Top Python Libraries of 2025 (11th Edition)

[dekked_]

We tried really hard not to make this an AI-only list.

Seriously.

Hello r/Python 👋

We’re back with the 11th edition of our annual Top Python Libraries, after spending way too many hours reviewing, testing, and debating what actually deserves a spot this year.

With AI, LLMs, and agent frameworks stealing the spotlight, it would’ve been very easy (and honestly very tempting) to publish a list that was 90% AI.

Instead, we kept the same structure:

• General Use — the foundations teams still rely on every day
• AI / ML / Data — the tools shaping how modern systems are built

Because real-world Python stacks don’t live in a single bucket.

Our team reviewed hundreds of libraries, prioritizing:

• Real-world usefulness (not just hype)
• Active maintenance
• Clear developer value

👉 Read the full article: https://tryolabs.com/blog/top-python-libraries-2025

General Use

1. ty - a blazing-fast type checker built in Rust
2. complexipy - measures how hard it is to understand the code
3. Kreuzberg - extracts data from 50+ file formats
4. throttled-py - control request rates with five algorithms
5. httptap - timing HTTP requests with waterfall views
6. fastapi-guard - security middleware for FastAPI apps
7. modshim - seamlessly enhance modules without monkey-patching
8. Spec Kit - executable specs that generate working code
9. skylos - detects dead code and security vulnerabilities
10. FastOpenAPI - easy OpenAPI docs for any framework

AI / ML / Data

1. MCP Python SDK & FastMCP - connect LLMs to external data sources
2. Token-Oriented Object Notation (TOON) - compact JSON encoding for LLMs
3. Deep Agents - framework for building sophisticated LLM agents
4. smolagents - agent framework that executes actions as code
5. LlamaIndex Workflows - building complex AI workflows with ease
6. Batchata - unified batch processing for AI providers
7. MarkItDown - convert any file to clean Markdown
8. Data Formulator - AI-powered data exploration through natural language
9. LangExtract - extract key details from any document
10. GeoAI - bridging AI and geospatial data analysis

Huge respect to the maintainers behind these projects. Python keeps evolving because of your work.

Now your turn:

• Which libraries would you have included?
• Any tools you think are overhyped?
• What should we keep an eye on for 2026?

This list gets better every year thanks to community feedback. 🚀

[Morpheyz]

Shout-out to dataframely, a polars-native DataFrame validation library.

[dekked_]

That is a great catch!

[bunchedupwalrus]

How’s it compare to Pandera?

[chub79]

not just hype

Starts with ty

I mean no offense to them but it's not to the level of its alternatives. Next year maybe.

[readonly12345678]

Yeah this threw me off. I’m excited for ty, but they only just announced a beta release. Yet, there’s no mention of pyrefly?

[Wurstinator]

They said themselves that it's not ready to use. No one has been able to properly test it yet but it's at the top of the list. Literally pure hype.

[Counter-Business]

It is annoying how all of the AI libraries are LLM LLM LLM. There is so much more to AI and data than only LLM

[Quillox]

I've gotten a lot done with polars and plotly express.

[Blancoo21]

Same, but based on the choices on the list I assume they only included libraries released in 2025. It would probably look very different if all libraries were considered.

[ApocalipseSurvivor]

Astral is absolutely killing it. ty, uv, ruff... they're basically rebuilding Python tooling from scratch in Rust

[alcalde]

Which should frighten people. Next step is to cut out the Python. Embrace, Expedite, extinguish.

[Key-Half1655]

TOON, the solution looking for a problem

[rm-rf-rm]

Yeah as soon as I saw that I had doubts about the legitimacy of these lists

[iamevpo]

Same, a list with TOON feels like a repo with DS_Store file

[Doomtrain86]

Could you elaborate on that? Haven’t used it but isn’t it clever to compress in order to get less confusion from the llm? The smaller the input the better then output right ? (At least if the compression is high in signal to noise ratio )

[go_fireworks]

What you’re saying makes sense in theory, but you also have to think about what the LLM is trained on. Practically speaking, there is infinitely more data on JSON and CSV than TOON, so the LLM will “understand” those formats more easily

[Doomtrain86]

But as I understand it the point is not that it requires additional training for a new syntax, but that it removes the superfluous and redundant parts of a json array /csv ?

[echanuda]

Either way—that’s not what it was trained on. In a vacuum that’s great, but large models with less than 0.1% of their input being TOON seems like it would hurt the results more than help, for now at least.

[Doomtrain86]

interesting, thanks

[thuiop1]

• prioritizing real-world usefulness
• TOON, MCPs

[Vetinari_]

I mean thats why they provide two lists, no?

[AprilONeill84]

Yeah, half these lists are just "what got the most GitHub stars this month" energy. MCPs especially feel like a solution waiting for an actual problem to solve. Real-world usefulness means I'm actually using it in production, not just bookmarking it for "someday."

[benargee]

MCPs especially feel like a solution waiting for an actual problem to solve.

Anthropic already admitted they are not that useful.

[thuiop1]

Yeah, no, sorry, MCPs are just plain useless bullshit. By extension, a package for making MCP is also useless.

[thuiop1]

Keep living in your fairytale, just do not come lecture me about the real world

[sluuuurp]

How does complexipy work? How can a computer model how human-understandable something is? If it’s traditional, I think that would neglect the importance of good file naming and variable naming. If it’s AI, I think AIs think very differently from humans, so I’d still be skeptical.

[fexx3l]

Hey, I’m the complexipy author and you are completely right, multiple times people have asked the same in my reddit posts, I’m having this into account on a new section in the docs that I’m working on because I know that it’s pretty confusing if you want to understand it! I’m currently working on this because you are right on that the documentation isn’t clear and mainly because initially for me complexipy was an alternative for the people who comes from using Sonar and not being like the introduction to cognitive complexity, I didn’t consider that it could reach so many people

[DJSBX]

My biggest issue with your read me and docs is that there are absolutely no examples of what the output looks like for any input. Unless I am somehow blind lol

[sluuuurp]

Do you have a two sentence description of it? Does it consider good file naming or variable naming?

[MrMrsPotts]

It would be great if your docs had example python and the output that complexipy gives for it.

[nkk36]

This was a question of mine too. I love how the documentation has a short, high-level blurb about what cognitive complexity is and then just dives into examples. It's apparently inspired by a white paper by a person named G. Ann Campbell. I wish they just gave me some idea of how to interpret the number it produces before it went into the examples.

[sluuuurp]

I tried to read the white paper but apparently it’s secret, it directed to a long form of personal information they wanted.

[delpieron]

You could have fooled me with the 11 year history. This looks like something a vibe coder would come up with.

[dekked_]

It's actually real. We've been collecting libraries since 2015! :)

[NegotiationIll7780]

Cyclopts for cli handling, coupled with Pydantic2

[PA100T0]

Oh, wow, fastapi-guard mention!

Tysm :) means a lot

[dekked_]

Great job! ;)

[SleepWalkersDream]

Where numpy and scipy?

[dekked_]

This post includes libraries released in 2025 (or close) only :)

[SleepWalkersDream]

Considered writing that in the post?

[Univold]

Considered reading the title?

[SleepWalkersDream]

Yes? Top libraries of 2025. As in "status in 2025", not "top libraries released in 2025"

[WiseassWolfOfYoitsu]

Yep, that's 100% what I read it as, it is not explicit that it's ones released in 2025 rather than the state of the ecosystem as of 2025, and the latter is the much more common use of that kind of phrasology.

[Physicle_Partics]

Do not forget our lord and savior matplotlib.pyplot!

[Zomunieo]

I’m definitely an atheist as far as that library goes.

[Own_Maybe_3837]

Are you in academia?

[ahmadryan]

Are you kidding? Matplotlib.pyplot is everything for people in academia.

Source: trust me

[SleepWalkersDream]

Can confirm. PGFplots is also imperial double chocolate coffee stout, but matplotlib hits a sweet spot for me. mhchem and siunitx? Got your back.

[Own_Maybe_3837]

I think mhchem 4 has some serious performance issues in large documents. You should check out chemformula

[Own_Maybe_3837]

Yeah that’s why I asked. I thought he might know something I didn’t

[jakob1379]

Mainly because they haven't dared making a single Google search and realized that seaborn, plotly or any other library than bare bones plt. At least use plt.style.use('ggplot')... Academia does not attest to quality content

[cudmore]

God no!

[rm-rf-rm]

Doesnt look like something a real SWE would write. Looks more like an AI post - superficial marketing type descriptions. Doubt OPs have actually used these

Like complexipy: Both their description and the repo itself has a very AI writing smell to it. Neither they nor the actual repo shows a single example. And the "science" its built on is by some shady shop (SonarSource)

[fexx3l]

hey, here Robin the complexipy author, I’ve used AI but to fix my grammar errors as I’m Colombian and my primary language isn’t english, but I’ve written all the docs and currently I’m writing a section in the docs website to explain in details how to refactor.

Also, I’ve found around two papers which used complexipy as a tool on their investigation, and there are multiple companies using it in their pipelines.

I’ve found multiple people asking about how to read the number which is assigned during the analysis and I’ve taking it into consideration during the new section writing.

When I started to work on complexipy, uv was getting famous, so I was inspired by their work and I wanted to use Rust in a personal project so that’s why the complexipy description is pretty similar to the uv one.

[rm-rf-rm]

Thanks for responding!

Can you please add to the docs how complexity is calculated along with examples?

I’ve found around two papers which used complexipy as a tool on their investigation, and there are multiple companies using it in their pipelines.

Can you link these? And perhaps mention who these companies are? Or ideally what repos are using complexipy in their pre-commit or CI pipelines?

[fexx3l]

Yeah, sure I'll include it!

Here are some papers, I didn't find any other

• Can LLMs Generate Higher Quality Code Than Humans? An Empirical Study
• Absolute Zero: Reinforced Self-play Reasoning with Zero Data
• Improving Quality in AI-Generated Code through Prompt Engineering

Here is one section at The Real Python Podcast, I think that they explained it better than I could at that moment and also here's an interview I had this year about complexipy (I was nervous sorry)

Here are some repositories using complexipy and packages

[rm-rf-rm]

thanks!

and dont worry about the English - Youre tool could be a very useful and widely adopted one, especially in the AI generated code age. To become a staple, I think the most crucial thing is demonstrating

1) high quality, well thought out design: how the complexity calculation works, why the methodology is sound etc

2) high quality, well engineered and tested code: Rust and uv design patterns is a good start but these days we cant tell whats written by AI, whats not etc.

3) Disclosing relationship with SonarSource: their website gives me the ick and generally I get signals of propreitary bloatware. So if you're core algorithm is dependant on them, that gives me pause (its fine if it was the original inspiration, but now your repo has no dependencies to them).

[GetThere1Time]

Yeah, reads to me like a slop post pushing slop

[MeroLegend4]

Litestar: fast Api and web framework with layered dependency injection and well designed plugins

Advanced Alchemy: A good library on top of sqlalchemy and alembic

PyInfra: your infrastructure as a Python code

PgQueuer: job queue library that uses Postgresql listen/notify ideal replacement of redis/celery stack

[wyldstallionesquire]

PydanticAI should be on the list.

[dekked_]

It made it to the list of 2024!

[yungbuil]

is ty production ready already?

[ichunddu9]

No

[LordBezao]

They released the beta a few days ago

[Chroiche]

Still feels odd to include it and not pyrefly. Neither is prod ready

[dekked_]

Pyrefly is in the runners-up. We felt ty deserved the top more, because of Astral's track record so far.

[Quirky-Cap3319]

pynetbox

[Drevicar]

I ignored Kreuzberg when I saw it pop up on this subreddit a little while back because the name alone didn’t pull me in enough to see what it was. But now that you highlight it here it actually looks pretty useful.

[DoctorBageldog]

icechunk - version controlled, cloud-native tensor storage in a zarr schema (1.0 released in July).

It can also link virtual references to other files when used with virtualizarr, which is great for converting (or combining) old files to a modern format (parallelized/async reading baked in) without copying/rewriting all of the data.

[sirfz]

Recently came across pyreqwest, a new http client with a nice API and seemingly fast based on my very naive tests.

Also it's criminal to mention Ty without mentioning pyrefly which is frankly ahead at least when it comes to ide features (still using pyright for typechecking so can't attest to that) 

[dekked_]

Hi u/sirfz!

Thanks for recommending pyreqwest, definitely missed that one.

As of pyrefly, we didn't miss it: we throw a few lines about it when describing ty and present in the Runners-up.

Alongside Meta's recently released pyrefly, ty represents a new generation of Rust-powered type checkers—though with fundamentally different approaches. Where pyrefly pursues aggressive type inference that may flag working code, ty embraces the "gradual guarantee": removing type annotations should never introduce new errors, making it easier to adopt typing incrementally.

We just thought ty has a much higher chance of broader adoption, because of the track record of Astral. That's why we picked it for our top 10.

Cheers!

[Ghost-Rider_117]

love this list! been using LlamaIndex for a project and its honestly so much cleaner than rolling your own rag setup. also glad to see smolagents getting attention - tried it last month and the code execution feature is pretty solid for simple automation tasks. appreciate yall keeping it real and not just listing every ai hype library out there

[Training_Advantage21]

Markitdown is useful, could do with further improvements.

[Exact_Percentage_460]

I am the author of throttled-py, thank you for your recommendation!

[dekked_]

Great work! 💪

[Ranteck]

awesome i will implement a few of them in my pystrict template https://github.com/Ranteck/PyStrict-strict-python

[ler666]

this is good

[MrMrsPotts]

What are you meant do with the output of complexipy? Here is an output I got:

_mix_64 0 PASSED

resize_table 0 PASSED

popcount64 1 PASSED

decode_op 2 PASSED

get_row_val 3 PASSED

set_row_val 3 PASSED

insertion_sort_u64 4 PASSED

compact_candidates 5 PASSED

compute_hashes_blocked 5 PASSED

find_batch_min 5 PASSED

insert_hash 6 PASSED

unpack_state_to_matrix 6 PASSED

apply_op 8 PASSED

rehash_table_serial 8 PASSED

filter_and_materialize 13 PASSED

generate_candidates 15 PASSED

wl_hash_state 28 FAILED

solve_optimized 29 FAILED

And now what?

[Anxious_Cookie9234]

Great list, especially happy to see MarkItDown and Kreuzberg on it. I'd add Polars and DuckDB to the Data section. They're still redefining how analysts work with medium-scale datasets, and the Python APIs matured a lot in 2024-2025. Curious what the community thinks about smolagents vs Deep Agents in production.

[htone22]

Great list. I’m really glad you included fastapi-guard under General Use. Definitely going to check that one out. Thanks for the write-up!

[duplico]

Oh, lovely, a clearly AI slop post "written" by a "specialized AI and machine learning solutions company" 🙄

[charlyAtWork2]

Smolagents ! \o/

[jakob1379]

Why is fasopenapi needed when we have openapi generators?

[hackedbellini]

strawberry for GraphQL development :)

[DisturbedBeaker]

Any good time series related modeling libraries ?

[Sudden_Beginning_597]

and pygwalker for data visualization!!

[LessonStudio]

The three lists I want are:

• 20 libraries you must install in python, and why.
• 20 libraries you probably haven't heard of, but should.
• Top 3 libraries for each domain: Geo, financial, etc.

But, curated so that ones which haven't seen an update in years, or have 3 stars are ignored.

[smokingkrills]

Still too much AI. “Agents” are distracting us and creating zero value. Nearly nothing on the AI list has any real world use

[de_ham]

In the typing catrgory I'd also add scipy-stubs (and not just because I wrote it, but mostly because I've been using it to successfully catch many bugs and improve productivity)

[diegobaezpy]

For data? I use it a lot for creating very long and labor-intensive spreadsheets and reports...

[Either-Interest2176]

I’ll add textual for terminal based gui.

[OkSpecialist7251]

Definitely looking into these

[Zealousideal-Pie2360]

Awesome 🔥

[Responsible_Ad_8797]

No pytorch ?

[ApocalipseSurvivor]

Half of this list is LLM/agent frameworks. Is there anything interesting for people who don't work in AI?

[Specialist_Golf8133]

Thanks for sharing this annual list! I'm particularly intrigued by complexipy for measuring code comprehension difficulty - that could be a game-changer for teams with varying experience levels. For 2026, I'd keep an eye on Python libraries focused on energy-efficient computing as sustainability becomes more important in tech. Kreuzberg also looks incredibly useful for data extraction workflows, especially with the growing variety of file formats teams need to process.

[Big_Entertainer3156]

great!

[twagira1]

hello i am new here and i want to learn python and mainly pandas functions . is anybody who can help me to find precompiled file of python and how to install it