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Add compare tool #280
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Add compare tool #280
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# | ||
# compare.py | ||
# | ||
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||
from pathlib import Path | ||
import click | ||
from rich_click.rich_command import RichCommand | ||
from rich_click.rich_group import RichGroup | ||
from rich import print | ||
from typing import cast | ||
import pandas as pd | ||
from etl import tempcompare | ||
from owid import catalog | ||
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@click.group(cls=RichGroup) | ||
def cli() -> None: | ||
"""Compare two dataframes, both structurally and the values. | ||
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This tool loads two dataframes, either from the local ETL and the remote catalog | ||
or just from two different files. It compares the columns, index columns and index values (row indices) as | ||
sets between the two dataframes and outputs the differences. Finally it compares the values of the overlapping | ||
columns and rows with the given threshold values for absolute and relative tolerance. | ||
|
||
The exit code is 0 if the dataframes are equal, 1 if there is an error loading the dataframes, 2 if the dataframes | ||
are structurally equal but are otherwise different, 3 if the dataframes have different structure and/or different values. | ||
""" | ||
pass | ||
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def diff_print_and_exit( | ||
df1: pd.DataFrame, | ||
df2: pd.DataFrame, | ||
df1_label: str, | ||
df2_label: str, | ||
absolute_tolerance: float, | ||
relative_tolerance: float, | ||
show_values: bool, | ||
show_shared: bool, | ||
truncate_lists_at: int, | ||
) -> None: | ||
"""Runs the comparison and prints the differences, then exits with the appropriate exit code.""" | ||
diff = tempcompare.HighLevelDiff(df1, df2, absolute_tolerance, relative_tolerance) | ||
if diff.are_equal: | ||
print("[green]Dataframes are equal (within the given thresholds)[/green]") | ||
exit(0) | ||
else: | ||
lines = diff.get_description_lines_for_diff( | ||
df1_label, | ||
df2_label, | ||
use_color_tags=True, | ||
preview_different_dataframe_values=show_values, | ||
show_shared=show_shared, | ||
truncate_lists_longer_than=truncate_lists_at, | ||
) | ||
for line in lines: | ||
print(line) | ||
if diff.are_structurally_equal: | ||
exit(2) | ||
else: | ||
exit(3) | ||
|
||
|
||
@cli.command(cls=RichCommand) | ||
@click.argument("channel") | ||
@click.argument("namespace") | ||
@click.argument("dataset") | ||
@click.argument("table") | ||
@click.option( | ||
"--absolute-tolerance", | ||
default=0.00000001, | ||
show_default=True, | ||
help="The absolute tolerance for floating point comparisons.", | ||
) | ||
@click.option( | ||
"--relative-tolerance", | ||
default=0.05, | ||
show_default=True, | ||
help="The relative tolerance for floating point comparisons.", | ||
) | ||
@click.option( | ||
"--show-values/--hide-values", | ||
default=False, | ||
show_default=True, | ||
help="Show a preview of the values where the dataframes are different.", | ||
) | ||
@click.option( | ||
"--show-shared/--hide-shared", | ||
default=False, | ||
show_default=True, | ||
help="Show the structural overlap of the two dataframes (shared columns, index columns and index values).", | ||
) | ||
@click.option( | ||
"--truncate-lists-at", | ||
default=20, | ||
show_default=True, | ||
help="Print truncated lists if they are longer than the given length.", | ||
) | ||
def etl_catalog( | ||
channel: str, | ||
namespace: str, | ||
dataset: str, | ||
table: str, | ||
absolute_tolerance: float, | ||
relative_tolerance: float, | ||
show_values: bool, | ||
show_shared: bool, | ||
truncate_lists_at: int, | ||
) -> None: | ||
""" | ||
Compare a table in the local catalog with the one in the remote catalog. | ||
|
||
It compares the columns, index columns and index values (row indices) as | ||
sets between the two dataframes and outputs the differences. Finally it compares the values of the overlapping | ||
columns and rows with the given threshold values for absolute and relative tolerance. | ||
|
||
The exit code is 0 if the dataframes are equal, 1 if there is an error loading the dataframes, 2 if the dataframes | ||
are structurally equal but are otherwise different, 3 if the dataframes have different structure and/or different values. | ||
""" | ||
try: | ||
remote_df = catalog.find_one( | ||
table=table, namespace=namespace, dataset=dataset, channels=channel | ||
) | ||
local_catalog = catalog.LocalCatalog("data") | ||
local_df = local_catalog.find_one( | ||
table=table, | ||
namespace=namespace, | ||
dataset=dataset, | ||
channel=cast(catalog.CHANNEL, channel), | ||
) | ||
except Exception as e: | ||
print(e) | ||
exit(1) | ||
|
||
diff_print_and_exit( | ||
remote_df, | ||
local_df, | ||
"remote", | ||
"local", | ||
absolute_tolerance, | ||
relative_tolerance, | ||
show_values, | ||
show_shared, | ||
truncate_lists_at, | ||
) | ||
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def load_table(path_str: str) -> catalog.Table: | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. (There's a similar method that could be used instead, but it'd probably look weirder than your method) |
||
"""Loads a Table (dataframe + metadata) from a path.""" | ||
path = Path(path_str) | ||
if not path.exists(): | ||
raise Exception("File does not exist: " + path_str) | ||
|
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if path.suffix.lower() == ".feather": | ||
return catalog.tables.Table.read_feather(path_str) | ||
elif path.suffix.lower() == ".csv": | ||
return catalog.tables.Table.read_csv(path_str) | ||
else: | ||
raise Exception("Unknown file format: " + path_str) | ||
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def load_dataframe(path_str: str) -> pd.DataFrame: | ||
"""Loads a DataFrame from a path.""" | ||
path = Path(path_str) | ||
if not path.exists(): | ||
raise Exception("File does not exist: " + path_str) | ||
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if path.suffix.lower() == ".feather": | ||
return cast(pd.DataFrame, pd.read_feather(path_str)) | ||
elif path.suffix.lower() == ".csv": | ||
return pd.read_csv(path_str) | ||
elif path.suffix.lower() == ".parquet": | ||
return cast(pd.DataFrame, pd.read_parquet(path_str)) | ||
else: | ||
raise Exception("Unknown file format: " + path_str) | ||
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@cli.command(cls=RichCommand) | ||
@click.argument("dataframe1") | ||
@click.argument("dataframe2") | ||
@click.option( | ||
"--absolute-tolerance", | ||
default=0.00000001, | ||
show_default=True, | ||
help="The absolute tolerance for floating point comparisons.", | ||
) | ||
@click.option( | ||
"--relative-tolerance", | ||
default=0.05, | ||
show_default=True, | ||
help="The relative tolerance for floating point comparisons.", | ||
) | ||
@click.option( | ||
"--show-values/--hide-values", | ||
default=False, | ||
show_default=True, | ||
help="Show a preview of the values where the dataframes are different.", | ||
) | ||
@click.option( | ||
"--show-shared/--hide-shared", | ||
default=False, | ||
show_default=True, | ||
help="Show the structural overlap of the two dataframes (shared columns, index columns and index values).", | ||
) | ||
@click.option( | ||
"--truncate-lists-at", | ||
default=20, | ||
show_default=True, | ||
help="Print truncated lists if they are longer than the given length.", | ||
) | ||
def dataframes( | ||
dataframe1: str, | ||
dataframe2: str, | ||
absolute_tolerance: float, | ||
relative_tolerance: float, | ||
show_values: bool, | ||
show_shared: bool, | ||
truncate_lists_at: int, | ||
) -> None: | ||
""" | ||
Compare two dataframes given as paths. | ||
|
||
It compares the columns, index columns and index values (row indices) as | ||
sets between the two dataframes and outputs the differences. Finally it compares the values of the overlapping | ||
columns and rows with the given threshold values for absolute and relative tolerance. | ||
|
||
The exit code is 0 if the dataframes are equal, 1 if there is an error loading the dataframes, 2 if the dataframes | ||
are structurally equal but are otherwise different, 3 if the dataframes have different structure and/or different values. | ||
""" | ||
df1: pd.DataFrame | ||
df2: pd.DataFrame | ||
print("🦸 OWID's friendly dataframe comparision tool - at your service! 🦸") | ||
try: | ||
df1 = load_table(dataframe1) | ||
except Exception: | ||
print( | ||
f"[yellow]Reading {dataframe1} as table with metadata failed, trying to read as plain dataframe[/yellow]" | ||
) | ||
try: | ||
df1 = load_dataframe(dataframe1) | ||
except Exception as e: | ||
print(f"[red]Reading {dataframe1} as dataframe failed[/red]") | ||
print(e) | ||
exit(1) | ||
|
||
try: | ||
df2 = load_table(dataframe2) | ||
except Exception: | ||
print( | ||
f"[yellow]Reading {dataframe2} as table with metadata failed, trying to read as plain dataframe[/yellow]" | ||
) | ||
try: | ||
df2 = load_dataframe(dataframe2) | ||
except Exception as e: | ||
print(f"[red]Reading {dataframe2} as dataframe failed[/red]") | ||
print(e) | ||
exit(1) | ||
|
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diff_print_and_exit( | ||
df1, | ||
df2, | ||
"dataframe1", | ||
"dataframe2", | ||
absolute_tolerance, | ||
relative_tolerance, | ||
show_values, | ||
show_shared, | ||
truncate_lists_at, | ||
) | ||
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if __name__ == "__main__": | ||
cli() |
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(For me it would be more natural to write it as a path / URI
channel/namespace/dataset/table
instead of having them separated)