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v0.20.x
  • Introduction to AI Testing
  • Welcome to Distributional
  • Motivation
  • What is AI Testing?
  • Stages in the AI Software Development Lifecycle
    • Components of AI Testing
  • Distributional Testing
  • Getting Access to Distributional
  • Learning about Distributional
    • The Distributional Framework
    • Defining Tests in Distributional
      • Automated Production test creation & execution
      • Knowledge-based test creation
      • Comprehensive testing with Distributional
    • Reviewing Test Sessions and Runs in Distributional
      • Reviewing and recalibrating automated Production tests
      • Insights surfaced elsewhere on Distributional
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    • Data in Distributional
      • The flow of data
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      • Uploading data to Distributional
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  • Using Distributional
    • Getting Started
    • Access
      • Organization and Namespaces
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      • Tokens
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    • Testing
      • Creating Tests
        • Test Page
        • Test Drawer Through Shortcuts
        • Test Templates
        • SDK
      • Defining Assertions
      • Production Testing
        • Auto-Test Generation
        • Recalibration
        • Notable Results
        • Dynamic Baseline
      • Testing Strategies
        • Test That a Given Distribution Has Certain Properties
        • Test That Distributions Have the Same Statistics
        • Test That Columns Are Similarly Distributed
        • Test That Specific Results Have Matching Behavior
        • Test That Distributions Are Not the Same
      • Executing Tests
        • Manually Running Tests Via UI
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      • Reviewing Tests
      • Using Filters
        • Filters in the Compare Page
        • Filters in Tests
    • Python SDK
      • Quick Start
      • Functions
        • login
        • Project
          • create_project
          • copy_project
          • export_project_as_json
          • get_project
          • get_or_create_project
          • import_project_from_json
        • Run Config
          • create_run_config
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          • get_column_results
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          • close_run
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          • get_run
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          • create_run_query
          • get_run_query
          • set_run_as_baseline
          • set_run_query_as_baseline
        • Test Session
          • create_test_session
      • Objects
        • Project
        • RunConfig
        • Run
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        • TestSession
        • TestRecalibrationSession
        • TestGenerationSession
        • ResultData
      • Experimental Functions
        • create_test
        • get_tests
        • get_test_sessions
        • wait_for_test_session
        • get_or_create_tag
        • prepare_incomplete_test_spec_payload
        • create_test_recalibration_session
        • wait_for_test_recalibration_session
        • create_test_generation_session
        • wait_for_test_generation_session
      • Eval Module
        • Quick Start
        • Application Metric Sets
        • How-To / FAQ
        • LLM-as-judge and Embedding Metrics
        • RAG / Question Answer Example
        • Eval Module Functions
          • Index of functions
          • eval
          • eval.metrics
    • Notifications
    • Release Notes
  • Tutorials
    • Instructions
    • Hello World (Sentiment Classifier)
    • Trading Strategy
    • LLM Text Summarization
      • Setting the Scene
      • Prompt Engineering
      • Integration testing for text summarization
      • Practical considerations
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On this page
  • Parameters
  • Returns
  • Examples

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  1. Using Distributional
  2. Python SDK
  3. Functions
  4. Project

import_project_from_json

Create a new dbnl Project from a JSON object

dbnl.import_project_from_json(
    *,
    params: dict[str, Any],
) -> :

Parameters

Arguments
Description

params

Returns

Type
Description

The newly created dbnl Project.

Examples

import dbnl
dbnl.login()


proj1 = dbnl.get_or_create_project(name="test_proj1")
export_json = dbnl.export_project_as_json(project=proj1)
export_json["project"]["name"] = "test_proj2"
proj2 = dbnl.import_project_from_json(params=export_json)

assert proj2.name == "test_proj2"
Previousget_or_create_projectNextRun Config

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JSON object representing the Project, generally based on a exported via . Example:

{
    "project": {
        "name": "My Project",
        "description": "This is my project."
    },
    "tags": [
        {
            "name": "my-tag",
            "description" :"This is my tag."
        }
    ],
    "test_specs": [
        {
            "assertion": { "name": "less_than", "params": { "other": 0.5 } },
            "description": "Testing the difference in the example statistic",
            "name": "Gr.0: Non Parametric Difference: Example_Statistic",
            "statistic_inputs": [
                {
                    "select_query_template": {
                        "filter": null,
                        "select": "{EXPERIMENT}.Example_Statistic"
                    }
                },
                {
                    "select_query_template": {
                        "filter": null,
                        "select": "{BASELINE}.Example_Statistic"
                    }
                }
            ],
            "statistic_name": "my_stat",
            "statistic_params": {},
            "tag_names": ["my-tag"]
        }
    ]
}
Project
export_project_as_json
Project