I have a problem with naming two similar methods. One is a static method and another one is a method that is the same method but works on the instance. Is it a proper way to do it or should I use only a static method.
Class GameBoard()
def __init__(self, blank_board):
self.board = blank_board
#staticmethod
def get_empty_cells(board):
"""Returns a list of empty cells coordinates (x,y)"""
empty = []
for row_no, row in enumerate(board):
for cell_no, cell in enumerate(row):
if cell == ' ':
empty.append((row_no, cell_no))
return empty
def board_empty_cells(self):
return self.get_empty_cells(self.board)
board1 = GameBoard(blank_board)
board2 = [.....]
empty_board1 = board1.board_empty_cells()
empty_board2 = GameBoard.get_empty_cells(board2)
The reason of that is that I would like to be able to evaluate other boards with the static method, but also if I want to get the instance's empty cells I would like to call board_empty_cells().
Is that a clean code approach or should I get empty cells like:
board1 = GameBoard(blank_board)
empty_board1 = board1.get_empty_cells(board1.board)
What would be proper names for those two functions to be descriptive and unambiguous that one of them is a static method and another operates on instance. Is there any convention to follow to distinguish static methods from methods?
#staticmethod
def get_empty_cells(board):
pass
def board_empty_cells(self):
pass
A lot of times I run into a 'problem' with proper naming for methods and functions.
Is there any guide/convention how to properly name methods (like get_board, is_finished etc.)? I don't mean PEP 8 which I'm familiar with. I mean something that would help me choose proper names that actually would make my code more readable.
Related
I have a question on the usage of the setattr method in python.
I have a python class with around 20 attributes, which can be initialized in the below manner:
class SomeClass():
def __init__(self, pd_df_row): # pd_df_row is one row from a dataframe
#initialize some attributes (attribute_A to attribute_Z) in a similar manner
if 'column_A' in pd_df_row.columns:
self.attribute_A = pd_df_row['column_A']
else:
self.attribute_A = np.nan
....
if 'column_Z' in pd_df_row.columns:
self.attribute_Z = pd_df_row['column_Z']
else:
self.attribute_Z = np.nan
# initialize some other attributes based on some other columns in pd_df_row
self.other_attribute = pre_process(pd_df_row['column_123'])
# some other methods
def compute_something(self):
return self.attribute_A + self.attribute_B
Is it advisable to write the class in the below way instead, making use of the setattr method and for loop in python:
class SomeClass():
# create a static list to store the mapping between attribute names and column names that can be initialized using a similar logic.
# However, the mapping would not cover all columns in the input pd_df_row or cover all attributes of the class, because not all columns are read and stored in the same way
# (this mapping will be hardcoded. Its initialization cannot be further simplified using a loop, because the attribute name and the corresponding column name do not actually follow any particular patterns)
ATTR_LIST = [('attribute_A', 'column_A'), ('attribute_B', 'column_B'), ...,('attribute_Z', 'column_Z')]
def __init__(self, pd_df_row): #where pd_df_row is a dataframe
#initialize some attributes (attribute_A to attribute_Z) in a loop
for attr_name, col_name in SomeClass.ATTR_LIST:
if col_name in pd_df_row.columns:
setattr(self, attr_name, pd_df_row[col_name])
else:
setattr(self, attr_name, np.nan)
# initialize some other attributes based on some other columns in pd_df_row
self.other_attribute = pre_process(pd_df_row['column_123'])
# some other methods
def compute_something(self):
return self.attribute_A + self.attribute_B
the second way of writing this class seem to be able to shorten the code. However, it also seem to make the structure of the class a bit confusing, by creating the static list of attribute and column name mapping (which will be used to initiate only some but not all of the attributes). Also, I noticed that code auto-completion will not work for the second piece of code as the code editor wont be able to know what attribute is created until run time. Therefore my question is, is it advisable to use setattr() in this way? In what cases should I write my code in this way and in what cases I should avoid doing so?
In addition, does creating the static mapping in the class violate object oriented programming principles? should I create and store this mapping in some other place instead?
Thank you.
You could, but I would consider having a dict of attributes rather than separate similarly named attributes.
class SomeClass():
def __init__(self, pd_df_row): # pd_df_row is one row from a dataframe
self.attributes = {}
for x in ['A', ..., 'Z']:
column = f'column_{x}'
if column in pd_df_row:
self.attributes[x] = pd_df_row[column]
else:
self.attributes[x] = np.nan
# initialize some other attributes
self.other_attribute = some_other_values
# some other methods
def compute_something(self):
return self.attribute['A'] + self.attribute['B']
I'm trying to create some simple objects that are defined dynamically through a class - to allow me to rapidly iterate through the creation of all possibilities of these objects.
class NSObjects:
def __init__(self, shape, position, shading):
self.shape = shape
self.position = position
self.shading = shading
def __str__(self):
return '{} - {} - {}'.format(self.shape(), self.position(), self.shading())
def NSGenerator_1():
for i in range (0,3):
obj_1_i = NSObjects(shape_init_top + i, posn_init_top+i, shading_init_top+i)
for i in range (3,6):
obj_1_i = NSObjects(shape_init_mid + i, posn_init_mid+i, shading_init_mid+i)
for i in range (6,9):
obj_1_i = NSObjects(shape_init_mid + i, posn_init_mid+i, shading_init_mid+i)
NSGenerator_1()
print(obj_1_2)
At the moment it is telling me that obj_1_2 doesn't exist. For the purpose of this you can assume that I have defined all the init variables to start at 0, 1 or 2 elsewhere in the code. I am basically trying to create a series of objects which will have properties as defined by a mathematical formula.
Thanks in advance for any help you can provide (I only started coding a few weeks ago so this might be a very silly question!)
You only ever assigned to obj_1_i, not obj_1_2, and it was local to the function. There is no way for Python to tell that the _i was meant as a separate variable instead of part of the longer variable name. For a quick fix, try replacing the
obj_1_i = parts with globals()[f'obj_1_{i}'] =.
But rolling numeric indexes into the variable names like that (_1_2) is a code smell. A better design is to actually use them as indexes to a data structure, like a list or dict.
For example, define
obj = {} at the top level (outside of any class or function).
Then you can replace obj_1_2 everywhere with obj[1, 2], etc. If you wrote them that way,obj[1, i] would work as you expect inside those for loops.
I have a class where I want to initialize an attribute self.listN and an add_to_listN method for each element of a list, e.g. from attrs = ['list1', 'list2'] I want list1 and list2 to be initialized as empty lists and the methods add_to_list1 and add_to_list2 to be created. Each add_to_listN method should take two parameters, say value and unit, and append a tuple (value, unit) to the corresponding listN.
The class should therefore look like this in the end:
class Foo():
def __init__(self):
self.list1 = []
self.list1 = []
def add_to_list1(value, unit):
self.list1.append((value, unit))
def add_to_list2(value, unit):
self.list2.append((value, unit))
Leaving aside all the checks and the rest of the class, I came up with this:
class Foo():
def __init__(self):
for attr in ['list1', 'list2']:
setattr(self, attr, [])
setattr(self, 'add_to_%s' % attr, self._simple_add(attr))
def _simple_add(self, attr):
def method(value, unit=None):
getattr(self, attr).append((value, unit))
return method
I also checked other solutions such as the ones suggested here and I would like to do it "right", so my questions are:
Are/Should these methods (be) actually classmethods or not?
Is there a cost in creating the methods in __init__, and in this case is there an alternative?
Where is the best place to run the for loop and add these methods? Within the class definition? Out of it?
Is the use of metaclasses recommended in this case?
Update
Although Benjamin Hodgson makes some good points, I'm not asking for a (perhaps better) alternative way to do this but for the best way to use the tools that I mentioned. I'm using a simplified example in order not to focus on the details.
To further clarify my questions: the add_to_listN methods are meant to be additional, not to replace setters/getters (so I still want to be able to do l1 = f.list1 and f.list1 = [] with f = Foo()).
You are making a design error. You could override __getattr__, parse the attribute name, and return a closure which does what you want, but it's strange to dynamically generate methods, and strange code is bad code. There are often situations where you need to do it, but this is not one of them.
Instead of generating n methods which each do the same thing to one of n objects, why not just write one method which is parameterised by n? Something roughly like this:
class Foo:
def __init__(self):
self.lists = [
[],
[]
]
def add(self, row, value):
self.lists[row].append(value)
Then foo.add1(x) becomes simply foo.add(1, x); foo.add2(x) becomes foo.add(2, x), and so on. There's one method, parameterised along the axis of variation, which serves all cases - rather than a litany of ad-hoc generated methods. It's much simpler.
Don't mix up the data in your system with the names of the data in your system.
I'm trying to create a way to apply a prefix to an item which would modify the item's existing stats. For example in the code below I am trying to apply the 'huge' prefix to the 'jar' item. I'd like to make the code reusable so that I could have different prefixes ('fast', 'healthy') that would modify different item stats.
Is it possible to hold the name of a class member in a variable?
If so, is there any reason I shouldn't?
If not, what alternatives are there?
class Prefix(object):
def __init__(self, word, stat, valu):
self.word = word
self.stat = stat
self.valu = valu
class Item(object):
def __init__(self, name, size):
self.name = name
self.size = size
def apply_prefix(self, prefix):
self.prefix.stat += prefix.valu # <-- Here is my issue
self.name = prefix.word + ' ' + self.name
# My hope is to make the code reusable for any stat
def print_stats(self):
print self.name, self.size
def main():
jar = Item('jar', 10)
huge_prefix = Prefix('huge', 'size', 5)
jar.apply_prefix(huge_prefix)
jar.print_stats()
You're trying to dynamically refer to some attribute. You do that by using getattr. And if you want to set the attribute, well... that's setattr :)
def apply_prefix(self, prefix):
target_attr = getattr(self,prefix.stat) #dynamically gets attr
setattr(self,prefix.stat,target_attr+prefix.valu)
As to whether this is the best coding style: it depends. There are some instances that code is made more clear by use of getattr. Since right now you only have two stats, it seems excessive to need this kind of dynamic attribute referencing, since I could easily do:
bogus_prefix = Prefix('huge','bogus',3)
Which is a valid Prefix, but throws an AttributeError when I try to apply it. That's not the most straightforward thing to debug.
However, there are bonuses to the getattr approach: if you add more stats, you don't have to change a bit (haha) of code in Prefix.
Other alternatives? There are always options in Python. :-)
The way I'd do it is to make Prefix just a dict of word:value pairs. Then apply_prefix would loop over the word keys, updating as many values as I wanted in one shot. It's a similarly dynamic approach, but a bit more scalable.
I want two objects to share a single string object. How do I pass the string object from the first to the second such that any changes applied by one will be visible to the other? I am guessing that I would have to wrap the string in a sort of buffer object and do all sorts of complexity to get it to work.
However, I have a tendency to overthink problems, so undoubtedly there is an easier way. Or maybe sharing the string is the wrong way to go? Keep in mind that I want both objects to be able to edit the string. Any ideas?
Here is an example of a solution I could use:
class Buffer(object):
def __init__(self):
self.data = ""
def assign(self, value):
self.data = str(value)
def __getattr__(self, name):
return getattr(self.data, name)
class Descriptor(object):
def __get__(self, instance, owner):
return instance._buffer.data
def __set__(self, instance, value):
if not hasattr(instance, "_buffer"):
if isinstance(value, Buffer):
instance._buffer = value
return
instance._buffer = Buffer()
instance._buffer.assign(value)
class First(object):
data = Descriptor()
def __init__(self, data):
self.data = data
def read(self, size=-1):
if size < 0:
size = len(self.data)
data = self.data[:size]
self.data = self.data[size:]
return data
class Second(object):
data = Descriptor()
def __init__(self, data):
self.data = data
def add(self, newdata):
self.data += newdata
def reset(self):
self.data = ""
def spawn(self):
return First(self._buffer)
s = Second("stuff")
f = s.spawn()
f.data == s.data
#True
f.read(2)
#"st"
f.data
# "uff"
f.data == s.data
#True
s.data
#"uff"
s._buffer == f._buffer
#True
Again, this seems like absolute overkill for what seems like a simple problem. As well, it requires the use of the Buffer class, a descriptor, and the descriptor's impositional _buffer variable.
An alternative is to put one of the objects in charge of the string and then have it expose an interface for making changes to the string. Simpler, but not quite the same effect.
I want two objects to share a single
string object.
They will, if you simply pass the string -- Python doesn't copy unless you tell it to copy.
How do I pass the string object from
the first to the second such that any
changes applied by one will be visible
to the other?
There can never be any change made to a string object (it's immutable!), so your requirement is trivially met (since a false precondition implies anything).
I am guessing that I would have to
wrap the string in a sort of buffer
object and do all sorts of complexity
to get it to work.
You could use (assuming this is Python 2 and you want a string of bytes) an array.array with a typecode of c. Arrays are mutable, so you can indeed alter them (with mutating methods -- and some operators, which are a special case of methods since they invoke special methods on the object). They don't have the myriad non-mutating methods of strings, so, if you need those, you'll indeed need a simple wrapper (delegating said methods to the str(...) of the array that the wrapper also holds).
It doesn't seem there should be any special complexity, unless of course you want to do something truly weird as you seem to given your example code (have an assignment, i.e., a *rebinding of a name, magically affect a different name -- that has absolutely nothing to do with whatever object was previously bound to the name you're rebinding, nor does it change that object in any way -- the only object it "changes" is the one holding the attribute, so it's obvious that you need descriptors or other magic on said object).
You appear to come from some language where variables (and particularly strings) are "containers of data" (like C, Fortran, or C++). In Python (like, say, in Java), names (the preferred way to call what others call "variables") always just refer to objects, they don't contain anything except exactly such a reference. Some objects can be changed, some can't, but that has absolutely nothing to do with the assignment statement (see note 1) (which doesn't change objects: it rebinds names).
(note 1): except of course that rebinding an attribute or item does alter the object that "contains" that item or attribute -- objects can and do contain, it's names that don't.
Just put your value to be shared in a list, and assign the list to both objects.
class A(object):
def __init__(self, strcontainer):
self.strcontainer = strcontainer
def upcase(self):
self.strcontainer[0] = self.strcontainer[0].upper()
def __str__(self):
return self.strcontainer[0]
# create a string, inside a shareable list
shared = ['Hello, World!']
x = A(shared)
y = A(shared)
# both objects have the same list
print id(x.strcontainer)
print id(y.strcontainer)
# change value in x
x.upcase()
# show how value is changed in both x and y
print str(x)
print str(y)
Prints:
10534024
10534024
HELLO, WORLD!
HELLO, WORLD!
i am not a great expert in python, but i think that if you declare a variable in a module and add a getter/setter to the module for this variable you will be able to share it this way.