Metadata-Version: 2.1
Name: fasttsfeatures
Version: 0.0.1
Summary: Scalable time series features computation
Home-page: https://github.com/Nixtla/fasttsfeatures/tree/master/
Author: Nixtla and contributors
Author-email: fede.garza.ramirez@gmail.com
License: MIT License
Keywords: time series,features,static features,temporal features
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: License :: OSI Approved :: MIT License
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: dev
License-File: LICENSE

# FastTSFeatures
> Scale the computation of static or temporal time-series.


## Install

`pip install fasttsfeatures`

## How to use

For the moment you need to upload your dataset to s3.
The response will be written in s3 as well.

```python
from fasttsfeatures.core import TSFeatures
```

```python
tsfeatures = TSFeatures()
```

```python
resp = tsfeatures.calculate_features_from_url(url=f's3://tsfeatures-api-public/train.csv', freq=7, kind='static')
```


