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Remove unused python packages (#2437)

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* Remove dependency on following unused python packages by updating
  requirements.txt, LICENSE, standalone binary requirements, cmake and
  docker requirements
    * matplotlib
    * kaleido
    * pymongo
    * colorlover
    * tqdm

* Remove unused code from src/utils/gui.py

* Reformat python using ruff
This commit is contained in:
vedithal-amd
2026-01-07 09:03:49 -05:00
committed by GitHub
parent 1ef6a86ee3
commit 050e88ee71
6 changed files with 6 additions and 93 deletions
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projects/rocprofiler-compute/src/utils/gui.py
+4 -79
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@@ -25,30 +25,20 @@
from typing import Any
import colorlover # type: ignore
import pandas as pd
import plotly.express as px # type: ignore
from dash import dash_table, html # type: ignore
from dash import dash_table # type: ignore
from utils import schema
from utils.logger import console_error
pd.set_option(
"mode.chained_assignment", None
) # ignore SettingWithCopyWarning pandas warning
IS_DARK = True # TODO: Remove hardcoded in favor of class property
##################
# HELPER FUNCTIONS
##################
def filter_df(column: str, df: pd.DataFrame, filt: list[str]) -> pd.DataFrame:
if not filt:
return df
return df.loc[df[schema.PMC_PERF_FILE_PREFIX][column].astype(str).isin(filt)]
####################
# GRAPHICAL ELEMENTS
####################
def multi_bar_chart(
table_id: int, display_df: pd.DataFrame
) -> dict[str, dict[str, Any]]:
@@ -69,68 +59,6 @@ def multi_bar_chart(
return nested_bar
def discrete_background_color_bins(
df: pd.DataFrame, n_bins: int = 5, columns: str | list[str] = "all"
) -> tuple[list[dict[str, Any]], html.Div]:
bounds = [i * (1.0 / n_bins) for i in range(n_bins + 1)]
if columns == "all":
df_numeric_columns = (
df.select_dtypes("number").drop(["id"], axis=1)
if "id" in df.columns
else df.select_dtypes("number")
)
else:
df_numeric_columns = df[columns]
df_max = df_numeric_columns.max().max()
df_min = df_numeric_columns.min().min()
ranges = [((df_max - df_min) * i) + df_min for i in bounds]
styles: list[dict[str, Any]] = []
legend: list[html.Div] = []
for i in range(1, len(bounds)):
min_bound = ranges[i - 1]
max_bound = ranges[i]
background_color = colorlover.scales[str(n_bins)]["seq"]["Blues"][i - 1]
color = "white" if i > len(bounds) / 2.0 else "inherit"
for column in df_numeric_columns.columns:
filter_query = f"{{{column}}} >= {min_bound}" + (
f" && {{{column}}} < {max_bound}" if i < len(bounds) - 1 else ""
)
styles.append({
"if": {
"filter_query": filter_query,
"column_id": column,
},
"backgroundColor": background_color,
"color": color,
})
legend.append(
html.Div(
style={"display": "inline-block", "width": "60px"},
children=[
html.Div(
style={
"backgroundColor": background_color,
"borderLeft": "1px rgb(50, 50, 50) solid",
"height": "10px",
}
),
html.Small(round(min_bound, 2), style={"paddingLeft": "2px"}),
],
)
)
return styles, html.Div(legend, style={"padding": "5px 0 5px 0"})
####################
# GRAPHICAL ELEMENTS
####################
def create_instruction_mix_bar_chart(display_df: pd.DataFrame, df_unit: str) -> px.bar:
display_df = display_df.copy()
display_df["Avg"] = display_df["Avg"].apply(lambda x: int(x) if x != "" else 0)
@@ -294,9 +222,6 @@ def build_bar_chart(
def get_dark_mode_styles() -> tuple[
dict[str, Any], dict[str, Any], list[dict[str, Any]]
]:
if not IS_DARK:
return {}, {}, []
style_header = {
"backgroundColor": "rgb(30, 30, 30)",
"color": "white",