Source code for openfisca_core.tracers.performance_log

from __future__ import annotations

import typing

import csv
import importlib.resources
import itertools
import json
import os

from openfisca_core import tracers

if typing.TYPE_CHECKING:
    Trace = dict[str, dict]
    Calculation = tuple[str, dict]
    SortedTrace = list[Calculation]




class PerformanceLog:
    def __init__(self, full_tracer: tracers.FullTracer) -> None:
        self._full_tracer = full_tracer

    def generate_graph(self, dir_path: str) -> None:
        with open(os.path.join(dir_path, "performance_graph.html"), "w") as f:
            template = importlib.resources.read_text(
                "openfisca_core.scripts.assets",
                "index.html",
            )

            perf_graph_html = template.replace(
                "{{data}}",
                json.dumps(self._json()),
            )

            f.write(perf_graph_html)

    def generate_performance_tables(self, dir_path: str) -> None:
        flat_trace = self._full_tracer.get_flat_trace()

        csv_rows = [
            {
                "name": key,
                "calculation_time": trace["calculation_time"],
                "formula_time": trace["formula_time"],
            }
            for key, trace in flat_trace.items()
        ]

        self._write_csv(
            os.path.join(dir_path, "performance_table.csv"),
            csv_rows,
        )

        aggregated_csv_rows = [
            {"name": key, **aggregated_time}
            for key, aggregated_time in self.aggregate_calculation_times(
                flat_trace,
            ).items()
        ]

        self._write_csv(
            os.path.join(dir_path, "aggregated_performance_table.csv"),
            aggregated_csv_rows,
        )

    def aggregate_calculation_times(
        self,
        flat_trace: Trace,
    ) -> dict[str, dict]:
        def _aggregate_calculations(calculations: list) -> dict:
            calculation_count = len(calculations)

            calculation_time = sum(
                calculation[1]["calculation_time"] for calculation in calculations
            )

            formula_time = sum(
                calculation[1]["formula_time"] for calculation in calculations
            )

            return {
                "calculation_count": calculation_count,
                "calculation_time": tracers.TraceNode.round(calculation_time),
                "formula_time": tracers.TraceNode.round(formula_time),
                "avg_calculation_time": tracers.TraceNode.round(
                    calculation_time / calculation_count,
                ),
                "avg_formula_time": tracers.TraceNode.round(
                    formula_time / calculation_count,
                ),
            }

        def _groupby(calculation: Calculation) -> str:
            return calculation[0].split("<")[0]

        all_calculations: SortedTrace = sorted(flat_trace.items())

        return {
            variable_name: _aggregate_calculations(list(calculations))
            for variable_name, calculations in itertools.groupby(
                all_calculations,
                _groupby,
            )
        }

    def _json(self) -> dict:
        children = [self._json_tree(tree) for tree in self._full_tracer.trees]
        calculations_total_time = sum(child["value"] for child in children)

        return {
            "name": "All calculations",
            "value": calculations_total_time,
            "children": children,
        }

    def _json_tree(self, tree: tracers.TraceNode) -> dict:
        calculation_total_time = tree.calculation_time()
        children = [self._json_tree(child) for child in tree.children]

        return {
            "name": f"{tree.name}<{tree.period}>",
            "value": calculation_total_time,
            "children": children,
        }

    def _write_csv(self, path: str, rows: list[dict]) -> None:
        fieldnames = list(rows[0].keys())

        with open(path, "w") as csv_file:
            writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
            writer.writeheader()

            for row in rows:
                writer.writerow(row)