I have been a Python Scientific Programmer for a few years now, and I find myself coming to a sort specific problem as my programs get larger and larger. I am self taught so I have never had any formal training and spent any time really on 'conventions' of coding in Python "properly".
Anyways, to the point, I find myself always creating a utils.py file that I store all my defined functions in that my programs use. I then find myself grouping these functions into their respective purposes. One way of I know of grouping things is of course using Classes, but I am unsure as to whether my strategy goes against what classes should actually be used for.
Say I have a bunch of functions that do roughly the same thing like this:
def add(a,b): return a + b def sub(a,b): return a -b def cap(string): return string.title() def lower(string): return string.lower()
Now obviously these 4 functions can be seen as doing two seperate purposes one is calculation and the other is formatting. This is what logic tells me to do, but I have to work around it since I don't want to initialise a variable that corresponds to the class evertime.
class calc_funcs(object): def __init__(self): pass @staticmethod def add(a,b): return a + b @staticmethod def sub(a, b): return a - b class format_funcs(object): def __init__(self): pass @staticmethod def cap(string): return string.title() @staticmethod def lower(string): return string.lower()
This way I have now 'grouped' these methods together into a nice package that makes finding desired methods much faster based on their role in the program.
print calc_funcs.add(1,2) print format_funcs.lower("Hello Bob")
However that being said, I feel this is a very 'unpython-y' way to do things, and it just feels messy. Am I going about thinking this the right way or is there an alternate method?
Pandas groupby is used for grouping the data according to the categories and apply a function to the categories. It also helps to aggregate data efficiently. Pandas dataframe.groupby() function is used to split the data into groups based on some criteria. pandas objects can be split on any of their axes.
A pretty useful technique for simulating multiple constructors in a Python class is to provide . __init__() with optional arguments using default argument values. This way, you can call the class constructor in different ways and get a different behavior each time.
Classes provide a means of bundling data and functionality together. Creating a new class creates a new type of object, allowing new instances of that type to be made. Each class instance can have attributes attached to it for maintaining its state.
The __init__ method lets the class initialize the object's attributes and serves no other purpose. It is only used within classes.
Another approach is to make a util
package and split up your functions into different modules within that package. The basics of packages: make a directory (whose name will be the package name) and put a special file in it, the __init__.py
file. This can contain code, but for the basic package organization, it can be an empty file.
my_package/ __init__.py module1.py/ modle2.py/ ... module3.py
So say you are in your working directory:
mkdir util touch util/__init__.py
Then inside your util
directory, make calc_funcs.py
def add(a,b): return a + b def sub(a,b): return a -b
And format_funcs.py
:
def cap(string): return string.title() def lower(string): return string.lower()
And now, from your working directory, you can do things like the following:
>>> from util import calc_funcs >>> calc_funcs.add(1,3) 4 >>> from util.format_funcs import cap >>> cap("the quick brown fox jumped over the lazy dog") 'The Quick Brown Fox Jumped Over The Lazy Dog'
Notice, though, if we restart the interpreter session:
>>> import util >>> util.format_funcs.cap("i should've been a book") Traceback (most recent call last): File "<stdin>", line 1, in <module> AttributeError: module 'util' has no attribute 'format_funcs'
This is what the __init__.py
is for!
In __init__.py
, add the following:
import util.calc_funcs, util.format_funcs
Now, restart the interpreter again:
>>> import util >>> util.calc_funcs.add('1','2') '12' >>> util.format_funcs.lower("I DON'T KNOW WHAT I'M YELLING ABOUT") "i don't know what i'm yelling about"
Yay! We have flexible control over our namespaces with easy importing! Basically, the __init__.py
plays an analogous role to the __init__
method in a class definition.
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