Metadata-Version: 2.1
Name: ml-tracking-api
Version: 1.2.0
Summary: REST ML-AI API
Home-page: https://github.com/EimantasN/Equusight_BackEnd
Author: Eimantas Noreika
Author-email: noreika.eimantas@gmail.com
License: UNKNOWN
Keywords: OpenAPI,OpenAPI-Generator,REST ML-AI API
Platform: UNKNOWN
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: urllib3 (>=1.25.3)
Requires-Dist: python-dateutil

# ml-tracking-api
No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator)

This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:

- API version: v1
- Package version: 1.0.2
- Build package: org.openapitools.codegen.languages.PythonClientCodegen

## Requirements.

Python >= 3.6

## Installation & Usage
### pip install

If the python package is hosted on a repository, you can install directly using:

```sh
pip install git+https:////.git
```
(you may need to run `pip` with root permission: `sudo pip install git+https:////.git`)

Then import the package:
```python
import ml_tracking
```

### Setuptools

Install via [Setuptools](http://pypi.python.org/pypi/setuptools).

```sh
python setup.py install --user
```
(or `sudo python setup.py install` to install the package for all users)

Then import the package:
```python
import ml_tracking
```

## Getting Started

Please follow the [installation procedure](#installation--usage) and then run the following:

```python

import time
import ml_tracking
from pprint import pprint
from ml_tracking.api import data_rows_api
from ml_tracking.model.create_data_row_command import CreateDataRowCommand
from ml_tracking.model.data_row_dto_paginated_list import DataRowDtoPaginatedList
from ml_tracking.model.update_data_row_command import UpdateDataRowCommand
# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = ml_tracking.Configuration(
    host = "http://localhost"
)



# Enter a context with an instance of the API client
with ml_tracking.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = data_rows_api.DataRowsApi(api_client)
    page_number = 1 # int |  (optional)
page_size = 1 # int |  (optional)

    try:
        api_response = api_instance.api_data_rows_get(page_number=page_number, page_size=page_size)
        pprint(api_response)
    except ml_tracking.ApiException as e:
        print("Exception when calling DataRowsApi->api_data_rows_get: %s\n" % e)
```

## Documentation for API Endpoints

All URIs are relative to *http://localhost*

Class | Method | HTTP request | Description
------------ | ------------- | ------------- | -------------
*DataRowsApi* | [**api_data_rows_get**](docs/DataRowsApi.md#api_data_rows_get) | **GET** /api/DataRows | 
*DataRowsApi* | [**api_data_rows_id_delete**](docs/DataRowsApi.md#api_data_rows_id_delete) | **DELETE** /api/DataRows/{id} | 
*DataRowsApi* | [**api_data_rows_id_put**](docs/DataRowsApi.md#api_data_rows_id_put) | **PUT** /api/DataRows/{id} | 
*DataRowsApi* | [**api_data_rows_limit_get**](docs/DataRowsApi.md#api_data_rows_limit_get) | **GET** /api/DataRows/{limit} | 
*DataRowsApi* | [**api_data_rows_post**](docs/DataRowsApi.md#api_data_rows_post) | **POST** /api/DataRows | 
*HostedServiceApi* | [**api_hosted_service_get**](docs/HostedServiceApi.md#api_hosted_service_get) | **GET** /api/HostedService | 
*PyTorchApi* | [**api_py_torch_post**](docs/PyTorchApi.md#api_py_torch_post) | **POST** /api/PyTorch | 


## Documentation For Models

 - [CreateDataRowCommand](docs/CreateDataRowCommand.md)
 - [DataRowDto](docs/DataRowDto.md)
 - [DataRowDtoPaginatedList](docs/DataRowDtoPaginatedList.md)
 - [HostedServiceDto](docs/HostedServiceDto.md)
 - [UpdateDataRowCommand](docs/UpdateDataRowCommand.md)


## Documentation For Authorization

 All endpoints do not require authorization.

## Author




## Notes for Large OpenAPI documents
If the OpenAPI document is large, imports in ml_tracking.apis and ml_tracking.models may fail with a
RecursionError indicating the maximum recursion limit has been exceeded. In that case, there are a couple of solutions:

Solution 1:
Use specific imports for apis and models like:
- `from ml_tracking.api.default_api import DefaultApi`
- `from ml_tracking.model.pet import Pet`

Solution 2:
Before importing the package, adjust the maximum recursion limit as shown below:
```
import sys
sys.setrecursionlimit(1500)
import ml_tracking
from ml_tracking.apis import *
from ml_tracking.models import *
```



