From bde254eb681e81b0362ecddd85e81d4f36bea3fd Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Morten=20Gr=C3=B8nbech?= Date: Tue, 31 Mar 2026 16:37:02 +0200 Subject: [PATCH 1/2] docs: encourage higher level tools for interacting with data modeling --- docs/source/data_modeling.rst | 11 +++++++++++ docs/source/transformations.rst | 2 ++ 2 files changed, 13 insertions(+) diff --git a/docs/source/data_modeling.rst b/docs/source/data_modeling.rst index af65a518cb..5f49aa8dce 100644 --- a/docs/source/data_modeling.rst +++ b/docs/source/data_modeling.rst @@ -1,5 +1,16 @@ Data Modeling ============= +.. note:: + The data modeling section of the SDK provides low level access to the data modeling API. Most users should use on the higher level libraries described in the sections below. + +Consuming data models +--------------------- +If you are consuming data from data models it is recommended to use `Cognite Pygen `_. unless you need the full flexibility of the SDK. `pygen` provides a high-level, user-friendly interface for working with data models, and it handles many of the complexities of the underlying API for you. +The same applies if you are need to write or update instances in data model in a dynamic way that cannot be handled by :ref:`transformations`. + +Building data models +-------------------- +If you are building data models, it is recommended to use `Cognite Toolkit `_ to design and maintain your data models. `Cognite Toolkit` provides a high-level interface for defining and managing data models, and it includes features such as versioning, testing, and deployment tools that can help you build robust and maintainable data models. Data Models ------------ diff --git a/docs/source/transformations.rst b/docs/source/transformations.rst index 1f01ef3a25..701c586d29 100644 --- a/docs/source/transformations.rst +++ b/docs/source/transformations.rst @@ -1,3 +1,5 @@ +.. _transformations: + Transformations =============== From 7b288a1b0c9e8525ac6353e704d9ac55aafe354f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Morten=20Gr=C3=B8nbech?= <42722577+MortGron@users.noreply.github.com> Date: Tue, 31 Mar 2026 16:41:54 +0200 Subject: [PATCH 2/2] Apply suggestions from code review Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> --- docs/source/data_modeling.rst | 15 +++++++++++---- 1 file changed, 11 insertions(+), 4 deletions(-) diff --git a/docs/source/data_modeling.rst b/docs/source/data_modeling.rst index 5f49aa8dce..320fcc664b 100644 --- a/docs/source/data_modeling.rst +++ b/docs/source/data_modeling.rst @@ -1,16 +1,23 @@ Data Modeling ============= .. note:: - The data modeling section of the SDK provides low level access to the data modeling API. Most users should use on the higher level libraries described in the sections below. + The data modeling section of the SDK provides low level access to the data modeling API. Most users should use + the higher level libraries described in the sections below. Consuming data models --------------------- -If you are consuming data from data models it is recommended to use `Cognite Pygen `_. unless you need the full flexibility of the SDK. `pygen` provides a high-level, user-friendly interface for working with data models, and it handles many of the complexities of the underlying API for you. -The same applies if you are need to write or update instances in data model in a dynamic way that cannot be handled by :ref:`transformations`. +If you are consuming data from data models, it is recommended to use `Cognite Pygen `_ +unless you need the full flexibility of the SDK. `pygen` provides a high-level, user-friendly interface for working +with data models, and it handles many of the complexities of the underlying API for you. +The same applies if you need to write or update instances in a data model in a dynamic way that cannot be handled by +:ref:`transformations`. Building data models -------------------- -If you are building data models, it is recommended to use `Cognite Toolkit `_ to design and maintain your data models. `Cognite Toolkit` provides a high-level interface for defining and managing data models, and it includes features such as versioning, testing, and deployment tools that can help you build robust and maintainable data models. +If you are building data models, it is recommended to use `Cognite Toolkit `_ +to design and maintain your data models. `Cognite Toolkit` provides a high-level interface for defining and managing +data models, and it includes features such as versioning, testing, and deployment tools that can help you build robust +and maintainable data models. Data Models ------------