[Numpy-discussion] Style guide for numpy code?

Joe Harrington jh at physics.ucf.edu
Thu May 9 14:12:28 EDT 2019

I have a handout for my PHZ 3150 Introduction to Numerical Computing 
course that includes some rules:

(a) All integer-valued floating-point numbers should have decimal points 
after them. For
example, if you have a time of 10 sec, do not use

y = np.e**10 # sec


y = np.e**10. # sec

instead.  For example, an item count is always an integer, but a 
distance is always a float.  A decimal in the range (-1,1) must always 
have a zero before the decimal point, for readability:

x = 0.23 # Right!

x = .23 # WRONG

The purpose of this one is simply to build the decimal-point habit.  In 
Python it's less of an issue now, but sometimes code is translated, and 
integer division is still out there.  For that reason, in other 
languages, it may be desirable to use a decimal point even for counts, 
unless integer division is wanted.  Make a comment whenever you intend 
integer division and the language uses the same symbol (/) for both 
kinds of division.

(b) Use spaces around binary operations and relations (=<>+-*/). Put a 
space after “,”.
Do not put space around “=” in keyword arguments, or around “ ** ”.

(c) Do not put plt.show() in your homework file! You may put it in a 
comment if you
like, but it is not necessary. Just save the plot. If you say


plots will automatically show while you are working.

(d) Use:

import matplotlib.pyplot as plt


import matplotlib.pylab as plt

(e) Keep lines to 80 characters, max, except in rare cases that are well 
justified, such as
very long strings. If you make comments on the same line as code, keep 
them short or
break them over more than a line:

code = code2   # set code equal to code2

# Longer comment requiring much more space because
# I'm explaining something complicated.
code = code2

code = code2   # Another way to do a very long comment,
                # like this one, which runs over more than
                # one line.

(f) Keep blocks of similar lines internally lined up on decimals, 
comments, and = signs.  This makes them easier to read and verify.  
There will be some cases when this is impractical.  Use your judgment 
(you're not a computer, you control the computer!):

x    =   1.      # this is a comment
y    = 378.2345  # here's another
fred = chuck     # note how the decimals, = signs, and
                  # comments line up nicely...
alacazamshmazooboloid = 2721 # but not always!

(g) Put the units and sources of all values in comments:

t_planet = 523.     # K, Smith and Jones (2016, ApJ 234, 22)

(h) I don't mean to start a religious war, but I emphasize the alignment 
of similar adjacent code lines to make differences pop out and reduce 
the likelihood of bugs.  For example, it is much easier to verify the 
correctness of:

a     = 3 * x + 3 * 8. *     short    - 5. * np.exp(np.pi * omega * t)
a_alt = 3 * x + 3 * 8. * anotshortvar - 5. * np.exp(np.pi * omega * t)


a = 3 * x + 3 * 8. * short - 5. * np.exp(np.pi * omega * t)
a_altvarname = 3 * x + 3*9*anotshortvar - 5. * np.exp(np.pi * omega * i)

(i) Assign values to meaningful variables, and use them in formulae and 

ny = 512
nx = 512
image = np.zeros((ny, nx))
expr1 = ny * 3
expr2 = nx * 4

Otherwise, later on when you upgrade to 2560x1440 arrays, you won't know 
which of the 512s are in the x direction and which are in the y 
direction.  Or, the student you (now a senior researcher) assign to code 
the upgrade won't!  Also, it reduces bugs arising from the order of 
arguments to functions if the args have meaningful names.  This is not 
to say that you should assign all numbers to functions.  This is fine:

circ = 2 * np.pi * r

(j) All functions assigned for grading must have full docstrings in 
numpy's format, as well as internal comments.  Utility functions not 
requested in the assignment and that the user will never see can have 
reduced docstrings if the functions are simple and obvious, but at least 
give the one-line summary.

(k) If you modify an existing function, you must either make a Git entry 
or, if it is not under revision control, include a Revision History 
section in your docstring and record your name, the date, the version 
number, your email, and the nature of the change you made.

(l) Choose variable names that are meaningful and consistent in style.  
Document your style either at the head of a module or in a separate text 
file for the project.  For example, if you use CamelCaps with initial 
capital, say that.  If you reserve initial capitals for classes, say 
that.  If you use underscores for variable subscripts and camelCaps for 
the base variables, say that.  If you accept some other style and build 
on that, say that.  There are too many good reasons to have such styles 
for only one to be the community standard.  If certain kinds of values 
should get the same variable or base variable, such as fundamental 
constants or things like amplitudes, say that.

(j) It's best if variables that will appear in formulae are short, so 
more terms can fit in one 80 character line.

Overall, having and following a style makes code easier to read. And, as 
an added bonus, if you take care to be consistent, you will write 
slower, view your code more times, and catch more bugs as you write 
them.  Thus, for codes of any significant size, writing pedantically 
commented and aligned code is almost always faster than blast coding, if 
you include debugging time.

Did you catch both bugs in item h?


On 5/9/19 11:25 AM, Chris Barker - NOAA Federal <chris.barker at noaa.gov> 
> Do any of you know of a style guide for computational / numpy code?
> I don't mean code that will go into numpy itself, but rather, users 
> code that uses numpy (and scipy, and...)
> I know about (am a proponent of) PEP8, but it doesn’t address the 
> unique needs of scientific programming.
> This is mostly about variable names. In scientific code, we often want:
> - variable names that match the math notation- so single character 
> names, maybe upper or lower case to mean different things ( in ocean 
> wave mechanics, often “h” is the water depth, and “H” is the wave height)
> -to distinguish between scalar, vector, and matrix values — often 
> UpperCase means an array or matrix, for instance.
> But despite (or because of) these unique needs, a style guide would be 
> really helpful.
> Anyone have one? Or even any notes on what you do yourself?
> Thanks,
> -CHB
>> -- 
>> Christopher Barker, Ph.D.
>> Oceanographer
>> Emergency Response Division
>> NOAA/NOS/OR&R            (206) 526-6959   voice
>> 7600 Sand Point Way NE   (206) 526-6329   fax
>> Seattle, WA  98115       (206) 526-6317   main reception
>> Chris.Barker at noaa.gov <mailto:Chris.Barker at noaa.gov>
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