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Port logic and csp notebooks to the JupyterLite companion (#1072)
Add two more in-browser PoC notebooks: - logic.ipynb: propositional model checking / DPLL and first-order forward chaining (the 'West is a criminal' KB). - csp.ipynb: map colouring with AC-3 / backtracking and 8-queens with min-conflicts. Both modules only need pure-Python packages Pyodide already ships (networkx for logic, sortedcontainers for csp), which are preloaded in jupyter-lite.json. To let them import in Pyodide, make ipythonblocks a lazy import in agents.py (logic/csp pull in aima.agents): BlockGrid is only used by GraphicEnvironment, so import it inside __init__ with a clear error message instead of at module top level. This also makes aima.agents usable in any environment without the optional GUI dependency. Verified: the lite site builds with all five notebooks and the lazy-import fix is in the bundled wheel; in a Pyodide proxy env (numpy/networkx/ sortedcontainers/ipython, no ipythonblocks) both notebooks import and run.
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‎aima/agents.py‎

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from aima.utils import distance_squared, turn_heading
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from statistics import mean
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from ipythonblocks import BlockGrid
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from IPython.display import HTML, display, clear_output
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from time import sleep
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@@ -635,6 +634,13 @@ def __init__(self, width=10, height=10, boundary=True, color={}, display=False):
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"""Define all the usual XYEnvironment characteristics,
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but initialise a BlockGrid for GUI too."""
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super().__init__(width, height)
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# imported lazily so the rest of aima.agents (and modules that import it,
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# e.g. logic/csp) can be used without the optional ipythonblocks GUI dep
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try:
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from ipythonblocks import BlockGrid
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except ImportError as e:
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raise ImportError("GraphicEnvironment needs the optional 'ipythonblocks' "
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"package; install it with `pip install ipythonblocks`.") from e
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self.grid = BlockGrid(width, height, fill=(200, 200, 200))
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if display:
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self.grid.show()

‎lite/README.md‎

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@@ -21,12 +21,22 @@ cannot run here. The `aima` wheel is therefore installed with `deps=False` and
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the demo notebooks are restricted to modules that import only Pyodide-provided
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packages.
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The proof-of-concept ships two such notebooks:
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The proof-of-concept ships these notebooks:
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- `content/search.ipynb` — BFS / A* on the Romania map (`aima.search`, numpy only).
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- `content/games.ipynb` — minimax / alpha-beta on Tic-Tac-Toe (`aima.games`, numpy only).
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- `content/logic.ipynb` — propositional model checking / DPLL and first-order
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forward chaining (`aima.logic`, needs `networkx`).
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- `content/csp.ipynb` — map colouring with AC-3 / backtracking and N-queens with
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min-conflicts (`aima.csp`, needs `sortedcontainers`).
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`content/Welcome.ipynb` shows the one-cell install pattern used by every notebook.
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`networkx` and `sortedcontainers` are pure-Python and ship with Pyodide; they are
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preloaded for the kernel in `jupyter-lite.json`. `content/Welcome.ipynb` shows the
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one-cell install pattern used by every notebook.
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Note: `aima.logic`/`aima.csp` pull in `aima.agents`, whose only GUI dependency
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(`ipythonblocks`) is imported lazily, so these modules import cleanly in Pyodide
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without it.
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## Build locally
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- Verify in-browser execution across browsers (Pyodide runs only in a real
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browser, so this cannot be checked in headless CI — the CI job only proves the
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static site *builds*).
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- Port more lightweight notebooks (logic, csp, planning, probability) once their
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in-browser behaviour is confirmed; csp needs `sortedcontainers`, logic needs
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`networkx` (both pure-Python, installable in Pyodide).
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- Port more lightweight notebooks (planning, probability) once their in-browser
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behaviour is confirmed.
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- Decide whether to grow this into a full MyST / Jupyter Book textbook companion.

‎lite/content/csp.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Constraint satisfaction in the browser\n",
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"\n",
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"Map colouring and N-queens from chapter 6, running fully in your browser with\n",
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"`aima.csp`."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import piplite\n",
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"await piplite.install(\"aima\", deps=False)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Map colouring\n",
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"\n",
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"Colour the map of Australia with three colours so that no two neighbouring\n",
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"regions share one. First we enforce arc consistency (AC-3), then solve by\n",
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"backtracking search."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from aima.csp import australia_csp, AC3, backtracking_search\n",
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"\n",
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"consistent, checks = AC3(australia_csp)\n",
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"print(\"AC-3 arc-consistent:\", consistent, \" (\", checks, \"constraint checks )\")\n",
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"print(\"backtracking solution:\", backtracking_search(australia_csp))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## N-queens\n",
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"\n",
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"Place 8 non-attacking queens by local search (min-conflicts). The solution\n",
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"maps each column to the row of its queen."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import random\n",
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"from aima.csp import NQueensCSP, min_conflicts\n",
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"\n",
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"random.seed(0)\n",
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"solution = min_conflicts(NQueensCSP(8), max_steps=1000)\n",
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"print(\"8-queens (column -> row):\", solution)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python (Pyodide)",
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"language": "python",
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"name": "python"
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},
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"language_info": {
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"name": "python"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

‎lite/content/logic.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Logic in the browser\n",
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"\n",
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"Propositional and first-order reasoning from chapters 7-9, running fully in\n",
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"your browser with `aima.logic`."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import piplite\n",
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"await piplite.install(\"aima\", deps=False)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Propositional logic\n",
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"\n",
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"Model checking by truth-table enumeration, and satisfiability via DPLL."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from aima.logic import expr, tt_entails, dpll_satisfiable\n",
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"\n",
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"# modus ponens: does P & (P => Q) entail Q ?\n",
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"print(\"(P & (P ==> Q)) |= Q :\", tt_entails(expr(\"(P & (P ==> Q))\"), expr(\"Q\")))\n",
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"\n",
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"# satisfiability\n",
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"print(\"P | ~P satisfiable :\", bool(dpll_satisfiable(expr(\"P | ~P\"))))\n",
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"print(\"P & ~P satisfiable :\", bool(dpll_satisfiable(expr(\"P & ~P\"))))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## First-order logic\n",
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"\n",
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"The classic \"West is a criminal\" knowledge base (section 9.3), solved by\n",
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"forward chaining."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from aima.logic import expr, FolKB, fol_fc_ask\n",
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"\n",
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"clauses = [\n",
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" \"(American(x) & Weapon(y) & Sells(x, y, z) & Hostile(z)) ==> Criminal(x)\",\n",
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" \"Owns(Nono, M1)\",\n",
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" \"Missile(M1)\",\n",
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" \"(Missile(x) & Owns(Nono, x)) ==> Sells(West, x, Nono)\",\n",
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" \"Missile(x) ==> Weapon(x)\",\n",
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" \"Enemy(x, America) ==> Hostile(x)\",\n",
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" \"American(West)\",\n",
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" \"Enemy(Nono, America)\",\n",
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"]\n",
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"kb = FolKB([expr(c) for c in clauses])\n",
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"print(\"Who is a criminal? \", list(fol_fc_ask(kb, expr(\"Criminal(x)\"))))"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python (Pyodide)",
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"language": "python",
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"name": "python"
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},
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"language_info": {
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"name": "python"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

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