- 22x speedup
- 3x lower memory
- 50% code reduction
- Native dataframe validation with minimal overhead using Dataframely
Watch: www.youtube.com/watch?v=TL-3...
- 22x speedup
- 3x lower memory
- 50% code reduction
- Native dataframe validation with minimal overhead using Dataframely
Watch: www.youtube.com/watch?v=TL-3...
pola.rs/posts/case-m...
pola.rs/posts/case-m...
pola.rs/posts/series...
pola.rs/posts/series...
Watch the session of Gijs Burghoorn, core developer @ Polars, here: youtu.be/xc5IsfwKRKE. In his talk he discussed how and why we optimize our Parquet reader.
Watch the session of Gijs Burghoorn, core developer @ Polars, here: youtu.be/xc5IsfwKRKE. In his talk he discussed how and why we optimize our Parquet reader.
You can now spawn >100k queries to a single cluster and we load balance them gracefully. Additionally, the query planning now is posted as a worker task and can be cancelled by the user.
github.com/pola-rs/pola...
You can now spawn >100k queries to a single cluster and we load balance them gracefully. Additionally, the query planning now is posted as a worker task and can be cancelled by the user.
github.com/pola-rs/pola...
Learn more in the case study: pola.rs/posts/case-d...
Learn more in the case study: pola.rs/posts/case-d...
Read the post to get started!
pola.rs/posts/polars...
Read the post to get started!
pola.rs/posts/polars...
There will be a talk the Polars team and a community talk. It is also the perfect place to meet fellow Polars users.
RSVP here: www.meetup.com/polars-meetu...
There will be a talk the Polars team and a community talk. It is also the perfect place to meet fellow Polars users.
RSVP here: www.meetup.com/polars-meetu...
We've partnered with @datacamp.bsky.social to create an interactive course that covers the fundamentals so you can write your next query with Polars.
The course is free till the end of August: www.datacamp.com/courses/intr...
We've partnered with @datacamp.bsky.social to create an interactive course that covers the fundamentals so you can write your next query with Polars.
The course is free till the end of August: www.datacamp.com/courses/intr...
Let's go through a few:
1/4
Selectors are now implemented in Rust and we can finally select arbitrary nested types:
Topics:
- Parquet reader improvements
- Migrating pipelines using Dataframely, Quantco's open-sourced schema validation tool.
RSVP: www.meetup.com/polars-meetu...
Topics:
- Parquet reader improvements
- Migrating pipelines using Dataframely, Quantco's open-sourced schema validation tool.
RSVP: www.meetup.com/polars-meetu...
- Ritchie Vink covered the new streaming engine and shared updates on Polars Cloud and the upcoming distributed engine.
- Vyas Ramasubramani shared how GPU accelerated Polars works.
youtube.com/watch?v=fYi9...
youtube.com/watch?v=fYi9S6
- Ritchie Vink covered the new streaming engine and shared updates on Polars Cloud and the upcoming distributed engine.
- Vyas Ramasubramani shared how GPU accelerated Polars works.
youtube.com/watch?v=fYi9...
youtube.com/watch?v=fYi9S6
Polars is the 3rd most admired rising tech in this years StackOverflow developer survey.
survey.stackoverflow.co/2025/technol...
Polars is the 3rd most admired rising tech in this years StackOverflow developer survey.
survey.stackoverflow.co/2025/technol...
Please consider trying it so that we can patch any regression before we ship the release next week.
github.com/pola-rs/pola...
Please consider trying it so that we can patch any regression before we ship the release next week.
github.com/pola-rs/pola...
Ritchie Vink will introduce Polars Cloud, the platform to scale Polars remotely. Vyas Ramasubramani from NVIDIA will be talking about the internals of accelerating your Polars queries with the GPU engine.
RSVP: lu.ma/60b6wfs8
Ritchie Vink will introduce Polars Cloud, the platform to scale Polars remotely. Vyas Ramasubramani from NVIDIA will be talking about the internals of accelerating your Polars queries with the GPU engine.
RSVP: lu.ma/60b6wfs8
Start using Polars .group_by() to make sense of your data. This tutorial shows you how to group, aggregate, and reveal hidden insights with hands-on examples
#python
Start using Polars .group_by() to make sense of your data. This tutorial shows you how to group, aggregate, and reveal hidden insights with hands-on examples
#python
Reviews 5 #Python validation libraries that work with @pola.rs DataFrames: Pandera, Patito, Pointblank, Validoopsie, & Dataframely.
Read it on the Pointblog: posit-dev.github.io/pointblank/b...
Reviews 5 #Python validation libraries that work with @pola.rs DataFrames: Pandera, Patito, Pointblank, Validoopsie, & Dataframely.
Read it on the Pointblog: posit-dev.github.io/pointblank/b...
Learn how UVM works in more detail and how to optimize the configuration for your use cases, including performance implications.
pola.rs/posts/uvm-la...
Learn how UVM works in more detail and how to optimize the configuration for your use cases, including performance implications.
pola.rs/posts/uvm-la...
See the full changelog here.
github.com/pola-rs/pola...
Want something more with DataType expressions, here is the RFC:
github.com/pola-rs/polars
See the full changelog here.
github.com/pola-rs/pola...
Want something more with DataType expressions, here is the RFC:
github.com/pola-rs/polars
The future of Polars looks bright and very, very fast!
pola.rs/posts/benchm...
The future of Polars looks bright and very, very fast!
pola.rs/posts/benchm...
Learn the fundamentals and get familiar with our API through hands-on exercises. The course is available for everyone and free until the end of August.
Start the free course here: www.datacamp.com/courses/intr...
Learn the fundamentals and get familiar with our API through hands-on exercises. The course is available for everyone and free until the end of August.
Start the free course here: www.datacamp.com/courses/intr...
In the last months, the team has worked incredibly hard on the new-streaming engine and the results pay off. It is incredibly fast, and beats the Polars in-memory engine by a factor of 4 on a 96vCPU machine.
In the last months, the team has worked incredibly hard on the new-streaming engine and the results pay off. It is incredibly fast, and beats the Polars in-memory engine by a factor of 4 on a 96vCPU machine.
These expressions perform computations across columns. (Or along rows, depending on how you look at it.)
If your horizontal operation isn’t implemented, you can use the general-purpose fold.
These expressions perform computations across columns. (Or along rows, depending on how you look at it.)
If your horizontal operation isn’t implemented, you can use the general-purpose fold.