import sys
import json
import unittest
from pathlib import Path
from exectiming.exectiming import StaticTimer, Timer

folder = Path(__file__).resolve().parent
sys.path.append(str(folder.parent))

from jtools import Filter, Key, Query, Formatter, __version__

with open(folder / "data/10000.json", "r") as file:
    large_data = json.loads(file.read())

with open(folder / "data/20.json", "r") as file:
    small_data = json.loads(file.read())


class PerformanceTesting(unittest.TestCase):
    def test_query_reuse(self):
        runs = 100

        value1, recreate_time = StaticTimer.time_it(
            lambda: Query('email.$split("@").1.$split(".").0').single(large_data[0]),
            runs=runs, iterations_per_run=1, display=False, log_arguments=False
        )

        getter = Query('email.$split("@").1.$split(".").0')
        value2, reuse_time = StaticTimer.time_it(
            getter.single, large_data[0],
            runs=runs, iterations_per_run=1, display=False, log_arguments=False
        )

        print(recreate_time / reuse_time, "x faster to reuse Query then recreate")
        self.assertEqual(value1, value2)
        self.assertGreater(recreate_time / reuse_time, 5)

    def test_filter_reuse(self):
        runs = 100

        value1, recreate_time = StaticTimer.time_it(
            lambda: Filter(Key("gender").eq("male").and_(Key("friends.$length").gte(3))).single(large_data[0]),
            runs=runs, iterations_per_run=1, display=False, log_arguments=False
        )

        f = Filter(Key("gender").eq("male").and_(Key("friends.$length").gte(3)))
        value2, reuse_time = StaticTimer.time_it(
            f.single, large_data[0],
            runs=runs, iterations_per_run=1, display=False, log_arguments=False
        )

        print(recreate_time / reuse_time, "x faster to reuse Filter then recreate")
        self.assertEqual(value1, value2)
        self.assertGreater(recreate_time / reuse_time, 5)

    def test_formatter_reuse(self):
        runs = 100

        value1, recreate_time = StaticTimer.time_it(
            lambda: Formatter(
                "Age: @age, Domain: @email.$split('@').1, Friends: @friends.$map('index', 'name').$join"
            ).single(large_data[0]),
            runs=runs, iterations_per_run=1, display=False, log_arguments=False
        )

        f = Formatter("Age: @age, Domain: @email.$split('@').1, Friends: @friends.$map('index', 'name').$join")
        value2, reuse_time = StaticTimer.time_it(
            f.single, large_data[0],
            runs=runs, iterations_per_run=1, display=False, log_arguments=False
        )

        print(f.single(large_data[0]))
        print(recreate_time / reuse_time, "x faster to reuse Formatter then recreate")
        self.assertEqual(value1, value2)
        self.assertGreater(recreate_time / reuse_time, 5)


if __name__ == "__main__":
    print(__version__)
    timer = Timer()

    # timer.time_it(Filter(Key("age") > 40).many, lambda: large_data[:randint(0, len(large_data))],
    #               call_callable_args=True, runs=10, iterations_per_run=1, log_arguments=True,
    #               split_label="Filter ('age')")
    #
    # timer.time_it(Filter(Key("friends.$length") > 3).many, lambda: large_data[:randint(0, len(large_data))],
    #               call_callable_args=True, runs=10, iterations_per_run=1, log_arguments=True,
    #               split_label="Filter ('friends.$length')")
    #
    # timer.time_it(Filter(
    #     Key("latitude").gte(-45) & Key("latitude").lte(45) & Key("longitude").lte(0)
    # ).many, lambda: large_data[:randint(0, len(large_data))],
    #               call_callable_args=True, runs=10, iterations_per_run=1, log_arguments=True,
    #               split_label="Filter (lat/lon)")
    #
    # timer.plot(split_index=0, transformer=len, multiple=True, plot_curve=True,
    #            curve=timer.best_fit_curve(0, curve_type="Linear", transformers=len),
    #            equation_rounding=4)
    # timer.plot(split_index=1, transformer=len, multiple=True, plot_curve=True,
    #            curve=timer.best_fit_curve(1, curve_type="Linear", transformers=len),
    #            equation_rounding=4)
    # timer.plot(split_index=2, transformer=len, plot_curve=True,
    #            curve=timer.best_fit_curve(2, curve_type="Linear", transformers=len),
    #            equation_rounding=4)
    #
    # timer.statistics()

    # q = Query("friends.0.name.$split(' ').$join(': ')")
    # print(q.single(large_data[0]))
    # timer.time_it(
    #     q.many, large_data,
    #     iterations_per_run=1, runs=10
    # )
    #
    # q = Query("registered.$strptime.$attr('year')")
    # print(q.single(small_data[0]))
    # timer.time_it(
    #     q.many, small_data,
    #     iterations_per_run=50, runs=10
    # )

    item = {
        "x1": 1,
        "y1": 1,
        "x2": 12,
        "y2": 54
    }
    f = Formatter("Midpoint: [@x2.$subtract(@x1).$divide(2), @y2.$subtract(@y1).$divide(2)]")
    print(f.single(item))
    timer.time_it(
        f.single, item,
        iterations_per_run=10000, runs=10
    )

    timer.statistics()

import sys
import json
import unittest
from pathlib import Path
from exectiming.exectiming import StaticTimer, Timer

folder = Path(__file__).resolve().parent
sys.path.append(str(folder.parent))

from jtools import Filter, Key, Query, Formatter, __version__

with open(folder / "data/10000.json", "r") as file:
    large_data = json.loads(file.read())

with open(folder / "data/20.json", "r") as file:
    small_data = json.loads(file.read())


class PerformanceTesting(unittest.TestCase):
    def test_query_reuse(self):
        runs = 100

        value1, recreate_time = StaticTimer.time_it(
            lambda: Query('email.$split("@").1.$split(".").0').single(large_data[0]),
            runs=runs, iterations_per_run=1, display=False, log_arguments=False
        )

        getter = Query('email.$split("@").1.$split(".").0')
        value2, reuse_time = StaticTimer.time_it(
            getter.single, large_data[0],
            runs=runs, iterations_per_run=1, display=False, log_arguments=False
        )

        print(recreate_time / reuse_time, "x faster to reuse Query then recreate")
        self.assertEqual(value1, value2)
        self.assertGreater(recreate_time / reuse_time, 5)

    def test_filter_reuse(self):
        runs = 100

        value1, recreate_time = StaticTimer.time_it(
            lambda: Filter(Key("gender").eq("male").and_(Key("friends.$length").gte(3))).single(large_data[0]),
            runs=runs, iterations_per_run=1, display=False, log_arguments=False
        )

        f = Filter(Key("gender").eq("male").and_(Key("friends.$length").gte(3)))
        value2, reuse_time = StaticTimer.time_it(
            f.single, large_data[0],
            runs=runs, iterations_per_run=1, display=False, log_arguments=False
        )

        print(recreate_time / reuse_time, "x faster to reuse Filter then recreate")
        self.assertEqual(value1, value2)
        self.assertGreater(recreate_time / reuse_time, 5)

    def test_formatter_reuse(self):
        runs = 100

        value1, recreate_time = StaticTimer.time_it(
            lambda: Formatter(
                "Age: @age, Domain: @email.$split('@').1, Friends: @friends.$map('index', 'name').$join"
            ).single(large_data[0]),
            runs=runs, iterations_per_run=1, display=False, log_arguments=False
        )

        f = Formatter("Age: @age, Domain: @email.$split('@').1, Friends: @friends.$map('index', 'name').$join")
        value2, reuse_time = StaticTimer.time_it(
            f.single, large_data[0],
            runs=runs, iterations_per_run=1, display=False, log_arguments=False
        )

        print(f.single(large_data[0]))
        print(recreate_time / reuse_time, "x faster to reuse Formatter then recreate")
        self.assertEqual(value1, value2)
        self.assertGreater(recreate_time / reuse_time, 5)


if __name__ == "__main__":
    print(__version__)
    timer = Timer()

    # timer.time_it(Filter(Key("age") > 40).many, lambda: large_data[:randint(0, len(large_data))],
    #               call_callable_args=True, runs=10, iterations_per_run=1, log_arguments=True,
    #               split_label="Filter ('age')")
    #
    # timer.time_it(Filter(Key("friends.$length") > 3).many, lambda: large_data[:randint(0, len(large_data))],
    #               call_callable_args=True, runs=10, iterations_per_run=1, log_arguments=True,
    #               split_label="Filter ('friends.$length')")
    #
    # timer.time_it(Filter(
    #     Key("latitude").gte(-45) & Key("latitude").lte(45) & Key("longitude").lte(0)
    # ).many, lambda: large_data[:randint(0, len(large_data))],
    #               call_callable_args=True, runs=10, iterations_per_run=1, log_arguments=True,
    #               split_label="Filter (lat/lon)")
    #
    # timer.plot(split_index=0, transformer=len, multiple=True, plot_curve=True,
    #            curve=timer.best_fit_curve(0, curve_type="Linear", transformers=len),
    #            equation_rounding=4)
    # timer.plot(split_index=1, transformer=len, multiple=True, plot_curve=True,
    #            curve=timer.best_fit_curve(1, curve_type="Linear", transformers=len),
    #            equation_rounding=4)
    # timer.plot(split_index=2, transformer=len, plot_curve=True,
    #            curve=timer.best_fit_curve(2, curve_type="Linear", transformers=len),
    #            equation_rounding=4)
    #
    # timer.statistics()

    # q = Query("friends.0.name.$split(' ').$join(': ')")
    # print(q.single(large_data[0]))
    # timer.time_it(
    #     q.many, large_data,
    #     iterations_per_run=1, runs=10
    # )
    #
    # q = Query("registered.$strptime.$attr('year')")
    # print(q.single(small_data[0]))
    # timer.time_it(
    #     q.many, small_data,
    #     iterations_per_run=50, runs=10
    # )

    item = {
        "x1": 1,
        "y1": 1,
        "x2": 12,
        "y2": 54
    }
    f = Formatter("Midpoint: [@x2.$subtract(@x1).$divide(2), @y2.$subtract(@y1).$divide(2)]")
    print(f.single(item))
    timer.time_it(
        f.single, item,
        iterations_per_run=10000, runs=10
    )

    timer.statistics()

# timer.time_it(Filter(Key("age") > 40).many, lambda: large_data[:randint(0, len(large_data))], #               call_callable_args=True, runs=10, iterations_per_run=1, log_arguments=True, #               split_label="Filter ('age')") # # timer.time_it(Filter(Key("friends.$length") > 3).many, lambda: large_data[:randint(0, len(large_data))], #               call_callable_args=True, runs=10, iterations_per_run=1, log_arguments=True, #               split_label="Filter ('friends.$length')") # # timer.time_it(Filter( #     Key("latitude").gte(-45) & Key("latitude").lte(45) & Key("longitude").lte(0) # ).many, lambda: large_data[:randint(0, len(large_data))], #               call_callable_args=True, runs=10, iterations_per_run=1, log_arguments=True, #               split_label="Filter (lat/lon)") # # timer.plot(split_index=0, transformer=len, multiple=True, plot_curve=True, #            curve=timer.best_fit_curve(0, curve_type="Linear", transformers=len), #            equation_rounding=4) # timer.plot(split_index=1, transformer=len, multiple=True, plot_curve=True, #            curve=timer.best_fit_curve(1, curve_type="Linear", transformers=len), #            equation_rounding=4) # timer.plot(split_index=2, transformer=len, plot_curve=True, #            curve=timer.best_fit_curve(2, curve_type="Linear", transformers=len), #            equation_rounding=4) # # timer.statistics() # q = Query("friends.0.name.$split(' ').$join(': ')") # print(q.single(large_data[0])) # timer.time_it( #     q.many, large_data, #     iterations_per_run=1, runs=10 # ) # # q = Query("registered.$strptime.$attr('year')") # print(q.single(small_data[0])) # timer.time_it( #     q.many, small_data, #     iterations_per_run=50, runs=10 # )