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Implement GT.pipe()
and GT.pipes()
#363
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from __future__ import annotations | ||
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from typing import TYPE_CHECKING, Callable, Any | ||
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if TYPE_CHECKING: | ||
from .gt import GT | ||
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def pipe(self: "GT", func: Callable[..., "GT"], *args: Any, **kwargs: Any) -> "GT": | ||
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. I wonder if we could use ParamSpec here? Something like... from typing import ParamSpec, Callable
P = ParamSpec("P")
def punt(f: Callable[P, int], *args: P.args, **kwargs: P.kwargs) -> int:
return f(*args, **kwargs)
def add(x: int, y: int) -> int:
return x + y
# flagged in static check as z is not an arg to add
punt(add, 1, y = 2, z = 3) https://mypy-play.net/?mypy=latest&python=3.12&gist=23dd2d435071c6e9f5639cfcadf7dd16 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. Of course! This is somewhat new to me, so please feel free to correct me if I've misunderstood anything. 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. @machow and @rich-iannone, this PR has been pending for a while. Could we schedule it for merging, or are there any remaining concerns? |
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""" | ||
Provide a structured way to chain a function for a GT object. | ||
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This function accepts a function that receives a GT object along with optional positional and | ||
keyword arguments, returning a GT object. This allows users to easily integrate a function | ||
into the chained API offered by **Great Tables**. | ||
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Parameters | ||
---------- | ||
func | ||
A function that receives a GT object along with optional positional and keyword arguments, | ||
returning a GT object. | ||
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*args | ||
Optional positional arguments to be passed to the function. | ||
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**kwargs | ||
Optional keyword arguments to be passed to the function. | ||
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Returns | ||
------- | ||
gt | ||
A GT object. | ||
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Examples: | ||
------ | ||
Let's use the `name`, `land_area_km2`, and `density_2021` columns of the `towny` dataset to | ||
create a table. First, we'll demonstrate using two consecutive calls to the `.tab_style()` | ||
method to highlight the maximum value of the `land_area_km2` column with `"lightgray"` and the | ||
maximum value of the `density_2021` column with `"lightblue"`. | ||
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```{python} | ||
import polars as pl | ||
from great_tables import GT, loc, style | ||
from great_tables.data import towny | ||
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towny_mini = pl.from_pandas(towny).head(10) | ||
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( | ||
GT( | ||
towny_mini[["name", "land_area_km2", "density_2021"]], | ||
rowname_col="name", | ||
) | ||
.tab_style( | ||
style=style.fill(color="lightgray"), | ||
locations=loc.body( | ||
columns="land_area_km2", | ||
rows=pl.col("land_area_km2").eq(pl.col("land_area_km2").max()), | ||
), | ||
) | ||
.tab_style( | ||
style=style.fill(color="lightblue"), | ||
locations=loc.body( | ||
columns="density_2021", | ||
rows=pl.col("density_2021").eq(pl.col("density_2021").max()), | ||
), | ||
) | ||
) | ||
``` | ||
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Next, we'll demonstrate how to achieve the same result using the `.pipe()` method to | ||
programmatically style each column. | ||
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```{python} | ||
columns = ["land_area_km2", "density_2021"] | ||
colors = ["lightgray", "lightblue"] | ||
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def tbl_style(gtbl: GT, columns: list[str], colors: list[str]) -> GT: | ||
for column, color in zip(columns, colors): | ||
gtbl = gtbl.tab_style( | ||
style=style.fill(color=color), | ||
locations=loc.body(columns=column, rows=pl.col(column).eq(pl.col(column).max())), | ||
) | ||
return gtbl | ||
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( | ||
GT( | ||
towny_mini[["name", "land_area_km2", "density_2021"]], | ||
rowname_col="name", | ||
).pipe(tbl_style, columns, colors) | ||
) | ||
``` | ||
""" | ||
return func(self, *args, **kwargs) |
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import polars as pl | ||
from great_tables import GT, loc, style | ||
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def test_pipe(): | ||
columns = ["x", "y"] | ||
colors = ["lightgray", "lightblue"] | ||
df = pl.DataFrame(dict(zip(columns, [[1, 2, 3], [3, 2, 1]]))) | ||
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gt1 = ( | ||
GT(df) | ||
.tab_style( | ||
style=style.fill(color=colors[0]), | ||
locations=loc.body( | ||
columns=columns[0], rows=pl.col(columns[0]).eq(pl.col(columns[0]).max()) | ||
), | ||
) | ||
.tab_style( | ||
style=style.fill(color=colors[1]), | ||
locations=loc.body( | ||
columns=columns[1], rows=pl.col(columns[1]).eq(pl.col(columns[1]).max()) | ||
), | ||
) | ||
) | ||
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def tbl_style(gtbl: GT, columns: list[str], colors: list[str]) -> GT: | ||
for column, color in zip(columns, colors): | ||
gtbl = gtbl.tab_style( | ||
style=style.fill(color=color), | ||
locations=loc.body(columns=column, rows=pl.col(column).eq(pl.col(column).max())), | ||
) | ||
return gtbl | ||
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gt2 = GT(df).pipe(tbl_style, columns, colors) # check *args | ||
gt3 = GT(df).pipe(tbl_style, columns=columns, colors=colors) # check **kwargs | ||
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assert gt1._styles == gt2._styles == gt3._styles |
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What about putting pipe in the helper functions section. @rich-iannone WDYT?