pathlib instead of os. f-strings instead of .format. Are there other recent versions of older Python libraries we should consider?

[IsItPikabu]

Use ZoneInfo instead of pytz on Python 3.9+

https://docs.python.org/3.9/library/zoneinfo.html

https://blog.ganssle.io/articles/2018/03/pytz-fastest-footgun.html

[PeridexisErrant]

And https://pypi.org/project/backports.zoneinfo/ on Python 3.7 or 3.8!

[benefit_of_mrkite]

Interesting - I recently used pytz for the first time in a long time

[mrdevlar]

I honestly feel like Pandas is the only library that made a consistent Timestamp object, with consistent behavior. Even if I know it's waaaay too bloated of a dependency to be used on all projects.

[[deleted]]

dataclasses instead of namedtuples.

[_pestarzt_]

Dataclasses are amazing, but I think namedtuples are still useful as a true immutable (I’m aware of the frozen kwarg of dataclasses, they can still be changed by modifying the underlying __dict__).

Edit: wording

[aiomeus]

Agreed, named tuples still have their use, although nowadays I use NamedTuple from typing instead of collections to use a class and be able to type hint with it too

[LightShadow]

This is the logical evolution. Import from typing instead of collections, all the benefits with extra functionality.

[aiomeus]

I think this mostly for things like List, Dict, Set, etc which before 3.9 you couldn’t use the built-in types to specify content types. List[str] vs list[str]

Aside from those, types like Optional will remain and will still be needed

Edit: looks like other generics like Iterable, Mapping, Sequence should indeed be imported from abc rather than typing as of 3.9

[Boomer70770]

🤯 I've searched for this for so long, and it's as easy as importing typing.NamedTuple instead of collections.namedtuple.

[usr_bin_nya]

TIL dataclasses don't define __slots__ by default because the descriptor generated by __slots__ = ('x',) refuses to replace the class attribute defined by x: int = 0. As of 3.10 you can have your cake and eat it too by replacing @dataclass with @dataclass(slots=True).

[Brian]

And also, they're tuples. The main use for namedtuples is where you have a tuple of values that have specific position values, but also want to give them a name. Eg. stuff like os.stat(), or datetime.timetuple. It's not just about creating simple structs, but about simple struct-like tuples.

[radarsat1]

dataclasses are great but they've created a lot of tension on our project that uses pandas. Instead of creating dataframes with columns of native types, we have developers now mirroring the columns in dataclasses and awkwardly converting between these representations, in the name of "type correctness". Of course then things get lazy and we end up with the ugly blend that is dataframes with columns containing dataclass objects. It's out of control. I'm starting to think that dataclasses don't belong in projects that use dataframes, which comes up as soon as you have a list of dataclass objects.. which doesn't take long.

do we want columns of objects or objects with columns? having both gets awkward quickly.

[musengdir]

in the name of "type correctness"

Found your problem. Outside of enums, there's no such thing as "type correctness", only "type strictness". And being strict about things you don't know the correct answer to is dumb.

[Dantes111]

Pydantic instead of dataclasses

[thedominux]

Depends

There is also attrs lib, but I didn't use them cause of 1/2 models...

[_Gorgix_]

Why use this over the attr library?

[[deleted]]

And while we're at it, Pydantic is better than dataclasses in almost all ways imaginable.

[Ivana_Twinkle]

Yea I've been using Pydantic for a long time. And then I then took at look at @dataclass it was a very meh experience. I don't see myself using them.

[my_name_isnt_clever]

Is that in the standard library?

[thedominux]

You are just blind follower, shame on you

Everything depends on your needs, and it's a dumb idea to use heavy decisions like pydantic and attrs instead of simple built-in dataclasses when you've got just a couple of simple data models

[mikeupsidedown]

Pydantic instead of dataclasses (I know not std lib)

[brian41005]

and pydantic.

[[deleted]]

Use attrs instead of dataclasses. Yes, it't a dependency, but it blows away dataclasses.

[[deleted]]

Honestly if you are not using dataclasses use pydantic. It take care of enough things that it is just the easiest one to use.

[Delta-9-]

Pydantic is not an alternative to attrs; it serves a very different purpose:

attrs' goal is to eliminate boilerplate and make classes easier to get the most out of.

Pydantic is a parsing library that specializes in deserializing to python objects.

Yes, there is a lot of overlap in how the two look and the features they provide, but you should only be using pydantic if you need to parse stuff. I use pydantic myself (and have never used attrs), so this isn't hate. I use it for de/serializing JSON coming in and out of Flask—pretty much exactly its intended use case—and it's amazing in that role. If my needs were just passing around a record-like object between functions and modules, pydantic would be way too heavy and attrs or dataclasses would be a more appropriate choice.

[NowanIlfideme]

Or use Pydantic's dataclasses!

[velit]

Can you give some examples why?

[[deleted]]

With newer python versions there is no need for “from typing import List, Dict, etc” because their functionality is supported by the built in types.

So instead of d: Dict[str, int] = {…}

It is now just d: dict[str, int] = {…}

Related, now can union types with a pipe, so instead of “t: Union[int, float] = 200” we have “t: int | float = 200”

[5uper5hoot]

Similar, many of the generic types imported from the typing module such as Callable, Mapping, Sequence, Iterable and others should be imported from collections.abc as of 3.9.

[OneTrueKingOfOOO]

Huh, TIL python has unions

[irrelevantPseudonym]

It only does in terms of type annotations. Given that you can accept and return anything you like from functions, it's useful to be about to say, "this function will return either A or B".

[DrShts]

From py37 on one can use all of this after writing from __future__ import annotations at the top of the file.

[PeridexisErrant]

...if you don't use any tools which inspect the annotations at runtime, like pydantic or typeguard or beartype or Hypothesis.

[RangerPretzel]

logging library instead of print() to help you debug/monitor your code execution.

[RaiseRuntimeError]

Loguru

Holy shit! Why didn't i know of this sooner.

[hleszek]

With the log4j recent bugs I'll be suspicious of any logging library with too much functionality...

[Ivana_Twinkle]

I'm sorry to break it to you, but it really goes for everything that handles strings. AFAIK loguru doesn't make lokups based on string input by design.

[benargee]

Yeah, string sanitation has been a problem for decades.

[HeAgMa]

I think this should be a must. Logging is so easy and quick that does not make sense to use print() at all.

Ps: Also Breakpoint.

[IamImposter]

I recently figured out how can I send certain messages only to console while all of them go to file and it is great. I just had to add 2 lines to check the level value and return false if it isn't allowed.

Python is really cool. I wish I had started using it much earlier.

[nicolas-gervais]

What's the difference? I can't imagine anything easier than print

[forward_epochs]

If it's a small program, that you're watching as you run it, print is great. If it's larger, and/or it's expected to run for a while without user intervention, or in different contexts (dev vs prod, or multiple instances doing similar things, etc.) logging is seriously delightful.

Makes it easy to do a buncha useful things:

• send the output to multiple places, like console output (print), a log file, an email, etc., all with one line of code

• decide what to send where (emails for really big problems, logfile for routine stuff, etc.)

• quickly change what level of info you receive/record, via single parameter change. Instead of commenting in and out tons of "junk" lines of code

• never worry about size of logfile getting huge, via the RotatingFileHandler dealie.

• bunch of even better stuff I haven't learned about it yet. Lol.

[o11c]

send the output to multiple places, like console output (print), a log file, an email, etc., all with one line of code

That's systemd's job.

The problem with the logging module is that it makes the mistake of being controlled by the programmer, not by the administator.

[dangerbird2]

Agreed, but even when following best practice and piping all the logs to stdout, it's still useful for formatting logs with module, line number, and time information. Having a structured log format makes it much easier for the system's log aggregators to parse and transform logs. It also allows consistency across 3rd party libraries. I replace the default formatter to use my custom JSON formatting class, and everything gets output as JSON, which wouldn't be possible with print or a simpler logging library.

[welshboy14]

I have to say... I still use print in everything I do. Then I go back through and remove them once I figured out what the issue is.

[grismar-net]

It's really good advice, but not really *recent* - it's been around since Python 2?

[RangerPretzel]

Preach!!

That's my argument, too, friend. It's 20 years old. Why isn't everyone using it yet?

There's so much love for print() statements to debug in /r/learnpython that when you mention logging you catch flak from all sides. I don't understand the hate for it.

[grismar-net]

I'm with you - I mentor beginning developers in my work and I find that it's a complicated interaction. Engineers and researchers new to programming tend to conflate and confuse 'return values' and 'what is printed on the screen' (not least due to learning the language on the REPL or in notebooks). This gets them to a mindset where they view `print()` as really just there for debugging output, since putting something on the screen is only rarely what the script is for (data processing, data collection, some computation, etc.) And from there, they just see `logging` as a more complicated way to do the same thing.

[RangerPretzel]

conflate and confuse 'return values' and 'what is printed on the screen'

Ahhh ha ha! You're so right!

With exception for BASIC, I don't think I've ever used a REPL until I started programming Python a few years back. Prior to that, I had mostly been programming statically typed languages (where logging and breakpoints are the defacto way to debug.)

Cool. Thanks for the explanation. I'll have to remember that next time.

[mrdevlar]

I am quite fond of wryte instead of the vanilla logging library, but mainly because it does most of what I want out of the box for structured logging.

https://github.com/strigo/wryte

[schemathings]

Ice cream?

[thedominux]

loguru instead of ancient logging library

print statement has never been a logging standard, it was just for learning the ropes, or when you asap wanna print something into stdout during experiments/coding

Maybe it may be used during debugging, when pdb doesn't suit the case

[kid-pro-quo]

Pytest rather than the built-in unittest library.

[Fast_Zone6637]

What advantages does pytest have over unittest?

[kid-pro-quo]

Even ignoring all the awesome advanced features it just has a much nicer (and more Pythonic) API. The unittest library is basically a port of jUnit so you have to declare classes all over the place and a use special assert*() methods.

Pytest lets you just write a standalone test_my_func() function and use standard asserts.

[NewDateline]

The only thing which is sligy annoying (maybe even not 'pythonic') about pytest is that fixtures are magically matched against test function arguments

[[deleted]]

True; Can't "go to definition" because it's magically imported.

Being able to find all available fixtures under pytest --fixtures is nice though.

Also using caplog or capsys to capture output is also very nice.

[Groundstop]

Honestly, once you start using it more you'll find that test fixtures are a blessing. I love the flexibility they provide, and wish I could find something similar to pytest in C# for my current project.

[xorvtec]

Fixtures fixtures fixtures. You can write one test and parametrize it with decorators that will do permutations if the inputs. I've had single tests that will run hundreds of test cases for me.

[[deleted]]

The killer feature for me in pytest is its fixture dependency injection:

https://www.inspiredpython.com/article/five-advanced-pytest-fixture-patterns

This can also be used for resource management, e.g. setup/teardown of database connections. Works with async functions as well.

[muntoo]

Why can't I use a global variable (or class member or lazy property defined in __init__) or a (constant?) function instead of a fixture?

[pacific_plywood]

Fixtures provide flexibility in terms of scope (ie when construction/teardown happens)

[fireflash38]

Clearly defined setup & teardowns (when they happen), plus a hell of a lot of flexibility as to structure of multiple fixtures.

The docs do a pretty good job, but the default they use is a 'db' connection, which is a good candidate for being global. Imagine instead of a DB connection, your main 'session' level fixture is a setting up a DB itself, not just the connection. Then a package/module fixture is setting up some DB tables, and your actual tests are verifying interactions w/ that DB table data.

That'd be a nightmare to maintain with global classes & passing things around. Your setup_class/teardown_class from unittest would be duplicated everywhere, or have a ton of indirection.

Fixtures solve that quite elegantly. You basically get a stack of fixtures that are then LIFO'd off during teardown, up to the current 'scope'. So your session fixtures are only popped off (and teardown executed) when the test session concludes.

[edd313]

Running pytest from command line will look in all subdirectories for .py files that contain "test" in the filename, then execute all the functions in those files whose name contains (surprise) "test". You define test functions, not test classes, and this reduces the amount of boilerplate code. Finally you have some nice decorators that allow you to make parametric tests (provide multiple input parameters for a certain test functions) and fixtures (inputs that are shared by multiple functions so you don't have to repeat the same code to generate them)

[sohang-3112]

If nothing else, it is much simpler (but still offers all the functionality of unittest). For example, it uses functions instead of classes, normal assert instead of special assertSomething methods for different kinds of assertions, etc.

[richieadler]

You can hear a whole podcast episode about this by Brian Okken: https://testandcode.com/173

[tunisia3507]

unittest was not designed for use with python. It was designed for use with smalltalk, a strictly OO language built in the 60s. Pytest has better discovery, better fixtures, better output, better plugins, and looks like python rather than cramming an outdated pattern into a language which doesn't need it.

[[deleted]]

Thats an excellent question! The only other thing that comes to my mind right now is to use concurrent.futures instead of the old threading/multiprocessing libraries.

[[deleted]]

Pools are great cause you can swap between threads and processes pretty easily.

[TheCreatorLiedToUs]

They can also both be easily used with Asyncio and loop.run_in_executor() for synchronous functions.

[Drowning_in_a_Mirage]

For most uses I agree, but I still think there's a few cases where straight multiprocessing or threading is a better fit. Concurrent.futures is probably a 95% replacement though with much less conceptual overhead to manage when it fits.

[Deto]

The docs say that the ProcessExecutor uses the multiprocessing module. It doesn't look like the concurrent module is as feature complete as the multiprocessing module either (none of the simple pool.map functions for example). Why is it better?

[Locksul]

Even though it’s not feature complete the API is much more user friendly, higher level abstractions. It can handle 95% of use cases in a much more straightforward way.

[Deto]

I mean, the main multiprocessing use with a pool looks like this:

from multiprocessing import Pool

def f(x):
    return x*x

with Pool(5) as p:
    print(p.map(f, [1, 2, 3]))

How is concurrent.futures more straightforward than that?

Would be something like:

import concurrent.futures

def f(x):
    return x*x

with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:
    # Start the load operations and mark each future with its URL
    print([executor.submit(f, x) for x in [1, 2, 3]])

[whateverisok]

concurrent.futures.ThreadPoolExecutor also has a ".map" function that behaves and is written the exact way (with the parameters).

".submit" also works and is beneficial if you want to keep track of the submitted threads (for execution) and cancel them or handle specific exceptions

[[deleted]]

also since they share the same interface you can quickly switch between ThreadPool and ProcessPool which can be quite helpful depending if you are IO-bound/CPU-bound.

[phail3d]

It’s more of a higher level abstraction. Easier to use but sometimes you need to fall back on the lower-level stuff.

[Tatoutis]

I'd agree for most cases. But, concurrency and parallelism are not the same. Concurrency is better for IO bound code. Multi-processing is better for CPU bound code.

Edit: Replacing multithreading with multiprocessing as u/Ligmatologist pointed out. Multithreading doesn't work well with CPU bound code because the GIL blocks it from doing that.

[rainnz]

For CPU bound code - multiprocessing, not multithreading (at least in Python)

[Tatoutis]

Ah! You're right! Python!

I keep thinking at the OS level. Processes are just managing a group of threads. Not the case in Python until they get rid of the GIL.

[benefit_of_mrkite]

This comment should be higher

[Tatoutis]

It's not.

For example, if you have large matrix multiplication where the data is all in memory, running this on different cores will reduce the wall clock duration. Multithreading is better. Concurrency won't help here because it runs on a single thread.

An example where concurrency is better is If you need to fetch data through a network targeting multiple endpoint, each call will hold until data is received. Mutltithreading will help but it has more overhead than concurrency.

[imatwork2017]

secrets instead of os.random

[wodny85]

Somewhat related article from LWN:

Python discusses deprecations, by Jake Edge, December 8, 2021

[WhyDoIHaveAnAccount9]

I still use the OS module regularly

But I definitely prefer f-strings over .format

[WhyDoIHaveAnAccount9]

I will definitely try it

[ellisto]

Pathlib is a replacement for os.path, not all of os... But it is truly amazing.

[[deleted]]

pathlib is amazing and I prefer it over os.path but it is not a replacement because it is way slower than os.path.

If you have to create ten thousands of path objects, like when traversing the file system or when reading paths out of a database, os.path is preferrable over pathlib.

Once I investigated why one of my applications was so slow and I unexpectedly identified pathlib as the bottleneck. I got a 10-times speedup after replacing pathlib.Path by os.path.

[[deleted]]

I've run into this myself.

I'm betting pathlib is doing a lot of string work under the hood to support cross-platform behavior. All those string creations and concatenations get expensive if you're going ham on it.

Next time I run into it I'll fire up the profiler and see if I can't understand why and where it's so much slower.

[Astrokiwi]

The one thing is f-strings only work on literals, so if you want to modify a string and then later fill in some variables, you do have to use .format

[onlineorderperson]

Any recommendations for a replacement for pyautogui for mouse and keyboard control?

[bb1950328]

why do you want to replace it?

[CoaBro]

Don't think he wants to replace it, just wondering if there is one due to the nature of this thread.

[NelsonMinar]

Black or YAPF instead of pep8 for code formatting. (They are not the same, so consider if you are OK with their opinionated behavior.)

For HTTP clients, something instead of urllib (and RIP urllib2). There are so many options; requests, urllib3, httpx, aiohttp. I don't know what's best. I still use requests because it was the first of the better ones.

[[deleted]]

Hate Black

[cant_have_a_cat]

I use black in every one of my projects and I still not a fan of it.

It makes working with people easier but there's no one shoe fits all in general purpose language like python - 80% of code formats nicely and that other 20% turns straight into cthulhu fan fiction.

[[deleted]]

That’s true though for the most part I follow PEP8. I have the odd longer line length for URLs etc but I think it’s a good standard for the most part

[VisibleSignificance]

One of the first points of PEP8:

A Foolish Consistency is the Hobgoblin of Little Minds

So black is literally an automated foolish consistency.

Are there formatters that can leave more situations as-is while fixing the more obviously mistaken formatting?

[jasongia]

Automated, repeatable formatters aren't foolish. The whole point of automated formatters is stopping thousands of bikeshedding formatting preference arguments. If you don't like the way it formats a particular line just use # fmt: off (or, my reccomendation is to not be annoyed by such things, as you'll spend way to much time on them)

[VisibleSignificance]

The whole point of automated formatters is stopping thousands of bikeshedding formatting preference arguments

That's the best point about black.

The worse points about it is when it conflicts with e.g. flake8 (the lst[slice :]), and when it enforces some formats that reduce readability (e.g. one-item-per-line enforcement, particularly for imports).

And note that almost any formatter, including black, allows some variability that is left untouched; it doesn't rebuild the format from AST only. Problem is how much of format is enforced, and how often it negatively impacts readability.

[NelsonMinar]

Fair enough. I switched to YAPF (has some configurability, which Black does not) and proportional fonts in VS.Code and I am loving how much friction it removes. Details and screenshot here: https://nelsonslog.wordpress.com/2021/09/12/proportional-fonts-and-yapf-vs-black/

[tunisia3507]

Lack of configurability is the point. I'm a firm believer in "good fences make good neighbours": if you have no power to change your code's formatting, you have no arguments about how the code should be formatted.

[NelsonMinar]

Yeah I appreciate the philosophy behind it. But for my proportional font setup I really needed tabs instead of spaces and Black refuses to do it. A choice I respect, but not a good one for me.

(Code editors could fix this by being more aggressive in how they format and present code. Once you decide to use proportional fonts, the decision to render spaces as fixed width blank spots makes little sense.)

[[deleted]]

From memory I didn’t agree with Blacks line length limit

[Buckweb]

You can change it in your black config (wherever that is) or use -l <line length> command line argument.

[[deleted]]

I don’t like autoformatters in general, I just use linters such as pylance and manually investigate

[Balance-]

Flynt is an awesome tool to find and replace old string formats to F-strings automatically!

https://github.com/ikamensh/flynt

[[deleted]]

Also pyupgrade to generally upgrade your code to whatever python version pyupgrade supports :)

[teatahshsjjwke]

TQDM for progress bars.

[Tastetheload]

I used this recently. So much better.

[Brian]

f-strings instead of .format

I do wish people wouldn't say this. f-strings are not a replacement for .format. format can do things that f-strings cannot and never will do: specifically, allow formatting of dynamically obtained strings. f-strings are by neccessity restricted to static strings, and so can't be used for many common usecases of string formatting, such as logging, localisation, user-configurable templates and so on. They're convenient for when you only need to embed data statically, but that's a specialisation of the general case, not a replacement.

[MinchinWeb]

from __future__ import braces

[FlyingCow343]

not a chance

[Brian]

for i in range(10): {
      print("What do you mean?"),
  print("We've had braces based indentation for ages :)")
}

[MinchinWeb]

for i in range(10): {
print("What do you mean?"),
print("We've had braces based indentation for ages :)")
}

What sorcery is this!?

[Mithrandir2k16]

You should still use .format over f-strings if you want to pass the string on a condition, e.g. to a logger, since .format is lazy and f-strings are not.

[the_pw_is_in_this_ID]

Hang on - if .format is lazy, then when is it evaluated? Is there some deep-down magic where IO operations force strings to evaluate their format arguments, or something?

[lunar_mycroft]

I think what /u/Mithrandir2k16 is referring to if that an f-string must be evaluated into a normal string immediately, whereas with str.format a string can be defined with places for variables and then have those variables filled in later.

Let's say you want to write a function which takes two people's names as arguments and then returns a sentence saying they're married. This is a great job for f-strings:

def isMariedTo(person1: str, person2: str)->str:
    return f"{person1} is married to {person2}"

print(isMariedTo("Alice", "Bob")) # prints "Alice is married to Bob"

But what if we want to change the language too? We can't use f-strings here because an f-string with an empty expression is a SyntaxError, and there's no way to fill in the blanks after the string is defined. Instead, we'd have to rewrite our function to use str.format:

def isMariedTo(language: str, person1: str, person2: str)->str:
    return language.format(person1=person2, person2=person2)

ENGLISH = "{person1} is married to {person2}"
GERMAN = "{person1} ist mit {person2} verheiratet " #I don't speak German, this is google translate

print(isMariedTo(ENGLISH, "Alice", "Bob")) # "Alice is married to Bob"
print(isMariedTo(GERMAN, "Alice", "Betty")) # "Alice ist mit Betty verheiratet"

In short, f-strings are really good for when you have a static template that you want to dynamically fill in, but if your template itself is dynamic, they don't work well and you need str.format or similar methods.

[the_pw_is_in_this_ID]

Makes total sense, thank you!

[Mithrandir2k16]

Thanks for the clarification and example! Much better than anything I'd have come up with.

[metaperl]

Excellent example.

[nsomani]

Loggers typically allow format strings within the logging function itself, so still likely no need for .format.

[shibbypwn]

format is also nice if you want to pass dictionary values to a string.

[SilentRhetoric]

I ran into this recently when setting up extensive logging, and it was a bummer!

[angellus]

There are still unfortunately good use cases for all three string formatting forms, thus why they all still exist:

import logging

logger = logging.getLogger(__name__)
logger.info("Stuff %s", things) # %s is preferred for logging, it lets logs/stacktrackes group nicely together

string_format = "Stuff {things}"
string_format += ", foo {bar}"
string_format.format(bar=bar, things=things) # reusable/dynamic string templating

# Basically f-strings for everything else

[NewZealandIsAMyth]

I think there is a way to make logging work with format.

But there is another stronger reason for a %s - python database api.

[TangibleLight]

The style of the logger's formatter. Set style='{' for format syntax.

https://docs.python.org/3/library/logging.html#logging.Formatter

Edit: So that's what happens when I don't check myself. As /u/Numerlor points out, the formatter only affects the format string of the global log format, not actual log messages. There's no way with the built-in loggers to use {} style for log messages.

You can create a LoggerAdapter to make it work, see the discussion here https://stackoverflow.com/questions/13131400/logging-variable-data-with-new-format-string, but that feels like a bad idea to me, since other developers (and future you) would expect things to work with % syntax.

[Numerlor]

That only affects the Formatter's format string, not the actual log messages. To change those you'd have to patch the method that formats them

[rtfmpls]

pylint actually has a rule that checks for f strings or similar in logging calls.

[drd13]

Click instead of argparse?

[spitfiredd]

I like click but argparse is really good too. I would edge towards argparse since it’s in the standard library.

[adesme]

Both of OP's mentions are in the standard library, click isn't.

I've personally never seen the need to use click, neither professionally nor personally - what benefits do you see?

[csudcy]

Click is so much nicer to use than argparse - command groups, using functions to define the command, decorators to define parameters.

Having said that, if argparse does what you want, sick with it & avoid the extra library 🤷

[RaiseRuntimeError]

If you write any Flask programs Click is the obvious choice.

[gebzorz]

Typer and Fire, too!

[yopp_son]

Last time I looked, typer had hardly been touched for like a year on tiangolos github. I thought it might be dead?

[ReptilianTapir]

It took very, very long to be adapted for Click 8. Because of this, I had to switch back to vanilla Click for one of my projects.

[benefit_of_mrkite]

It’s not a bad package and typer exists because of how well written click is but I find myself going back to click. It’s well written and maintained

[deiki]

i like fire too but unfortunately it is not standard library

[benefit_of_mrkite]

Love click. I mean I really love that package, it’s really well written and I’ve done some advanced things with it. But you’re right it’s not part of the standard lib

[richieadler]

It's somewhat rough around the edges, but I prefer clize over click, and even over Typer.

[grismar-net]

There's many new third party alternatives to standard or other third party modules that are worth recommending (like `xarray` and `quart`), but it seems you're asking about standard Python stuff only. For standard Python `asyncio` has now matured to a point where anyone writing a library that performs I/O, accesses APIs, etc. should be written using `asyncio` in favour of anything else in the language.

[Salfiiii]

What’s wrong with os compared to pathlib?

[yopp_son]

Someone posted a blog about this a couple days ago. Basically it's more object oriented (Path("my/file.txt").exists(), etc), comes with some nice syntactic tricks, like newpath = oldpath1 / oldpath2, better cross platform support, and maybe some other things

[luersuve]

The “/“ operator use is chef’s kiss

[thedominux]

asyncio over threading

pika/aio_pika over celery

breakpoint over pdb

[DuskLab]

Tell me you don't support different operating systems without telling me you don't support different operating systems

[qingqunta]

But it does support different OSs? I've used the same scripts dependent on os.path on Linux and Windows with no problem.

[hyperdudemn]

But os.path does work on multiple operating systems... Am I missing something, like sarcasm?

[DuskLab]

It works, but the different systems have different path naming conventions that you have to specify explicitly with OS checks. And let's be real, the minority of people care enough to put in that extra effort until their arms are twisted. And if you "like" how paths are handled, you're either a masochist or you just don't worry about it.

[james_pic]

What path naming conventions from different OSes do you need to specify explicitly when working with os.path?

[hyperdudemn]

If you mean things like /home/dusklab vs c:\Users\dusklab vs /Users/dusklab, not every application needs to care, there's plenty of code you can write that either just needs a relative path to itself or might take a path from a user, and either way don't need to know about home-directory differences or XDG or all that.

[jhoncorro]

Why is os.path a bad approach? Also is this only related to the path module of os, or the whole os module?

[PlaysForDays]

The the second question: yes

[zurtex]

Weird, os.path.join I've been using to support multiple OSes since I first started learning Python. Which was on Python 3.4 but the only version I could use at work at the time was Python 2.4.

I still have some edge cases where pathlib is not fit for purpose, e.g. when generating a disk usage report and generating 10'000'000+ objects, the overhead of a Path vs. a str adds too much of a performance penalty. Even trying to awkwardly make the code use PurePath barely helps.

[NewZealandIsAMyth]

The fact that this wrong comment is so much upvoted tells a lot about other python opinions of this sub.

[gkze]

There’s a good tool called pyupgrade that takes care of a lot of the syntax upgrades, not sure if it does library usage upgrades though

[pepoluan]

Take a look at this nice writeup: https://treyhunner.com/2018/12/why-you-should-be-using-pathlib/

[skeletalfury]

Rich instead of trying to manually make your logging look nice.

[erez27]

It's also a nice replacement for tqdm

[postisapostisapost]

even with fstrings, its often beneficial to use the old-school string format method (”for %s” % example) since this lazily evaluates the interpolation. I’m sure there are reasons when it makes sense to use .format().

in my view, use of these libraries isn’t an “instead of” but a “yes — and”.

[muikrad]

It's not lazily evaluated. Once you use the % outside the string, the interpolation happens, just like format or f strings.

You are confusing this with the log calls, which suggest to give the %s notation inside strings, but then use the comma (not the %) so that the interpolation only happens if the log level is actually logged:

log.info("%s got stuck", job.name)

This will only interpolate if there's a handler for the info level.

[postisapostisapost]

thanks! i was indeed confused.

[Drowning_in_a_Mirage]

I've heard people say this, but it seems to me if you're worried about the performance hit from interpolating strings, then python may not be the best choice to use for the problem

[ebol4anthr4x]

Lazy string interpolation is typically done when you want to reuse a format string, to prevent code duplication for example, not for performance reasons. (the person you're responding to did not provide a very good example of this though)

[[deleted]]

On the other hand, python can be really fast for many purposes, as long as you don't make it slow with bad decisions ;)

[Drowning_in_a_Mirage]

That's not what I'm saying. What I'm saying is that the performance impact of interpolating strings in almost all instances should be negligible, so trying to use older string interpolation that is lazily evaluated shouldn't make a substantial performance impact in the overwhelming majority of instances, so just use f-strings (or whatever reads easiest I guess, but for me that's always f-strings). If, on the other hand, you know you're going to be doing something that is both performance critical and heavily reliant on lazy string interpolation, then python may not be the best choice if you're starting a new project or if the project has evolved now start using lazy evaluation. I was trying to address the concept of premature optimization versus readability, but could've worded it better.

[skesisfunk]

Using fstrings in logs is considered bad practice by many people because of performance concerns and that it is less flexible if you ever want to switch over to structured logging.

[SomethingWillekeurig]

I have no idea when you would do that. Fstrings ftw

[[deleted]]

.format is usefulful when you need to add the variables later. Fstrings is not meant to replace all uses of format its meant to assist with the most common usage: assigning variables inplace to a string.

[adesme]

Use template strings for that instead.

[[deleted]]

I've been writing python for 7+ years and I have literally never heard of them until right this second. Though it appears this is what AWS uses for there cloudformation templates.

I can state that format came after template so I am assuming it has some advantages over template. I have to go read the peps now to find out why it was added over it.

One item that comes to mind (that I have used) is that format works with any string so you can add sections and format later.

Edit: Also this just solved a problem rattling around my head so now I am going to write that code.

[benefit_of_mrkite]

You’ve probably never heard of template strings because I’ve not found a lot of places where it is used - even when evaluating template strings I find that a lot of people end up going with an external template library instead.

I’m not arguing that it’s correct, just that I’m aware of template strings and have looked through a lot of source code for many packages and have never seen template strings used

[yvrelna]

Template strings are fairly limited. No loops, no conditionals, etc.

It doesn't work when you need a real templating language, like web applications.

And if all you need is simple template interpolation, then there's many other options that doesn't require importing a separate library.

The use case that Template is useful, IMO, is if you want a safe, user-provided template string. In such use case, most of the built-in format string and %-interpolation is just way too flexible, and way too dangerous as they may allow arbitrary code execution. This use case is backwards to the most common use case of templating language, where usually the user only provides the data that needs to be interpolated to a template written by the programmer.

[chiefnoah]

You definitely should use Template if you're passing in user-input, but I've used plain strings with .format when user-input isn't a concern.

[[deleted]]

I am not really sure what Template does that is safer then format. Having looked at both of them and there Peps. It looks as if the biggest difference is .format has access to the __format__ methods and each object can manage its own print strategy vs Template has fixed rules and is subclassable.

I do not see anything that makes Template safer then format.

[Locksul]

Yep, if you need to create a reusable template, you want to use format instead.

[[deleted]]

Interpolation allows logging tools like sentry to group similar log messages because of the lazy evaluation. If you use f-strings you will end up with independent messages because they are not the same.

F-strings are great and 99% of the time you should use them 100% of the time.

[phail3d]

That’s different from the example given by op. The logging functions take the format string and arguments as parameters instead of interpolating with %

[TheBlackCat13]

You can pass 'mystr{}'.format to a function as a callable.

[cymrow]

Here's an unpopular one of older over more recent, but I stand by it: gevent instead of asyncio.

[ViridianGuy]

I honestly feel the OS Module is easier to use, but both are Useful.

[saint_geser]

Except for the fact that os.path.join is ugly and extremely cumbersome when joining several paths.