dlt-fabric

dlt-fabric is a maintained fork of dlt with fixes for the Microsoft Fabric Warehouse destination and the related MS SQL family of destinations (mssql, synapse).

dlt's Fabric, mssql, and synapse destinations have open issues around authentication and reliability that are not yet released upstream. This fork carries the fixes on top of each dlt release so they can be used today, while the changes work their way through upstream review.

What this fork carries

This fork applies the following changes on top of the corresponding upstream dlt release:

• dlt-hub/dlt#4147: Microsoft Entra ID authentication for the mssql, synapse, and fabric destinations, an injectable pre-fetched access_token or externally constructed azure_credential, and authentication = "fab_notebookutils" for pipelines running inside a Fabric notebook. Supersedes the closed #4140.
• dlt-hub/dlt#4141: migration of the mssql, synapse, and fabric destinations from pyodbc to the mssql-python driver, which bundles its own client libraries so no system ODBC install is needed.
• dlt-hub/dlt#4142: a staging-optimized replace strategy for the Fabric destination, including a fix that makes concurrent multi-table-chain loads safe.
• dlt-hub/dlt#4258: a mssql_arrow backend for sql_database that uses mssql-python's native Arrow C Data Interface for zero-copy batch extraction.
• dlt-hub/dlt#4259: correct nvarchar-to-varchar length scaling in the Fabric type mapper (character precision x 4 for UTF-8 byte semantics).
• dlt-hub/dlt#4260: allow time columns through the Parquet load path on Fabric (the inherited Synapse rejection does not apply).
• dlt-hub/dlt#4261: map SQL Server MONEY and SMALLMONEY types to decimal(19,4) and decimal(10,4) in sql_database schema inference.
• dlt-hub/dlt#4275: an Azure Key Vault configuration provider for loading secrets and config from Azure Key Vault, with DefaultAzureCredential fallback and a dlt[azure_key_vault] extra.
• dlt-hub/dlt#4302: route OneLake filesystem configurations to a dedicated client that strips trailing separators before directory probes, which OneLake answers with 403 AuthenticationFailed.
• dlt-hub/dlt#4307: widen tinyint to smallint in the Fabric type mapper, since Fabric Warehouse has no tinyint and rejects the inherited SQL Server mapping.

These are proposed as pull requests against upstream dlt. Until they are merged and released, this fork is rebased onto each new dlt release to stay current.

How the branches fit together

Everything is developed as small branches that each become one upstream pull request. Two of them are stacked, because their content genuinely depends on another PR; the rest sit directly on devel.

upstream/devel
├── feat/mssql-access-token-credential         #4147  Entra ID auth, access_token/azure_credential, fab_notebookutils
│   ├── feat/azure-key-vault-provider          #4275  AzureKeyVaultProvider (uses the NotebookUtils credential)
│   └── feat/mssql-python-driver               #4141  pyodbc -> mssql-python migration
│       └── feat/2-mssql-python-arrow-batches  #4258  mssql_arrow backend
├── feat/fabric-staging-optimized              #4142  staging-optimized replace via DDL transactions
├── fix/3-nvarchar-utf8-length                 #4259
├── fix/4-fabric-time-parquet                  #4260
├── fix/5-money-decimal-precision              #4261
├── fix/8-onelake-directory-probes             #4302
└── fix/4306-fabric-tinyint-smallint           #4307

#4141 is stacked on #4147 rather than branched from devel so the Entra ID authentication exists once. When it was branched independently, both carried their own copy of the same two auth commits, which meant every change had to be made twice and the integration branch inherited the duplication.

GitHub cannot express this as a real stacked PR: a pull request's base must live in the upstream repository, and these branches live in the fork. Each PR body therefore names the PR it depends on, and the diff shown on GitHub includes the parent's commits until the parent lands.

Rebuilding the integration and release branches

integrated-all-prs is every PR merged together, for testing the combination. It starts from devel. Rebuild it with plain merges; the stacking means the two leaves carry everything below them:

git checkout integrated-all-prs && git reset --hard devel
git merge --no-ff feat/2-mssql-python-arrow-batches   # brings #4147 and #4141 along
git merge --no-ff feat/azure-key-vault-provider       # shares #4147, so this merges cleanly
git merge --no-ff feat/fabric-staging-optimized
git merge --no-ff fix/3-nvarchar-utf8-length
git merge --no-ff fix/4-fabric-time-parquet
git merge --no-ff fix/5-money-decimal-precision
git merge --no-ff fix/8-onelake-directory-probes
git merge --no-ff fix/4306-fabric-tinyint-smallint

Conflicts here are almost always two branches appending tests to the same file; keep both sides.

dlt-fabric is the published branch and starts from upstream/master, the latest stable release. Do not merge integrated-all-prs into it: that branch sits on devel, so merging it would drag every unreleased devel commit into the release. Cherry-pick the feature commits instead, which is exactly the set that is in the integration branch but not in devel:

git checkout dlt-fabric && git reset --hard upstream/master
git rev-list --reverse --no-merges devel..integrated-all-prs | while read c; do git cherry-pick "$c"; done
git cherry-pick <package as dlt-fabric> <resolve version and package name>

Verify afterwards that nothing from devel slipped in:

git rev-list upstream/master..dlt-fabric | while read c; do
  git merge-base --is-ancestor "$c" devel && git log -1 --oneline "$c"
done   # must print nothing

Versioning and release

pyproject.toml sets name = "dlt-fabric" and the version of the upstream release this fork sits on, with a .postN suffix per fork release. dlt/version.py resolves the distribution name so dlt.__version__ keeps working under the renamed package. Publish with make publish-library.

Installation

dlt-fabric is a drop-in replacement for dlt. Install it instead of the upstream package:

pip install dlt-fabric
# or
uv add dlt-fabric

Then use it exactly as you would use dlt:

import dlt

Both packages install the same dlt import path, so dlt-fabric cannot be installed alongside the upstream dlt package in the same environment.

Documentation

This fork does not maintain separate documentation. For everything beyond the fixes listed above, the upstream resources apply directly:

• Documentation and usage: https://dlthub.com/docs
• Upstream project: https://github.com/dlt-hub/dlt