# coding: utf-8

"""
    RankVectors API

    Intelligent internal linking optimization API using AI.   RankVectors helps you automatically discover and implement optimal internal links  across your website to improve SEO performance and user experience.  ## Key Features - **AI-Powered Analysis**: Uses OpenAI embeddings to find optimal linking opportunities - **Smart Crawling**: Automatically crawls and analyzes your website content - **Automated Implementation**: Implement links via webhooks or manual instructions - **Credit-Based System**: Pay-per-use model with transparent pricing - **Multi-Platform Support**: Works with any CMS or platform via REST API  ## Getting Started 1. Create a project with your website URL 2. Start a crawl to analyze your content 3. Generate AI-powered link suggestions 4. Implement suggestions via API or webhook 5. Track performance and manage credits  ## Authentication All API endpoints require authentication using your RankVectors API key. Include your API key in the `Authorization` header: ``` Authorization: Bearer YOUR_API_KEY ```  Get your API key from your RankVectors dashboard: Settings → API Keys 

    The version of the OpenAPI document: 1.2.0
    Contact: tj@rankvectors.com
    Generated by OpenAPI Generator (https://openapi-generator.tech)

    Do not edit the class manually.
"""  # noqa: E501


import unittest

from rankvectors.com.rankvectors.model.list_implementations200_response import ListImplementations200Response

class TestListImplementations200Response(unittest.TestCase):
    """ListImplementations200Response unit test stubs"""

    def setUp(self):
        pass

    def tearDown(self):
        pass

    def make_instance(self, include_optional) -> ListImplementations200Response:
        """Test ListImplementations200Response
            include_optional is a boolean, when False only required
            params are included, when True both required and
            optional params are included """
        # uncomment below to create an instance of `ListImplementations200Response`
        """
        model = ListImplementations200Response()
        if include_optional:
            return ListImplementations200Response(
                success = True,
                implementations = [
                    rankvectors.models.implementation.Implementation(
                        id = 'impl-123', 
                        status = 'success', 
                        platform = 'custom', 
                        implementation_method = 'api', 
                        credits_used = 1, 
                        created_at = '2025-01-15T10:00Z', 
                        completed_at = '2025-01-15T10:00:05Z', 
                        metadata = {"postId":456,"postUrl":"https://example.com/source"}, 
                        suggestion = rankvectors.models.suggestion.Suggestion(
                            id = 'sugg-123', 
                            project_id = 'proj-123', 
                            status = 'pending', 
                            relevance_score = 0.85, 
                            anchor_text = 'internal linking', 
                            context = 'Learn more about internal linking strategies.', 
                            source_page = rankvectors.models.page_info.PageInfo(
                                url = 'https://example.com/page', 
                                title = 'Page Title', 
                                description = 'Page description', 
                                word_count = 500, ), 
                            target_page = rankvectors.models.page_info.PageInfo(
                                url = 'https://example.com/page', 
                                title = 'Page Title', 
                                description = 'Page description', 
                                word_count = 500, ), 
                            reasoning = 'High semantic similarity between source and target content', 
                            created_at = '2025-01-15T10:00Z', 
                            updated_at = '2025-01-15T10:00Z', ), 
                        rollbacks = [
                            rankvectors.models.rollback.Rollback(
                                id = 'rollback-123', 
                                reason = 'Incorrect link placement', 
                                created_at = '2025-01-15T10:00Z', 
                                credits_refunded = 0.5, )
                            ], )
                    ],
                count = 25,
                filters = None
            )
        else:
            return ListImplementations200Response(
        )
        """

    def testListImplementations200Response(self):
        """Test ListImplementations200Response"""
        # inst_req_only = self.make_instance(include_optional=False)
        # inst_req_and_optional = self.make_instance(include_optional=True)

if __name__ == '__main__':
    unittest.main()
