Metadata-Version: 2.1
Name: turintech-evoml-client
Version: 1.6.0
Summary: Python client library for core functionality of evoml
Home-page: https://turintech.ai
Author: Turing Intelligence Technology
Author-email: support@turintech.ai
License: TURING INTELLIGENCE TECHNOLOGY LIMITED END-USER LICENCE
Keywords: evoml-client
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: Other/Proprietary License
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
License-File: AUTHORS.md
Requires-Dist: pandas (<2.0.0,>=1.4.2)
Requires-Dist: numpy (<2.0.0,>=1.21.5)
Requires-Dist: requests (>=2.27.0)
Requires-Dist: tqdm (>=4.62.3)
Requires-Dist: joblib (<2.0.0,>=1.1.0)
Requires-Dist: pydantic (<2.0.0,>=1.9.1)
Requires-Dist: pydantic[dotenv] (<2.0.0,>=1.0.0)
Requires-Dist: scikit-learn (<2.0.0,>=1.1.2)
Requires-Dist: pyarrow (>=8.0.0)
Requires-Dist: turintech-pagination (==1.2.2)
Requires-Dist: turintech-rest-clients (==1.2.2)
Requires-Dist: turintech-data-types (==1.2.3)
Requires-Dist: turintech-evoml-rocket-client (==1.2.0)
Provides-Extra: full
Requires-Dist: turintech-evoml-python-dependencies[external_runtime] (==2.6.0) ; extra == 'full'
Requires-Dist: numpy (<1.25.0) ; extra == 'full'
Requires-Dist: pydantic[dotenv] (<2.0.0) ; extra == 'full'

# turintech-evoml-client

Python client library to support script and notebook interactions with the platform


## Installation
There are two options to install the client library:

### Default installation

Installs basic requirements and versions of libraries like pandas, numpy.

```shell
pip install turintech_evoml_client
```

### Full installation
 
If you want to be able to generate models locally make sure you use the `full` extra when installing evoml_client.

```shell
pip install turintech_evoml_client[full]
```
Note that if you are using zsh, you might need to use one the following command instead:

```shell
pip install turintech_evoml_client\[full\]
pip install "turintech_evoml_client[full]"
noglob pip install turintech_evoml_client[full]
```


## Description

Currently supports the following concepts and actions:

### Datasets:
* Creation - EvoML client supports: Pandas DataFrames, numpy arrays and csv files. With 
Additional support to come.
* Uploading - Send the locally defined Dataset to the platform in preparation for future
trials.
* Statistical analysis - Using the Analyser class retrieve statistical info on the uploaded
dataset.

### Trials:
* Configuration - Multiple levels of abstraction provided by the TrialConfig class to allow
specification of as much or as little technical details as desired.
* Uploading - Send the locally defined trial to the platform to await execution.
* Execution - Trigger the optimization of the given trial.
* Result retrieval - Get either all models or the best model for a trial.
* local execution - Once retrieved and built, models can be run locally against new data.

### AutoML:
* Given a Pandas Dataframe, Numpy array or EvoML dataset and a target column
returns the best model trained to predict the given target column.

You can find further information and examples in our documentation page: https://docs.evoml.ai/evoml-client/introduction


