribute lists as above, zip will associate them
into tuples. Also, I used a keyword argument in the Player __init__ above because I
wanted to copy and paste the dict calls from the prior post, but knowing exact columns,
I'd probably do some thing like:
... def __init__(self, name, attack=None, defense=None): # require name
... self.name = name
... self.attack = attack
... self.defense = defense
...

>>> names = ['bob', 'sam', 'linda']
>>> attack = [7, 5, 8]
>>> defense = [6, 8, 6]
>>>

Then the players list is just

>>> players = [Player(*tup) for tup in zip(names, attack, defense)]

where *tup unpacks a tuple from the output of zip into the arg list of Player's __init__.

And you can extract the names like

>>> [player.name for player in players]

['bob', 'sam', 'linda']

Or whatever you want ...
bob 7 6
sam 5 8
linda 8 6

As mentioned, zip makes tuples of corresponding elements of its argument lists: [('bob', 7, 6), ('sam', 5, 8), ('linda', 8, 6)]

If you had huge input lists, you could avoid the terporary tuple list using ...
bob 7 6
sam 5 8
linda 8 6

You can look into __slots__ if you want to have objects but need reduced memory footprint.
But don't worry about optimizing 'til you can prove you need it, unless just for fun ;-)

Ok. That's enough relief for me. Got other stuff ...

Regards,
Bengt Richter