Update apache-airflow requirement from <3,>=2.8 to >=2.8,<4 in the python group

[dependabot]

Updates the requirements on apache-airflow to permit the latest version.
Updates apache-airflow to 3.3.1

Release notes

Sourced from apache-airflow's releases.

Apache Airflow 3.3.1

📦 PyPI: https://pypi.org/project/apache-airflow/3.3.1/ 📚 Docs: https://airflow.apache.org/docs/apache-airflow/3.3.1/ 🛠 Release Notes: https://airflow.apache.org/docs/apache-airflow/3.3.1/release_notes.html 🐳 Docker Image: "docker pull apache/airflow:3.3.1" 🚏 Constraints: https://github.com/apache/airflow/tree/constraints-3.3.1

Significant Changes

Pandas 3 changes how DataFrame XComs are stored and read back (#71169)

pandas 3 exposes its public classes from the pandas namespace, so a DataFrame is qualified as pandas.DataFrame instead of pandas.core.frame.DataFrame. XComs record that name alongside the serialized value, so the name written into the metadata database depends on the pandas version of the component that pushed the value. Airflow registers both names, and a DataFrame written by either pandas version can be read by either -- no configuration change is needed, and existing XComs stay readable.

What you should do:

• Roll this Airflow version out to every component before pandas 3 reaches any of them -- workers in particular. A component that predates this change cannot read a DataFrame XCom written under pandas 3, and fails the pull with:

  .. code-block:: text

  ImportError: pandas.DataFrame was not found in allow list for deserialization imports.
  To allow it, add it to allowed_deserialization_classes in the configuration
  

  The message points at configuration, but the allow list is not the cause and changing it does not help. The rows are not corrupt: they become readable again as soon as the reader is upgraded.

• Treat a downgrade as a one-way door for those XComs. Rolling back to an Airflow version without this change strands any DataFrame XCom written while on pandas 3, with the same error, until you roll forward again.

• Review Dags that inspect the dtypes of a pulled DataFrame. The pandas version of the reader determines what a pulled DataFrame looks like, not the version that wrote it. Under pandas 3, a column of strings comes back as str rather than object, and its missing values come back as nan rather than None. Values are unchanged, but downstream code that branches on dtype == "object", checks cells with is None, or compares against a reference frame with DataFrame.equals() can behave differently after the upgrade.

Fix 2.x to 3.0+ upgrade failure when a custom Dag bundle is configured (#70994)

The 0082_3_1_0_make_bundle_name_not_nullable migration assigned every legacy row bundle_name='dags-folder', so triggering a DagRun raised ``Requested bundle 'dags-folder' is

... (truncated)

Commits

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[github-actions]

Test Results

286 tests  ±0   280 ✅ ±0   7s ⏱️ ±0s
  1 suites ±0     6 💤 ±0 
  1 files   ±0     0 ❌ ±0 

Results for commit c5d1578. ± Comparison against base commit 7dae002.

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