Stefan Wolf <******@****.***> 1633938695 +0200

	line, col int
	Key       string `yaml:"key" json:"key"`
	Value     string `yaml:"value" json:"value"`
}

var _ yaml.Unmarshaler = &BatchJobKV{}

// UnmarshalYAML - BatchJobKV extends default unmarshal to extract line, col information.
func (kv *BatchJobKV) UnmarshalYAML(val *yaml.Node) error {
	type jobKV BatchJobKV
	var tmp jobKV
	err := val.Decode(&tmp)
	if err != nil {
		return err
	}
	*kv = BatchJobKV(tmp)

		Creds: credentials.NewStaticV4("access-key", "secret-key", ""),
	})
	if err != nil {
		log.Fatalln(err)
	}

	var opts minio.GetObjectOptions

	// Add extract header to request:
	opts.Set("x-minio-extract", "true")

	// Download API.md from the archive
	rd, err := s3Client.GetObject(context.Background(), "your-bucket", "path/to/file.zip/data.csv", opts)
	if err != nil {
		log.Fatalln(err)
	}

            Extractor extractor = StringUtil.isBlank(mimeType) ? null : extractorFactory.getExtractor(mimeType);
            if (extractor == null) {
                final String detectedMimeType = getMimeType(out);
                extractor = extractorFactory.getExtractor(detectedMimeType);
                if (extractor == null) {
                    if (logger.isDebugEnabled()) {

    signatureVersion: 'v4'
});

// List all contents stored in the zip archive
s3.listObjectsV2({Bucket : 'your-bucket', Prefix: 'path/to/file.zip/'}).
    on('build', function(req) { req.httpRequest.headers['X-Minio-Extract'] = 'true'; }).
    send(function(err, data) {
        if (err) {
            console.log("Error", err);
        } else {
            console.log("Success", data);
        }
    });

    # Enter the output directory.
    mkdir -p "$(dirname "$2")"
    pushd "$(dirname "$2")"

    # Download and extract the binary to the output directory.
    echo "Downloading ${SIDECAR}: $1 to $2"
    time ${DOWNLOAD_COMMAND} --header "${AUTH_HEADER:-}" "$1" |\
      tar --extract --gzip --strip-components=3 --to-stdout > "$2"
    chmod +x "$2"

# Returns:
#   None
function cp_normalized_srcjar() {
  src_jar="$1"
  dest_jar="$2"
  tmp_dir=$(mktemp -d)
  cp "${src_jar}" "${tmp_dir}/orig.jar"
  pushd "${tmp_dir}"
  # Extract any src/ files
  jar -xf "${tmp_dir}/orig.jar" src/
  # Extract any org/ files under src/main/java
  (mkdir -p src/main/java && cd src/main/java && jar -xf "${tmp_dir}/orig.jar" org/)
  # Repackage src/
  jar -cMf "${tmp_dir}/new.jar" src
  popd

Using the below example document:
<img width="85%" src="https://bradley.codes/static/img/jstream-levels.gif" alt="jstream"/>

we can choose to extract and act only the objects within the top-level array:
```go
f, _ := os.Open("input.json")
decoder := jstream.NewDecoder(f, 1) // extract JSON values at a depth level of 1
for mv := range decoder.Stream() {
  fmt.Printf("%v\n ", mv.Value)
}
```

output:
```

        {
            "detail": [
                {
                    "type": "model_attributes_type",
                    "loc": ["body"],
                    "msg": "Input should be a valid dictionary or object to extract fields from",
                    "input": "name=Foo&price=50.5",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {

        {
            "detail": [
                {
                    "type": "model_attributes_type",
                    "loc": ["body"],
                    "msg": "Input should be a valid dictionary or object to extract fields from",
                    "input": "name=Foo&price=50.5",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {