From 33f93a344889c63258e0c73e240fa15c27d7f52d Mon Sep 17 00:00:00 2001 From: David Silaghi Date: Wed, 5 Aug 2026 16:16:44 +0300 Subject: [PATCH] [MCC-1535269] Python SDK - Update README-v1.1.0 output sections for canonical envelope --- readme/README-v1.1.0.md | 24 +++++++++++++----------- 1 file changed, 13 insertions(+), 11 deletions(-) diff --git a/readme/README-v1.1.0.md b/readme/README-v1.1.0.md index eadf3ba..a19c464 100644 --- a/readme/README-v1.1.0.md +++ b/readme/README-v1.1.0.md @@ -1,7 +1,7 @@ # DataConnect Python Library v1.1.0 The DataConnect Python library provides a Python client for connecting to Medidata DataConnect and retrieving relevant data programmatically. -To use this library, you must have a valid iMedidata account and access to required building blocks in the Medidata Platform. For details, see the Medidata [Knowledge Hub](https://learn.medidata.com/en-US/bundle/data-connect/page/developer_center.html). +To use this library, you must have a valid iMedidokaata account and access to required building blocks in the Medidata Platform. For details, see the Medidata [Knowledge Hub](https://learn.medidata.com/en-US/bundle/data-connect/page/developer_center.html). ## Table of Contents @@ -213,11 +213,13 @@ dry_publish(project_token, dataset_name, key_columns, source_datasets, data, dat #### Output -Returns the result of publishing validations as a list containing clean, server-side data-quality metrics: -* **`valid_record_count`**: Number of clean records matching platform requirements (always ≥ 0). -* **`duplicate_record_count`**: Gross duplicate records identified across the payload composite keys. -* **`invalid_record_count`**: Number of records containing validation errors or missing required keys. -* **`invalid_records`**: A data frame containing the rows that failed validation. +Returns a result object with the following attributes: +* **`success`**: `True` if all validation checks passed, `False` otherwise. +* **`metadata`**: Dataset identity (`dataset_name`, `dataset_version`, `column_count`). +* **`metrics`**: Row counts — `total_valid_rows`, `total_invalid_rows`, `total_duplicate_rows`. +* **`checks`**: Validation outcomes — `schema_is_valid`, `config_is_valid`, `date_formats_are_valid`, `dataset_is_valid`, `invalid_datetime_formats`. +* **`errors`**: List of validation error messages, if any. +* **`invalid_records`**: A data frame containing the rows that failed validation, or `None`. #### Data Validations @@ -259,11 +261,11 @@ publish(project_token, dataset_name, key_columns, source_datasets, data, datetim #### Output -Returns the status of publish as a list containing the final backend execution results: -* **`valid_record_count`**: Total structural records written successfully to the destination table. -* **`duplicate_record_count`**: Gross row duplication counters. -* **`invalid_record_count`**: Total failure rows excluded during the network stream. -* **`invalid_records`**: A data frame containing the rows that failed validation. +Returns a result object with the following attributes: +* **`success`**: `True` if the dataset was published successfully. +* **`metadata`**: Dataset identity (`dataset_name`, `dataset_version`, `column_count`, `dataset_uuid`). +* **`metrics`**: Row counts — `total_valid_rows`, `total_invalid_rows`, `total_duplicate_rows`. +* **`invalid_records`**: A data frame containing any rows that failed validation, or `None`. #### Data Validations