playground

Code runtimes, in your tab.

Pick an example to run Node, install npm packages, or execute Python locally through Pyodide. Workloads that need native tooling can use the same SDK path to promote to the server backend.

Runtimeworking

Installwaiting

Runwaiting

Editorready

main.py

/workdir/main.py

import matplotlib
matplotlib.use("Agg")

import matplotlib.pyplot as plt

audience = [0, 1, 3, 7, 12, 25]
demo_confidence = [98, 92, 73, 41, 18, 4]
bugs_discovered = [0, 1, 4, 11, 27, 63]

fig, ax = plt.subplots(figsize=(7.5, 4.4))
ax.plot(audience, demo_confidence, marker="o", linewidth=3, color="#0f766e", label="demo confidence")
ax.fill_between(audience, demo_confidence, color="#99f6e4", alpha=0.35)
ax.set_title("Law of Demo Physics", fontsize=16, weight="bold")
ax.set_xlabel("people watching")
ax.set_ylabel("confidence (%)", color="#0f766e")
ax.tick_params(axis="y", labelcolor="#0f766e")
ax.set_ylim(0, 105)
ax.grid(True, alpha=0.22)

bugs = ax.twinx()
bugs.bar(audience, bugs_discovered, width=1.15, alpha=0.28, color="#f97316", label="bugs that waited until now")
bugs.set_ylabel("suddenly obvious bugs", color="#c2410c")
bugs.tick_params(axis="y", labelcolor="#c2410c")

fig.text(0.5, 0.01, "peer-reviewed by vibes; p < probably", ha="center", fontsize=10, color="#64748b")
fig.tight_layout(rect=(0, 0.04, 1, 1))

fig.savefig("plot.svg", format="svg", bbox_inches="tight")

print("Python is running in Pyodide with matplotlib.")
print("Today's metric: confidence drops exactly when the demo starts.")
print("wrote /workdir/plot.svg")

Preview

The plot will appear here after Python finishes.

Terminal

stdout / stderr