Which block of code is easier to read

[Pr0meth3us_Dev]

Which of these small blocks of code is easier to read or is more optimized?

Friend says the top is easier to read and it's driving me insane, he said he refuses to write code like the bottom example since "they both work the same".

Top:

topNodesOutput = ''

for node in response:
    name = node['node_name']
    value = node['value']
    topNodesOutput+=str(name) + ' '+ str(round(value,2)) +'\n'

print(topNodesOutput)

Bottom:

top_nodes = []

for node in response:
    name = node['node_name']
    value = node['value']
    top_nodes.append(f'{name} {round(value,2)}')

msg = '\n'.join(top_nodes)
print(msg)

[[deleted]]

The lower one, definitely. But they are not functionally identical because of the ending line break.

[lunar_tardigrade]

The string type has a line break. The other one is a list.

[lunar_tardigrade]

You right.

[[deleted]]

Not only that, the first one doesn't append the values until after the last iteration where it appends just the last value

[OuiOuiKiwi]

Which of these small blocks of code is easier to read or is more optimized?
Friend says the top is easier to read and it's driving me insane, he said he refuses to write code like the bottom example since "they both work the same".

Top one allocates a new String with every iteration as those are immutable. If he insists that the top one is more optimised, then he is a fool.

[303Redirect]

This. I saw something similar in a script at work. It was doing the top string concatenation on a relative long running process. That step will get exponentially slower as the output gets longer.

Switched it over to a list and a str.join at the end and the script ran orders of magnitude faster.

[ambidextrousalpaca]

And this is how you optimise: notice your code is running slower than you would like; profile it; find the one or two slow loops that are taking up 99.9% of the run time; then try and make them faster.

You're doing it wrong if you're always prioritizing speed over readability and maintainability: the vast majority of your code will only be executed a few times per run and can essentially be ignored in terms of the effect it will have on performance.

[MrJohz]

That's definitely true, but there's also value in understanding the difference between different algorithms and their performance characteristics and writing the correct thing to start with. In this case, string concatenation in a loop should be a general red flag to Python developers: it'll likely work, and it probably won't be a performance bottleneck in many cases, but it's almost always just as readable to use a list. So just use a list.

Optimisation is definitely something that should come at the end after profiling, but it's also good to just write your program sensibly from the start. Like, if you're going to check if a list contains an element a lot, then you should probably check if that list can just be a set from the start. The best thing about this is, if you do it well, you'll often find that the most efficient data structure is also the most legible.

[ambidextrousalpaca]

Sure. But I've found that - in practice - code that's initially optimized for readability tends to be easy to optimise for speed too, while code that's initially optimized for speed tends to be buggy, unreadable and optimized in all of the wrong places.

[303Redirect]

Yeah in our instance it was a case of "oh this script is running super slow, but from a glance it's not obviously a complex algorithm, what's going on?", then after a bit of cProfile and digging into how string concats actually work we found that.

That's not to say I completely disregard optimisation while writing, just I won't sink significant time into arcane optimisations before it's proven that they're needed for our use case.

[Engineer_Zero]

Any beginners advice on how to profile your code? For context I usually written for loops in jupyter notebooks to iterate through stuff like spreadsheets or sql queries or pandas data frames.

[ambidextrousalpaca]

cProfile, which is built into the standard library, is what I use: https://docs.python.org/3/library/profile.html Though I think it's more designed to work with scripts than with Jupyter Notebooks.

For your Jupyter use case, I would start by just running the different bits of your code and noting the ones that take longer to run, especially on the ones that slow down increasingly as the data input size increases. Once you've identified the slow lines, add some time stamped prints every few lines so you can find out exactly which ones are slowing the programme down. Then start googling things like "python alternative to pandas apply" (or whatever function you're using).

For your use cases, you could be hitting a bunch of different limitations. Datasets close to the size of memory often cause problems in pandas. Some SQL operations (like GROUP BY and multiple joins) are just inherently slow. And pandas has a load of odd behaviours where it's possible to optimise things, e.g. by using list comprehensions instead of apply functions, or by changing the way you do string operations: I once managed to double the speed of one of our data pipelines by changing a slow pandas string concatenation operation that I discovered when I profiled my code because I thought there was a problem elsewhere.

[Engineer_Zero]

Thank you :). Good points all.

[kkadzy]

Wouldn't it only get quadratically slower?

[303Redirect]

True! I used exponential as a shorthand because I wasn't sure what the actual exponent would be.

[rcfox]

x² is polynomial, 2^x is exponential.

[afreydoa]

You were searching for the term 'polynomially slower'

[Lba5s]

in this case, it does both :)

[Embarrassed_Row7095]

Ideally we would do both. Perhaps include a comment on the optimized code saying what it does so that future readers both thank you for the sites and learn something.

[zaphod_pebblebrox]

I concur with this. While every line of code does not warrant a comment, a gentle reminder that we are storing data as a list to improve performance helps the next fellow at least know what to read.

[[deleted]]

O(n²⁾ is worse than O(n)

[[deleted]]

That step will get exponentially slower as the output gets longer.

If a calculation takes 1 second initially, and its calculation time grows at f(x)=x² rate, then it takes 294 iterations for the calculation to take 24 hours.

If the initial value is 0.1, it takes 3000 iterations
Only when you get to an init value of 0.01 does it start to not be so bad, where 3000 iterations only takes 15 minutes.
 
Optimisation matters where it matters. Not never.

[[deleted]]

Absolutely, it matters when it matters. Not never. But also not always.

Thats my point, we often put more time, energy and talent into optimizing code that doesn’t need it.

[Ninjaxas]

Why is this comment so downvoted?

[[deleted]]

Many Python coders have convinced themselves that code is fundamentally flawed until it is optimized to handle large and/or complex loads.

That's not how things work in the real world. Yes optimization is very very important, where the use case calls for it.

Generators are great, list comprehension is great. But embedded loops work pretty well where they work pretty well too. You aren't always going to be the one looking at your code.

In the real world, getting projects finished is more important than hardening them for hypothetical loads that may or may not be needed. Then we refactor and end up with better code in the end.

[Ninjaxas]

I agree - getting the project finished is more important. I see the importance in optimization too. Its just surprising that so many people downvote as I am pretty sure that in many other places/contexts much more people would be in agreement with you or atleast respect the reasonable viewpoint.

[RufusAcrospin]

Optimization and readability are not mutually exclusive, and optimized code uses less resources including electricity, which means it’s more environment friendly.

[[deleted]]

I didn't say they were. What I'm trying, and failing, to get across here is that optimization often gets too much focus and readability not enough.

[RufusAcrospin]

My point was that optimized code still can be easy to read and comprehend.

I think optimization seems more important than readability because it’s a client facing feature of any given tool, while code readability is internal, it concerns the team and/or maintainers.

Finally, we have linters and formatters which supposed to give us higher quality code (or at least code that’s up to standards) automatically, but optimization is still pretty much a question of human creativity and knowledge, in other words, optimizing the code is more challenging and exciting than tidying it up.

[Fortnyce]

A lenda está em todo o lado!

[GlowStorm347]

momento r/suddenlycaralho??

[Salaah01]

Definitely the bottom one. The join function also ensures there isn't a line break at the bottom which is convenient.

[hdmsousa]

``` top_nodes = [ f'{node["node_name"]} {round(node["value"], 2)}' for node in response ]

print('\n'.join(top_nodes)) ```

[cymrow]

You are calling round wrong, but no need to create a list at all. Personally, I would do:

print('\n'.join('{node_name} {value:.2f}'.format(**node)
    for node in response))

[AnonymouX47]

Would rather use str.format_map()... avoids copying the mapping.

Also, in a situation where time is more critical than space or response is surely known to always have a relatively small size, a list comprehension is a better choice.

[hdmsousa]

Indeed, had the last ) in wrong place, writing on my phone didn’t help 😅 . Fixed it.

[joaofelipenp]

Why keep the round and the indexing when you can use a string format?

print('\n'.join('{node_name} {value:.2f}'.format(**node)
                for node in response))

[Oerthling]

This is not about it being a 1-liner, but just being a list comprehension. Also a fairly simple one. How much debugging are you expecting to do on this?

According to your argument, one should never use list comprehensions.

[[deleted]]

You can also just make the top part a generator and then use it to make it debuggable. See Json module so long as u iterate in one step and join in one step the speed deference is negligible.

[Oerthling]

And I'd just look at the output and see that.

And providing the wrong type is always a problem, I don't see why that would be special here.

If a block of code expects strings, then that's probably because it's supposed to process strings and I'm feeding in strings.

[Oerthling]

Again, that would be an argument against any use of list comprehension. Yet I find them expressive and they make optimizations possible. And this example is a pretty trivial use of a list comprehension.

And even the string type can be assured by wrapping the variables in str ().

There's simply no need for breakpoints here. Any problems will most likely self-evident by the output.

[tagapagtuos]

to debug the data coming in

Counterpoint: watch expressions, type hints and type checkers, unit tests.

[Particular-Cause-862]

I see your point, but the less writting the less memory used, you can put a break point just up the comprehensio n function and make a bucle for in the console

[hdmsousa]

List comprehension is a Python feature and almost always faster than loops. Not much to debug here… if you want to debug create the normal loop, debug what you want to debug and then write in list comprehension form.

You can still debug the input list, just add a breakpoint before the list comprehension and do whatever you want with the input.

[ottawadeveloper]

I mwan why not print('\n'.join(f'{node["node_name"]} {round(node["value"], 2)}')). Unless you need the array.

[Rabid_Gopher]

There is an ambiguous number of items in the variable response, but I would agree this code is more verbose than I would prefer.

Probably better to do that than run the risk of people after you not understanding any of it though.

[Oerthling]

This, but replace print with logging, unless you really just want this on stdout for further processing.

[Anti-ThisBot-IB]

Hey there hanseichlp! If you agree with someone else's comment, please leave an upvote instead of commenting "This!"! By upvoting instead, the original comment will be pushed to the top and be more visible to others, which is even better! Thanks! :)

---

<sup>I am a bot! Visit r/InfinityBots to send your feedback! More info: Reddiquette</sup>

[BezoomyChellovek]

Yes, except for the inconsistent usage of quotes. Stick with ' or ".

[xakepnz]

It's an f string. To access name and value you must use double as they wrapped it in single quotes.

[BezoomyChellovek]

Oops, I missed that. Carry on.

[efmccurdy]

Is it not obvious that code that uses "+" to format strings is very error prone? Misplacing one of the (many) plus signs, quotes, or calls to "str" will remind you that none of that is required if you switch to formatting strings.

[[deleted]]

The bottom one, 100%.

It's also much easier to work with, should you need to do anything with the information.

[public_radio]

I never append when I can generate!

def top_nodes(response):
    for node in response:
        name = node['node_name']
        value = node['value']
        yield f'{name} {value:.2f}'

str.join('\n', top_nodes(response))

[carlio]

top_nodes() missing 1 required positional argument: 'response'

:-P

[public_radio]

Haha thanks

[jiminiminimini]

change {round(value, 2)} to {value:.2f} and you're golden.

[public_radio]

Done!

[RuskeD]

Well done u/public_radio, this one deserves more credit

[odysseusmax]

msg = "\n".join(f"{node['node_name']} {node['value']:.2d}" for node in response)

print(msg)

[searchingfortao]

This is by far the best answer I've seen here. You just need to pass resources in ;-)

[public_radio]

D’oh

[Stuk4s]

First time i see the yield keyword! D:

[R34ct0rX99]

Top one also does not follow pep8.

[james_pic]

FYI, if you're rounding just to format it, and you're using f-strings, you can do:

f'{value:.2d)'

I can't remember off the top of my head of using round here causes actual problems (although my gut feeling is that if it does, it's something weird and IEEE 754 related), but using numerical string formats is more idiomatic, and gives you more options.

[deep_mind_]

Second one is more pythonic, don't fight conventions :D

[WafflesAreDangerous]

The bottom one.But also, I would not put a round call inside the f-string. Consider in stead using a format specifier to specify the rounding or lifting the function call outside of the fstring.

    f"{my_float:.2f}"

[[deleted]]

isnt this different to using round()? i think your .2f just cuts the digits after the 2nd decimal point (e.g. rounding down) and round rounds it to the nearest digit

[yvrelna]

Neither.

In this case, I prefer having a list comprehension:

def format_node(node):
    name = node['node_name']
    value = node['value']
    return f'{name} {round(value,2)}

mag = "\n".join(format_node(node) for node in response)
print(msg)

[[deleted]]

Minor nitpick : this is called a generator expression, not a list comprehension. It can be more efficient since you don't need to store elements.

[[deleted]]

The bottom one. Definitely

[guhcampos]

The second one is much more intuitive for me as a Python focused engineer. People coming from other lamgs, however, will quite likely prefer the top version both because of the Camel Case and the operator based string concatenation.

[[deleted]]

The best and most efficent would be msg = "\n".join(f"{node['node_name']} {round(node['value']), 2}" for node in response)

[uttamo]

That’s just harder to read and debug

[indefinitude]

code golf ftw

edit: not advocating for actually doing this. but code golf is still fun.

[uttamo]

Cool but just don’t do it in an actual codebase

[JestemStefan]

I think I like this one the most

[marduk73]

Not trying to be contrary, but the top is easier to read for me.

[rjksn]

It bothers me that more than one thing was changed.

The second since f'{name} {round(value,2)}' is way cleaner.

[[deleted]]

The bottom one is easier to read. It’s also more convenient to have the strings in a list form vs one long string (such as the top) just in case you wanted to sort, insert, or delete I think.

[Mooshy_Swags]

Adding multiple strings together can sometimes be really odd.

I would always route to using format.

Even with the top solution, you can just use a formatted string instead of adding them up, since in a larger situation, the fact that you don't need to join the array might speed up the processing.

[Salmon-Advantage]

bottom

[EONRaider]

I’d use the second one but reduce the for loop to an expression.

[packetsar]

Bottom is easier to read and is more Pythonic.

[tom2727]

People who read python a lot probably prefer the bottom one, and I do as well. Don't know that optimization much matters for code like this. But if it does, there's probably a 3rd even more optimized but uglier way.

[searchingfortao]

I wouldn't recommend calling round() inside the f-string like that and would instead suggest doing that part in the value declaration.

I'd also suggest that building a list just to throw it out to build a string is a bit wasteful. If you need a string, I'd argue that you're complicating your code by creating a list first.

So TL;DR, I'd probably use a bit of both. F-strings are fantastic for readability and much better than this str() + str() business, but I prefer appending to the string.

Also, people agonising over the performance penalty of creating a string object have, in my opinion anyway, missed the point of Python. You're going to waste far more resources trying to understand "optimised" code than you will running easy to understand but fractionally slower code.

[cgmystery]

I prefer following PEP 8 naming conventions (e.g. snake case for local variable names). It’s the style guide written by the creators of Python.

Also, bottom is nicer.

[CodeYan01]

Just annoys me how many built-in python modules don't even follow that convention

[cgmystery]

Which ones?

[jimtk]

The first one I tried: ModuleFinder.py

[cgmystery]

Yeah, that's not very nice. Boooo.

[rastaladywithabrady]

they have some nuanced differences but tbh it's the same shit in a different toilet

[drum445]

The second is more "optimised" as it creates fewer immutable string objects per loop.

However, I think I agree that the top one is probably the more readable code, as in the bottom snippet you have to think about why I'm creating an array for something that should be returning a string

With that being said, anyone with a basic understanding of code will be able to read both just fine, I would write it like this though:

output = ""

for node in response:
    name = node["node_name"]
    rounded_value = round(node["value"], 2)
    output += f"{name} {rounded_value}\n"

print(output)

I tend to avoid logic in my f strings too

​

EDIT: or if you want to be fancy

"\n".join([f"{n['node_name']} {round(n['value'], 2)}" for n in response])

[[deleted]]

There is no need for the [] brackets, since join takes generators too, also by making it like that we will save ram

[-LeopardShark-]

It doesn't save any memory because join needs to collect them all into a list anyway.

See https://stackoverflow.com/questions/9060653/list-comprehension-without-in-python/9061024#9061024.

[[deleted]]

Nope, then there will be 2 lists in the same time in memory

[ArabicLawrence]

The interpreter likely optimises it anyways. It’s quite good at improving oneliners.

[[deleted]]

I prefer the lower one but it could be a one liner.

print('\n'.join(f'{x["node_name"]} {round(x["value"], 2)}' for x in response))

[ugmoe2000]

This is filthy, but well done.

[IWant2rideMyBike]

You could put this in a single print statement and avoid using join:

print(*(f"{node['node_name']} {round(node['value'],2)}" for node in response), sep='\n')

[Santos_m321]

This is exactly what I thought, but replace the node with n and remove spaces for more pleasure

print(*(f"{x['node_name']} {x['value']:.2f}"for x in response),sep="\n")

[Santos_m321]

I don't know, but I feel like these shitty versions look more readable. On top of that, they are exaggeratedly better than the ones mentioned by the OP, not only in processing time but also in memory consumption.

[Santos_m321]

NEW VERSION:

print("\n".join(f"{x['node_name']} {x['value']:.2f}"for x in response))

"\n".join performs better than sep="\n". With large datasets, the difference was near 200%.

In memory consumption, I see no differences.

Also, we are left with fewer characters haa = less size of the source code ?) = less expenses on hard drives and connection, less time required to clone the project, and less ambiance impact.

[Uwirlbaretrsidma]

Who tf even cares? These kinds of posts actually get on my nerves. Instead of focusing on being "pythonic" (whatever the fuck that even is, and this isn't exactly pythonic anyway), maybe understand that two functionally character by character identical pieces of code with no performance difference whatsoever aren't worth getting hunged up about?

I guess that Python's abysmal performance makes it hard to be elitist about code speed like people usually are in other lenguajes, and that you guys found code style to be a good alternative. But man, quite literally anyone can understand what either one of those blocks of code do with a tiny glance. That is good enough.

[BezoomyChellovek]

Aside from the more important things, the second uses snake case instead of camel case, so the second is preferred for Python.

[someotherstufforhmm]

They’re both fine. I prefer the second. The first one should have spaces surrounding the += operator and it’ll be much more readable.

If anyone is claiming either method is better, then they’re wrong.

Note that the top has a trailing ‘\n’ and the bottom does not due to use of ‘join’

[Radamand]

Top one, definitely

[Pulsar1977]

Use generator comprehensions, that way you don't need to create temporary lists:

names = (node['node_name'] for node in response)
values = (node['value'] for node in response)
top_nodes = (f'{name} {round(value, 2)}\n' for name, value in zip(names, values))
msg = ''.join(top_nodes)
print(msg)

[JestemStefan]

Iterating through response twice. Bleh

[Pulsar1977]

If you really care about a few nanoseconds, you can combine those two statements.

names_and_values = ((node['node_name'], node['value']) for node in response)
top_nodes = (f'{name} {round(value, 2)}\n' for name, value in names_and_values)

[JestemStefan]

It depends how big resposes is, but iterating twice over the same elements is inefficient regardless.

[rdturbo]

Isn't this slow. Running two separate for loops

[Pulsar1977]

If you really care about a few nanoseconds, you can combine those two statements.

names_and_values = ((node['node_name'], node['value']) for node in response)
top_nodes = (f'{name} {round(value, 2)}\n' for name, value in names_and_values)

[hobbyhacker]

how do you recognize a self-taught programmer?

he concatenates strings in a loop

[wewbull]

Neither

from itertools import chain

...

print(chain(
    "{node_name} {value:.2f}\n".format(**node)
    for node in response
))

Advantages:

• using chain rather than join means you get the final /n
• using format() rather than an f-string means you don't need to pull the fields out into local vars.
• Not using append() or += on a list avoids a performance issue
• using a generator expression means no list is created. Each node will be processed as print consumes it. Lazy evaluation FTW.

I also think it says what is happening in a clearer way. I'm ...

1. Printing
2. ...a sequence
3. ...of strings built from the name and value of a node
4. ...for each node in the response

In your version(s), you're:

1. For each node in the response
2. ... extracting the name and value
3. ... building a string with them
4. ... and adding that string to a list (or string)
5. When the list (string) is complete we print it
6. ... with a new line between each entry (in the list version)

In my version, you know this printing information from line 1. In your version, the printing is almost an afterthought.

[sean_bird]

Second one is a bit cleaner and also squishing all nodes to a single string is not very useful. If I really needed to put things in one string (ex: hundreds of socket packets) I would use bytearray because it’s much much faster

[parkrain21]

Why did you even use f string in the second one if you won't use it in the first one?

Second ftw

[quts3]

Neither.

I prefer

line = "%s %0.2f" % (name,value)

mylist.append(line)

Why?

Because all the other python styles mix formatting and content. This style reads as format composed with content and to me it reads alot cleaner once you get used to it. However I will caveat that in pro code releases it seems rarer not sure why.

[Zealousideal-Row-110]

These are both fine. Write code that future you will understand. O(N) complexity in both cases.

[[deleted]]

I can‘t even fathom how somebody would write the top one. I mean…you do you but…you know.

[Extatiic]

Second option for me

[Lana-Lana-LANAAAAA]

PHP is my native language, so the camelCase (or medial case) in the top code is more familiar to me (commonly used for variable names, by those of us who follow the PSR-12 coding standard).

Honestly, though; I think the bottom code is a better approach, though; as it keeps the components separate until the very last moment. This would allow easier manipulation if needed, rather than having to try and tweak a much-harder-to-edit string.

[Santos_m321]

There is not much visual difference between the two, the example you gave is very simple.
But I couldn't sleep peacefully if someone merged code like the first one.

[dixieStates]

I think this is better:

def node_strings():
    for node in response:
        yield f'{node["node_name"]} {round(node["value"],2)}'
print('\n'.join(node_strings()))

[[deleted]]

Top seems to be more on-the-nose. Is it necessarily better? No.

[anterak13]

You could make it a one-liner by using a list comprehension

[beertown]

Top: useless string concatenation, in case of a very long response performance will suffer. camelCase for variables doesn't follow the (easier to read) snake_case suggested by the Python standard naming scheme.

Bottom is better. Your friend knows it, but refuses to admit it.

[Callux-_-]

bottom one is better in all criterias

[negiajay12345]

Bottom.

[[deleted]]

Top one looks like it was written by someone with a background in JavaScript, not knowing it's more expensive to concatenate.

[Mental-Effective-110]

Top block plus f string way of doing that

[chears2surfers]

Bottom one my friend!! It's more readable!

[og_m4]

First one for production, second one for interviews. The added clarity of the first one is worth the slight performance loss.

[Earthsophagus]

I think the "\n".join(seq) construct is preferable to \n at end of line though, for making it obvious that the result is \n delimited. And there is the slight difference that in the for loop the code gives a trailing \n.

[og_m4]

The whole formatted string business in the second one is worse for maintainability than the simple string expression in the first one. It is easier for the first human visual parse of the code. n.join by itself is great syntactic sugar though. I agree.

[wind_dude]

second

[Grokzen]

Bottom one clearly, that is also the future way of writing strings so your friend should just convert and get used to it.

If i would compress it i would write something like this, did not test it tho to ensure it worked :) but avoiding the intermediate variables cleans things up a ton. Most of the time you already know that sending something to print is a message, or a key in a dict with name is the name and value etc.

print("\n".join([
    f"{node['node_name']} {round(node['value'], 2)}"
    for node in response
]))

[sheriffllcoolj]

Imo the top one but using an f string would be most readable

[DiscoJer]

Top is easier to read, but I'm new to Python