# offset of in the current version of ubp.
# See https://github.com/protocolbuffers/upb/blob/9effcbcb27f0a665f9f345030188c0b291e32482/upb/upb.c#L183.
build --copt=-Wno-gnu-offsetof-extensions

# Store performance profiling log in the mounted artifact directory.
# The profile can be viewed by visiting chrome://tracing in a Chrome browser.
# See https://docs.bazel.build/versions/main/skylark/performance.html#performance-profiling

MinIO versioning is designed to keep multiple versions of an object in one bucket. For example, you could store `spark.csv` (version `ede336f2`) and `spark.csv` (version `fae684da`) in a single bucket. Versioning protects you from unintended overwrites, deletions, protect objects with retention policies.

development and evaluation. For production clusters, deploy a [Distributed](https://min.io/docs/minio/container/operations/install-deploy-manage/deploy-minio-single-node-multi-drive.html) MinIO deployment.

MinIO needs a persistent volume to store configuration and application data. For testing purposes, you can launch MinIO by simply passing a directory (`/data` in the example below). This directory gets created in the container filesystem at the time of container start. But all the data is...

```Python hl_lines="18-20"
{!../../../docs_src/sql_databases_peewee/sql_app/main.py!}
```

# > target platform.
# See also https://docs.bazel.build/versions/master/guide.html#build-configurations-and-cross-compilation
build --distinct_host_configuration=false

# Store performance profiling log in the mounted artifact directory.
# The profile can be viewed by visiting chrome://tracing in a Chrome browser.
# See https://docs.bazel.build/versions/main/skylark/performance.html#performance-profiling

  // More info: https://kubernetes.io/docs/concepts/overview/working-with-objects/labels
  // +optional
  map<string, string> labels = 11;

  // Annotations is an unstructured key value map stored with a resource that may be
  // set by external tools to store and retrieve arbitrary metadata. They are not
  // queryable and should be preserved when modifying objects.

Doing that in separated functions that don't share logic or variables together is more difficult as you would need to store values in global variables or similar tricks.

Because of that, it's now recommended to instead use the `lifespan` as explained above.

## Technical Details

Just a technical detail for the curious nerds. 🤓

```Python
commons: Annotated[dict, Depends(common_parameters)]
```

But because we are using `Annotated`, we can store that `Annotated` value in a variable and use it in multiple places:

=== "Python 3.10+"

    ```Python hl_lines="12  16  21"
    {!> ../../../docs_src/dependencies/tutorial001_02_an_py310.py!}
    ```

### Project file structure

Let's say your project file structure looks like this:

```
.
├── app
│   ├── __init__.py
│   ├── main.py
```

Now create a directory to store those static files.

Your new file structure could look like this:

```
.
├── app
│   ├── __init__.py
│   ├── main.py
└── static/
```

### Download the files

  fun receiveData(
    source: BufferedSource,
    length: Int,
  ) {
    lock.assertNotHeld()

    this.source.receive(source, length.toLong())
  }

  /** Accept headers from the network and store them until the client calls [takeHeaders]. */
  fun receiveHeaders(
    headers: Headers,
    inFinished: Boolean,
  ) {
    lock.assertNotHeld()

    val open: Boolean
    this.withLock {