Struct Descriptor 

pub struct Descriptor {
    pub nodes: Vec<Node>,
    pub env: Option<BTreeMap<String, EnvValue>>,
    pub communication: CommunicationConfig,
    pub deploy: Option<Deploy>,
    pub debug: Debug,
}

Dataflow Specification

The main configuration structure for defining a Dora dataflow. Dataflows are specified through YAML files that describe the nodes, their connections, and execution parameters.

Structure

A dataflow consists of:

• Nodes: The computational units that process data
• Communication: Optional communication configuration
• Deployment: Optional deployment configuration (unstable)
• Debug options: Optional development and debugging settings (unstable)

Example

nodes:
 - id: webcam
    operator:
      python: webcam.py
      inputs:
        tick: dora/timer/millis/100
      outputs:
        - image
  - id: plot
    operator:
      python: plot.py
      inputs:
        image: webcam/image

Fields

nodes: Vec<Node>

List of nodes in the dataflow

This is the most important field of the dataflow specification. Each node must be identified by a unique id:

Example

nodes:
  - id: foo
    path: path/to/the/executable
    # ... (see below)
  - id: bar
    path: path/to/another/executable
    # ... (see below)

For each node, you need to specify the path of the executable or script that Dora should run when starting the node. Most of the other node fields are optional, but you typically want to specify at least some inputs and/or outputs.

env: Option<BTreeMap<String, EnvValue>>

Global Environment variables inherited by all nodes (optional)

Example

env:
    MY_VAR: "my_var"

nodes:
  - id: foo
    path: path/to/the/executable
    # ... (see below)
  - id: bar
    path: path/to/another/executable
    # ... (see below)

Note that, If there is an env at the node level, Node level env will have more priority than the global env

communication: CommunicationConfig

Communication configuration (optional, uses defaults)

deploy: Option<Deploy>

Deployment configuration (optional, unstable)

debug: Debug

Debug options (optional, unstable)

Trait Implementations

impl Clone for Descriptor

fn clone(&self) -> Descriptor

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for Descriptor

fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Formats the value using the given formatter.

impl DescriptorExt for Descriptor

fn resolve_aliases_and_set_defaults( &self, ) -> Result<BTreeMap<NodeId, ResolvedNode>>

fn visualize_as_mermaid(&self) -> Result<String>

fn blocking_read(path: &Path) -> Result<Descriptor>

fn parse(buf: Vec<u8>) -> Result<Descriptor>

fn check(&self, working_dir: &Path) -> Result<()>

fn check_in_daemon( &self, working_dir: &Path, coordinator_is_remote: bool, ) -> Result<()>

impl<'de> Deserialize<'de> for Descriptor

fn deserialize<__D>( __deserializer: __D, ) -> Result<Descriptor, <__D as Deserializer<'de>>::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl JsonSchema for Descriptor

fn schema_name() -> Cow<'static, str>

The name of the generated JSON Schema.

fn schema_id() -> Cow<'static, str>

Returns a string that uniquely identifies the schema produced by this type.

fn json_schema(generator: &mut SchemaGenerator) -> Schema

Generates a JSON Schema for this type.

fn inline_schema() -> bool

Whether JSON Schemas generated for this type should be included directly in parent schemas, rather than being re-used where possible using the $ref keyword.

impl Serialize for Descriptor

fn serialize<__S>( &self, __serializer: __S, ) -> Result<<__S as Serializer>::Ok, <__S as Serializer>::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.