High Level Expressions for Dask
Project description
Dask Expressions
Dask DataFrames with query optimization.
This is a rewrite of Dask DataFrame that includes query optimization and generally improved organization.
More in our blog posts:
Example
import dask_expr as dx
df = dx.datasets.timeseries()
df.head()
df.groupby("name").x.mean().compute()
Query Representation
Dask-expr encodes user code in an expression tree:
>>> df.x.mean().pprint()
Mean:
Projection: columns='x'
Timeseries: seed=1896674884
This expression tree will be optimized and modified before execution:
>>> df.x.mean().optimize().pprint()
Div:
Sum:
Fused(375f9):
| Projection: columns='x'
| Timeseries: dtypes={'x': <class 'float'>} seed=1896674884
Count:
Fused(375f9):
| Projection: columns='x'
| Timeseries: dtypes={'x': <class 'float'>} seed=1896674884
Stability
This is the default backend for dask.DataFrame since version 2024.3.0.
API Coverage
Dask-Expr covers almost everything of the Dask DataFrame API. The only missing features are:
melt
- named GroupBy Aggregations
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
dask-expr-1.0.tar.gz
(163.7 kB
view hashes)
Built Distribution
dask_expr-1.0-py3-none-any.whl
(178.4 kB
view hashes)