Deduplication

Create Ai Ready Slice

Create an AI-ready data slice by tagging duplicate files as redundant.

Ensures the ‘Data Quality Status’ tag exists
Tags non-representative duplicate files as ‘redundant’, but only when the caller chose to exclude ‘redundant’ (see exclude_statuses) — tagging is a persistent side effect and must follow the caller’s selection rather than running unconditionally
Creates a data slice with condition excluding the caller’s chosen Data Quality Status values (see exclude_statuses)

POST

dedup

create_slice

Python

# pip install deasy-sdk
import os
from deasy import DeasyClient

client = DeasyClient(
    base_url=os.environ["UNSTRUCTURED_CLIENT_BASE_URL"],
    username=os.environ["UNSTRUCTURED_USERNAME"],
    password=os.environ["UNSTRUCTURED_PASSWORD"],
    auth_method="basic",
)

response = client.dedup.create_slice(
    data_connector_name="example_data_connector_name",
    slice_name="example_slice_name",
)
print(response)

{
  "detail": "<string>"
}

{
  "detail": "<string>"
}

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>",
      "input": "<unknown>",
      "ctx": {}
    }
  ]
}

{
  "detail": "<string>"
}

{
  "detail": "<string>"
}

Authorizations

Authorization

string

header

required

Basic authentication header of the form Basic <encoded-value>, where <encoded-value> is the base64-encoded string username:password.

Body

application/json

data_connector_name

string

required

slice_name

string

required

dataslice_id

string | null

description

string

default:""

rejected_group_ids

string[]

rejected_file_ids

string[]

exclude_statuses

string[] | null

require_safe

boolean

default:false

Response

Successful Response

⌘I

Python

# pip install deasy-sdk
import os
from deasy import DeasyClient

client = DeasyClient(
    base_url=os.environ["UNSTRUCTURED_CLIENT_BASE_URL"],
    username=os.environ["UNSTRUCTURED_USERNAME"],
    password=os.environ["UNSTRUCTURED_PASSWORD"],
    auth_method="basic",
)

response = client.dedup.create_slice(
    data_connector_name="example_data_connector_name",
    slice_name="example_slice_name",
)
print(response)

{
  "detail": "<string>"
}

{
  "detail": "<string>"
}

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>",
      "input": "<unknown>",
      "ctx": {}
    }
  ]
}

{
  "detail": "<string>"
}

{
  "detail": "<string>"
}

Overview

Data Connectors

Tags

Taxonomies

Metadata

Data Slices

Deduplication

Destinations

Projects

Workflows

Versioning

Task Tracking

Create Ai Ready Slice

Authorizations

Body

Response