{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "227cc453",
   "metadata": {},
   "source": [
    "# Tierkreis checkpoints; using pre build graphs\n",
    "\n",
    "In this example we will run a predefined graph in a customized environment.\n",
    "\n",
    "By default tierkreis will store the checkpoints of workflow runs in the filesystem at `~/.tierkreis/checkpoints`.\n",
    "This can be configured in the storage by providing the `tierkreis_directory` argument to the storage layer (e.g. `checkpoints2`).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "052a8990",
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install tierkreis qnexus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ff781681",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "from uuid import UUID\n",
    "\n",
    "from tierkreis.storage import FileStorage\n",
    "\n",
    "storage = FileStorage(\n",
    "    UUID(int=107),\n",
    "    do_cleanup=True,\n",
    "    tierkreis_directory=Path.home() / \".tierkreis\" / \"checkpoints2\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41cc0947",
   "metadata": {},
   "source": [
    "This change needs to be forwarded to the executors, which is why they take the logs path as additional argument.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8992df08",
   "metadata": {},
   "outputs": [],
   "source": [
    "from tierkreis.consts import PACKAGE_PATH\n",
    "from tierkreis.executor import UvExecutor\n",
    "\n",
    "executor = UvExecutor(PACKAGE_PATH.parent / \"tierkreis_workers\", storage.logs_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a4167ce",
   "metadata": {},
   "source": [
    "Typically now one would define a graph.\n",
    "Although, tierkreis ships some preconstructed graphs.\n",
    "For this example we are going a to run a circuit on nexus and poll for its results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cfeeea07",
   "metadata": {},
   "outputs": [],
   "source": [
    "from tierkreis.graphs.nexus.submit_poll import nexus_submit_and_poll\n",
    "\n",
    "graph = nexus_submit_and_poll()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca071701",
   "metadata": {},
   "source": [
    "Before we run the graph we can visualize it to get familiar with it.\n",
    "This will start a webserver and listen on [localhost](http://localhost:8000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "59f2f3e5",
   "metadata": {
    "tags": [
     "skip-execution"
    ]
   },
   "outputs": [],
   "source": [
    "from qnexus.client.auth import login\n",
    "from tierkreis_visualization.visualize_graph import visualize_graph\n",
    "\n",
    "login()\n",
    "visualize_graph(\n",
    "    graph,\n",
    ")  # this spawns a server, you need to manually terminate this cell."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34bea400",
   "metadata": {},
   "source": [
    "and finally we can run it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a61d07ad",
   "metadata": {
    "tags": [
     "skip-execution"
    ]
   },
   "outputs": [],
   "source": [
    "from pytket.qasm.qasm import circuit_from_qasm\n",
    "from qnexus import AerConfig\n",
    "\n",
    "from tierkreis.controller import run_graph\n",
    "from tierkreis.storage import read_outputs\n",
    "\n",
    "aer_config = AerConfig()\n",
    "circuit = circuit_from_qasm(Path().parent / \"data\" / \"ghz_state_n23.qasm\")\n",
    "circuits = [circuit]\n",
    "inputs = {\n",
    "    \"project_name\": \"2025-tkr-test\",\n",
    "    \"job_name\": \"job-1\",\n",
    "    \"circuits\": circuits,\n",
    "    \"n_shots\": [30] * len(circuits),\n",
    "    \"backend_config\": aer_config,\n",
    "}\n",
    "storage.clean_graph_files()\n",
    "run_graph(\n",
    "    storage,\n",
    "    executor,\n",
    "    graph,\n",
    "    inputs,\n",
    "    polling_interval_seconds=0.1,\n",
    ")\n",
    "res = read_outputs(graph, storage)"
   ]
  }
 ],
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