from typing import TYPE_CHECKING, List, Optional, Union
from flytekit import lazy_module
from flytekit.types.file import FlyteFile
if TYPE_CHECKING:
import markdown
import pandas as pd
import PIL.Image
import plotly.express as px
else:
pd = lazy_module("pandas")
markdown = lazy_module("markdown")
px = lazy_module("plotly.express")
PIL = lazy_module("PIL")
[docs]class FrameProfilingRenderer:
"""
Generate a ProfileReport based on a pandas DataFrame
"""
def __init__(self, title: str = "Pandas Profiling Report"):
self._title = title
[docs] def to_html(self, df: "pd.DataFrame") -> str:
assert isinstance(df, pd.DataFrame)
import ydata_profiling
profile = ydata_profiling.ProfileReport(df, title=self._title)
return profile.to_html()
[docs]class MarkdownRenderer:
"""Convert a markdown string to HTML and return HTML as a unicode string.
This is a shortcut function for `Markdown` class to cover the most
basic use case. It initializes an instance of Markdown, loads the
necessary extensions and runs the parser on the given text.
"""
[docs] def to_html(self, text: str) -> str:
return markdown.markdown(text)
[docs]class BoxRenderer:
"""
In a box plot, rows of `data_frame` are grouped together into a
box-and-whisker mark to visualize their distribution.
Each box spans from quartile 1 (Q1) to quartile 3 (Q3). The second
quartile (Q2) is marked by a line inside the box. By default, the
whiskers correspond to the box edges +/- 1.5 times the interquartile
range (IQR: Q3-Q1), see "points" for other options.
"""
# More detail, see https://plotly.com/python/box-plots/
def __init__(self, column_name):
self._column_name = column_name
[docs] def to_html(self, df: "pd.DataFrame") -> str:
fig = px.box(df, y=self._column_name)
return fig.to_html()
[docs]class ImageRenderer:
"""Converts a FlyteFile or PIL.Image.Image object to an HTML string with the image data
represented as a base64-encoded string.
"""
[docs] def to_html(self, image_src: Union[FlyteFile, "PIL.Image.Image"]) -> str:
img = self._get_image_object(image_src)
return self._image_to_html_string(img)
@staticmethod
def _get_image_object(image_src: Union[FlyteFile, "PIL.Image.Image"]) -> "PIL.Image.Image":
if isinstance(image_src, FlyteFile):
local_path = image_src.download()
return PIL.Image.open(local_path)
elif isinstance(image_src, PIL.Image.Image):
return image_src
else:
raise ValueError("Unsupported image source type")
@staticmethod
def _image_to_html_string(img: "PIL.Image.Image") -> str:
import base64
from io import BytesIO
buffered = BytesIO()
img.save(buffered, format="PNG")
img_base64 = base64.b64encode(buffered.getvalue()).decode()
return f'<img src="data:image/png;base64,{img_base64}" alt="Rendered Image" />'
[docs]class TableRenderer:
"""
Convert a pandas DataFrame into an HTML table.
"""
[docs] def to_html(self, df: pd.DataFrame, header_labels: Optional[List] = None, table_width: Optional[int] = None) -> str:
# Check if custom labels are provided and have the correct length
if header_labels is not None and len(header_labels) == len(df.columns):
df = df.copy()
df.columns = header_labels
style = f"""
<style>
.table-class {{
border: 1px solid #ccc; /* Add a thin border around the table */
border-collapse: collapse;
font-family: Arial, sans-serif;
color: #333;
{f'width: {table_width}px;' if table_width is not None else ''}
}}
.table-class th, .table-class td {{
border: 1px solid #ccc; /* Add a thin border around each cell */
padding: 8px; /* Add some padding inside each cell */
}}
/* Set the background color for even rows */
.table-class tr:nth-child(even) {{
background-color: #f2f2f2;
}}
/* Add a hover effect to the rows */
.table-class tr:hover {{
background-color: #ddd;
}}
/* Center the column headers */
.table-class th {{
text-align: center;
}}
</style>
"""
return style + df.to_html(classes="table-class", index=False)
class GanttChartRenderer:
"""
This renderer is primarily used by the timeline deck. The input DataFrame should
have at least the following columns:
- "Start": datetime.datetime (represents the start time)
- "Finish": datetime.datetime (represents the end time)
- "Name": string (the name of the task or event)
"""
def to_html(self, df: pd.DataFrame, chart_width: Optional[int] = None) -> str:
fig = px.timeline(df, x_start="Start", x_end="Finish", y="Name", color="Name", width=chart_width)
fig.update_xaxes(
tickangle=90,
rangeslider_visible=True,
tickformatstops=[
dict(dtickrange=[None, 1], value="%3f ms"),
dict(dtickrange=[1, 60], value="%S:%3f s"),
dict(dtickrange=[60, 3600], value="%M:%S m"),
dict(dtickrange=[3600, None], value="%H:%M h"),
],
)
# Remove y-axis tick labels and title since the time line deck space is limited.
fig.update_yaxes(showticklabels=False, title="")
fig.update_layout(
autosize=True,
# Set the orientation of the legend to horizontal and move the legend anchor 2% beyond the top of the timeline graph's vertical axis
legend=dict(orientation="h", y=1.02),
)
return fig.to_html()
