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docs(ingest): add docs on pydantic compatibility (#11423)

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Harshal Sheth 2024-09-20 13:22:15 -07:00 committed by GitHub
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5
docs/cli.md
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@ -34,9 +34,9 @@ datahub init
# authenticate your datahub CLI with your datahub instance
```
If you run into an error, try checking the [_common setup issues_](../metadata-ingestion/developing.md#Common-setup-issues).
If you run into an error, try checking the [_common setup issues_](../metadata-ingestion/developing.md#common-setup-issues).
Other installation options such as installation from source and running the cli inside a container are available further below in the guide [here](#alternate-installation-options)
Other installation options such as installation from source and running the cli inside a container are available further below in the guide [here](#alternate-installation-options).
## Starter Commands
@ -672,7 +672,6 @@ Old Entities Migrated = {'urn:li:dataset:(urn:li:dataPlatform:hive,logging_event
### Using docker
[![Docker Hub](https://img.shields.io/docker/pulls/acryldata/datahub-ingestion?style=plastic)](https://hub.docker.com/r/acryldata/datahub-ingestion)
[![datahub-ingestion docker](https://github.com/acryldata/datahub/workflows/datahub-ingestion%20docker/badge.svg)](https://github.com/acryldata/datahub/actions/workflows/docker-ingestion.yml)
If you don't want to install locally, you can alternatively run metadata ingestion within a Docker container.
We have prebuilt images available on [Docker hub](https://hub.docker.com/r/acryldata/datahub-ingestion). All plugins will be installed and enabled automatically.

14
metadata-ingestion/developing.md
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@ -55,7 +55,6 @@ logger.debug("this is the sample debug line")
#3. click on the `log` option
```
> **P.S. if you are not able to see the log lines, then restart the `airflow scheduler` and rerun the DAG**
### (Optional) Set up your Python environment for developing on Dagster Plugin
@ -70,6 +69,7 @@ datahub version # should print "DataHub CLI version: unavailable (installed in
```
### (Optional) Set up your Python environment for developing on Prefect Plugin
From the repository root:
```shell
@ -127,6 +127,18 @@ This sometimes happens if there's a version mismatch between the Kafka's C libra
</details>
<details>
<summary>Conflict: acryl-datahub requires pydantic 1.10</summary>
The base `acryl-datahub` package supports both Pydantic 1.x and 2.x. However, some of our specific sources require Pydantic 1.x because of transitive dependencies.
If you're primarily using `acryl-datahub` for the SDKs, you can install `acryl-datahub` and some extras, like `acryl-datahub[sql-parser]`, without getting conflicts related to Pydantic versioning.
We recommend not installing full ingestion sources into your main environment (e.g. avoid having a dependency on `acryl-datahub[snowflake]` or other ingestion sources).
Instead, we recommend using UI-based ingestion or isolating the ingestion pipelines using [virtual environments](https://docs.python.org/3/library/venv.html). If you're using an orchestrator, they often have first-class support for virtual environments - here's an [example for Airflow](./schedule_docs/airflow.md).
</details>
### Using Plugins in Development
The syntax for installing plugins is slightly different in development. For example: