ReactiveX operators for data science and machine learning.
RxSci is a set of RxPY operators and observable factories dedicated to data science. Being reactive, RxSci is especially suited to work on streaming data and time series.
However it can also be used on traditional datasets. Such datasets are processed as bounded streams by RxSci. So it is possible to use RxSci for both streaming data and file based datasets. This is especially useful when a machine learning model is trained with a dataset and deployed on streaming data.
Get Started
This example computes a rolling mean on a window and stride of three elements:
import rx
import rxsci as rs
source = [1, 2, 3, 4, 5, 6, 7]
rx.from_(source).pipe(
rs.state.with_memory_store([
rs.data.roll(window=3, stride=3, pipeline=[
rs.math.mean(reduce=True),
]),
]),
).subscribe(
on_next=print
)2.0
5.0See the Maki Nage documentation for more information.
Installation
RxSci is available on PyPi and can be installed with pip:
python3 -m pip install rxsci1 maintainer
Metadata
1 maintainer
Release files for rxsci 0.33.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| rxsci-0.33.0.tar.gz | 40.0 kB | Details |
Release files / rxsci-0.33.0.tar.gz
| Download URL | rxsci-0.33.0.tar.gz |
|---|---|
| Size | 40.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
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