* Multithreaded Python API and Pylot Example (#18)
* Refactoring for multithreading
* Refactoring code in order to use MemoryView
* Resolving multi output by casting Python output type
* Adding Python example runner
* Adding Rayon ThreadPool for CPU bound multithreading
* Adding benches
* Small Refactoring of Python Binding
* Adding documentation to Pylot Demo
* Removing cloning states data using RwLock
* Refactoring Servers to pass messages through tokio channels
* Removing unwrap when possible
* Splitting Zenoh function into separate module
* Refactoring Zenoh into a struct
* Adding several Python fix
* Fix eyre issue
* Adding docker for ease of build
* Fixing docker problem
* Reduce the frequency of source
* Adding better Python Operator
* Improving carla visualisation capabilities
* Enabling better visualisation
* adding object trajectory
* Improving planning
* Refactoring Python
* Adding control operator
* Improving planning operator
* Better Control Operator
* Fixing Planning Errors linked to applying Speed Factor
* Fixing Docker Image Build issues
* Adding a timestamp to messages
* Fixing PID mutlithread errors
* Drop Push Send after Pull period
* Limiting the latency
* Adding InfluxDB
* Fixing Influxdb Naming and quota
* Adding positional data
* Making launching container command faster
* Removing Dora-Pylot
* Refactor Error Handling
* Refactoring Error dubgging function
Co-authored-by: haixuanTao <hai-xuan.tao@student.ecp.fr>
* adding capnp metadata into messages
* Allowing Context to propagate throughout node
* Adding better tracing
* Refactoring opentelemetry mod
* Adding a degree parameter in messages
* Adding depth for better tracing
* Put a feature flag on tracing
* Removing unnecessary copy of the messages
* Small refactoring of messages
* Refactoring of context logging
* Adding opentelemetry metrics of system
* Adding process telemetry
* Commenting the build script
* Rename feature tracing
* Add documentation to module
* Adding message documentation
* Remove build script
* skip capnp generated file
* Reformating
* Reformating loop
* Testing example
* Removing zenoh dependencies in Python
* Improving example python api
* removing rayon that is appearing twice due to merge
* Simplifying python binding
* Create a separate crate for messages
* Moving `metrics` and `tracing` into separate crate
* Moving `python` into a separate crate and removing `main` crate
* Refactoring newly created crate
* Remove `depth` from the message `metadata`
* Add `capnp` installation within the CI
* Add `capnp` installation into CI `clippy` step
Co-authored-by: haixuanTao <hai-xuan.tao@student.ecp.fr>
* Refactoring for multithreading
* Refactoring code in order to use MemoryView
* Resolving multi output by casting Python output type
* Adding Python example runner
* Adding Rayon ThreadPool for CPU bound multithreading
* Adding benches
* Small Refactoring of Python Binding
* Adding documentation to Pylot Demo
* Removing cloning states data using RwLock
* Refactoring Servers to pass messages through tokio channels
* Removing unwrap when possible
* Splitting Zenoh function into separate module
* Refactoring Zenoh into a struct
* Adding several Python fix
* Fix eyre issue
* Adding docker for ease of build
* Fixing docker problem
* Reduce the frequency of source
* Adding better Python Operator
* Improving carla visualisation capabilities
* Enabling better visualisation
* adding object trajectory
* Improving planning
* Refactoring Python
* Adding control operator
* Improving planning operator
* Better Control Operator
* Fixing Planning Errors linked to applying Speed Factor
* Fixing Docker Image Build issues
* Adding a timestamp to messages
* Fixing PID mutlithread errors
* Drop Push Send after Pull period
* Limiting the latency
* Adding InfluxDB
* Fixing Influxdb Naming and quota
* Adding positional data
* Making launching container command faster
* Removing Dora-Pylot
* Refactor Error Handling
* Refactoring Error dubgging function
Co-authored-by: haixuanTao <hai-xuan.tao@student.ecp.fr>
Creates a basic prototype for parsing dataflows delared in YAML files using `serde`/`serde_yaml`. The dataflow file format is just an example, we can adjust this however we like.
To visualize the parsed dataflow, the main executable outputs a flowchart in mermaid syntax. GitHub supports this format natively in markdown files, alternatively it can be converted to an image on <https://mermaid.live>.
haixuanTao
Philipp Oppermann
haixuanTao