dummy: plot worst-case enter/exits of tasks

This is a quick-and-dirty demo for plotting the states of traced RTIC
tasks over time. The used timestamp is the worst-case timestamp.
Timestamp quality and the time required to context switch between
tasks (that is, the time between a task exit and a HW task returned
action) are not rendered.

rtic-scope-frontend-dummy/Cargo.toml

@@ -15,3 +15,7 @@ rtic-scope-api = { version = "0.3", path = "../rtic-scope-api" }
 anyhow = "1"
 tempfile = "3"
 serde_json = "1"
+
+[dependencies.pyo3]
+version = "0.15.1"
+features = ["macros"]

rtic-scope-frontend-dummy/src/main.rs

@@ -3,8 +3,11 @@
 #![doc = include_str!("../../docs/profile/README.md")]
 
 use anyhow::{Context, Result};
+use pyo3::prelude::*;
+use pyo3::types::{PyDict, PyString};
 use rtic_scope_api as api;
 use serde_json::Deserializer;
+use std::string::String;
 
 fn main() -> Result<()> {
     // Create frontend socket in a temporary directory, print it for the parent backend.
@@ -15,6 +18,9 @@ fn main() -> Result<()> {
         .context("Failed to bind frontend socket")?;
     println!("{}", socket_path.display());
 
+    let mut task_enters = std::collections::HashMap::new();
+    let mut csv = String::new();
+
     // Deserialize api::EventChunks from socket and print events to
     // stderr along with nanoseconds timestamp.
     let (socket, _addr) = listener.accept().context("Failed to accept()")?;
@@ -32,7 +38,59 @@ fn main() -> Result<()> {
         let diff = nanos - prev_nanos;
         eprintln!("@{nanos} µs (+{diff} ns) [{quality}]: {events:?}");
         prev_nanos = nanos;
+
+        for e in events {
+            match e {
+                api::EventType::Task { name, action } if action == api::TaskAction::Entered => {
+                    task_enters.insert(name, nanos);
+                }
+                api::EventType::Task { name, action } if action == api::TaskAction::Exited => {
+                    let start = task_enters.get(&name).unwrap_or(&0);
+                    let end = nanos;
+                    let entry = format!("{name},{start},{end}\n");
+                    eprintln!("CSV: {entry}");
+                    csv.push_str(entry.as_str());
+                }
+                _ => (),
+            }
+        }
     }
 
+    pyo3::prepare_freethreaded_python();
+    Python::with_gil(|py| {
+        let locals = PyDict::new(py);
+        let csv = PyString::new(py, &csv);
+        locals.set_item("csv", csv).unwrap();
+        py.run(
+            r#"
+import pandas as pd
+import io
+import matplotlib.pyplot as plt
+
+df = pd.read_csv(io.StringIO(csv), header=None, names=['Task', 'Start', 'End'])
+df['Diff'] = df.End - df.Start
+
+fig, ax = plt.subplots(figsize=(6,3))
+
+labels = []
+for i, task in enumerate(df.groupby('Task')):
+    labels.append(task[0])
+    data = task[1][["Start", "Diff"]]
+    ax.broken_barh(data.values, (i - 0.4, 0.8))
+
+ax.set_yticks(range(len(labels)))
+ax.set_yticklabels(labels)
+ax.set_xlabel('time [ns]')
+ax.set_ylabel('RTIC task')
+plt.tight_layout()
+plt.grid(visible=True, which='both', axis='x')
+plt.show()
+        "#,
+            None,
+            Some(locals),
+        )
+        .unwrap();
+    });
+
     Ok(())
 }