Metadata-Version: 2.1
Name: ml-tracking-api
Version: 1.2.2
Summary: REST ML-AI API
Home-page: https://github.com/EimantasN/Equusight_BackEnd
Author: Eimantas Noreika
Author-email: noreika.eimantas@gmail.com
License: UNKNOWN
Description: # ml-tracking-api
        No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator)
        
        The `ml-tracking` package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
        
        - API version: v1
        - Package version: 1.2.2
        - Build date: 2021-07-30T17:37:40.743Z[GMT]
        - Build package: org.openapitools.codegen.languages.PythonClientCodegen
        
        ## Requirements.
        
        Python >= 3.6
        
        ## Installation & Usage
        
        This python library package is generated without supporting files like setup.py or requirements files
        
        To be able to use it, you will need these dependencies in your own package that uses this library:
        
        * urllib3 >= 1.25.3
        * python-dateutil
        
        ## Getting Started
        
        In your own code, to use this library to connect and interact with ml-tracking-api,
        you can 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**](ml-tracking/docs/DataRowsApi.md#api_data_rows_get) | **GET** /api/DataRows | 
        *DataRowsApi* | [**api_data_rows_id_delete**](ml-tracking/docs/DataRowsApi.md#api_data_rows_id_delete) | **DELETE** /api/DataRows/{id} | 
        *DataRowsApi* | [**api_data_rows_id_put**](ml-tracking/docs/DataRowsApi.md#api_data_rows_id_put) | **PUT** /api/DataRows/{id} | 
        *DataRowsApi* | [**api_data_rows_limit_get**](ml-tracking/docs/DataRowsApi.md#api_data_rows_limit_get) | **GET** /api/DataRows/{limit} | 
        *DataRowsApi* | [**api_data_rows_post**](ml-tracking/docs/DataRowsApi.md#api_data_rows_post) | **POST** /api/DataRows | 
        *HostedServiceApi* | [**api_hosted_service_get**](ml-tracking/docs/HostedServiceApi.md#api_hosted_service_get) | **GET** /api/HostedService | 
        *PyTorchApi* | [**api_py_torch_after_epoch_post**](ml-tracking/docs/PyTorchApi.md#api_py_torch_after_epoch_post) | **POST** /api/PyTorch/AfterEpoch | 
        *PyTorchApi* | [**api_py_torch_iteration_post**](ml-tracking/docs/PyTorchApi.md#api_py_torch_iteration_post) | **POST** /api/PyTorch/Iteration | 
        *PyTorchApi* | [**api_py_torch_register_post**](ml-tracking/docs/PyTorchApi.md#api_py_torch_register_post) | **POST** /api/PyTorch/Register | 
        
        
        ## Documentation For Models
        
         - [CreateDataRowCommand](ml-tracking/docs/CreateDataRowCommand.md)
         - [DataRowDto](ml-tracking/docs/DataRowDto.md)
         - [DataRowDtoPaginatedList](ml-tracking/docs/DataRowDtoPaginatedList.md)
         - [EpochUpdateCommand](ml-tracking/docs/EpochUpdateCommand.md)
         - [HostedServiceDto](ml-tracking/docs/HostedServiceDto.md)
         - [IterationUpdateCommand](ml-tracking/docs/IterationUpdateCommand.md)
         - [RegisterModelRunCommand](ml-tracking/docs/RegisterModelRunCommand.md)
         - [UpdateDataRowCommand](ml-tracking/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 *
        ```
        
        
Keywords: OpenAPI,OpenAPI-Generator,REST ML-AI API
Platform: UNKNOWN
Requires-Python: >=3.6
Description-Content-Type: text/markdown
