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ee34a1f278
* Fixed isort * Fixed issues * FIxed linters --------- Co-authored-by: James Maslek <jmaslek11@gmail.com>
62 lines
1.7 KiB
Python
62 lines
1.7 KiB
Python
# IMPORTATION STANDARD
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from typing import Callable
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import pandas as pd
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import pytest
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from pandas._typing import Axis
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from pandas.testing import assert_frame_equal
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# IMPORTATION INTERNAL
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from openbb_terminal.helpers_denomination import (
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DENOMINATION,
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get_denomination,
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get_denominations,
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)
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from openbb_terminal.helpers_denomination import transform as transform_by_denomination
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df = pd.DataFrame(
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data={"Revenue": [1000000, 2000000, 3000000], "EPS": [3, 4, 5]},
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index=["ttm", "2022-01-01", "2021-01-01"],
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)
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dftr = df.transpose()
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@pytest.mark.parametrize(
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"source, target, maxValue, axis, skipPredicate",
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[
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("Units", None, None, 0, None),
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("Units", None, 100, 0, None),
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("Millions", "Thousands", None, 1, lambda s: s.name == "EPS"),
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],
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)
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def test_given_arguments_then_it_transforms_as_expected(
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source: DENOMINATION,
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target: DENOMINATION,
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maxValue: float,
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axis: Axis,
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skipPredicate: Callable[[pd.Series], bool],
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):
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target_df = dftr if axis == 1 else df
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expectedMax = maxValue if maxValue is not None else target_df.max().max()
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expectedTargetDenomination = (
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target if target is not None else get_denomination(expectedMax)[0]
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)
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expected_df = target_df.apply(
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lambda series: series
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if skipPredicate is not None and skipPredicate(series)
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else series
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* (
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get_denominations()[source]
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/ get_denominations()[expectedTargetDenomination]
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),
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axis,
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)
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(dft, denomination) = transform_by_denomination(
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target_df, source, target, maxValue, axis, skipPredicate
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)
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assert denomination == expectedTargetDenomination
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assert_frame_equal(dft, expected_df)
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