def gen_report_complex_with_files(datadir: Path,
single_file: bool = False,
local_report: bool = False) -> dp.Report:
# Asset tests
lis = [1, 2, 3]
small_df = gen_df()
big_df = gen_df(10000)
# text
# md_block
html_block = dp.HTML(html="<h1>Hello World</h1>")
html_block_1 = dp.HTML(html=h2("Hello World"))
code_block = dp.Code(code="print('hello')", language="python")
formula_block = dp.Formula(formula=r"\frac{1}{\sqrt{x^2 + 1}}")
big_number = dp.BigNumber(heading="Tests written", value=1234)
big_number_1 = dp.BigNumber(heading="Real Tests written :)",
value=11,
change=2,
is_upward_change=True)
embed_block = dp.Embed(url="https://www.youtube.com/watch?v=JDe14ulcfLA")
# assets
plot_asset = dp.Plot(data=gen_plot(), caption="Plot Asset")
list_asset = dp.File(data=lis, filename="List Asset", is_json=True)
img_asset = dp.File(file=datadir / "datapane-logo.png")
# tables
table_asset = dp.Table(data=small_df, caption="Test Basic Table")
# local reports don't support DataTable
dt_asset = table_asset if local_report else dp.DataTable(
df=big_df, caption="Test DataTable")
if single_file:
return dp.Report(dp.Group(blocks=[md_block, dt_asset]))
else:
return dp.Report(
dp.Page(
dp.Select(md_block,
html_block,
html_block_1,
code_block,
formula_block,
embed_block,
type=dp.SelectType.TABS),
dp.Group(big_number, big_number_1, columns=2),
),
dp.Page(
plot_asset,
list_asset,
img_asset,
table_asset,
dt_asset,
),
)
def gen_report_with_files(datadir: Path,
single_file: bool = False) -> dp.Report:
# Asset tests
lis = [1, 2, 3]
small_df = gen_df()
big_df = gen_df(10000)
# text
md_block = dp.Markdown(
text="# Test markdown block </hello> \n Test **content**")
html_block = dp.HTML(html="Hello World</hello>")
big_number = dp.BigNumber(heading="Tests written", value=1234)
big_number_1 = dp.BigNumber(heading="Real Tests written :)",
value=11,
change=2,
is_upward_change=True)
# assets
plot_asset = dp.Plot(data=alt.Chart(gen_df()).mark_line().encode(x="x",
y="y"),
caption="Plot Asset")
list_asset = dp.File(data=lis, name="List Asset", is_json=True)
img_asset = dp.File(file=datadir / "datapane-logo.png")
# tables
table_asset = dp.Table(data=small_df, caption="Test Basic Table")
dt_asset = dp.DataTable(df=big_df, caption="Test DataTable")
dt_pivot_asset = dp.DataTable(df=big_df,
caption="Test DataTable with Pivot",
can_pivot=True)
if single_file:
return dp.Report(dp.Blocks(blocks=[md_block, plot_asset]))
else:
return dp.Report(
md_block,
html_block,
big_number,
big_number_1,
plot_asset,
list_asset,
img_asset,
table_asset,
dt_asset,
dt_pivot_asset,
)
race_bar.update_layout(xaxis_title='assignment',
yaxis_title='average',
legend_title='Race',
legend_bordercolor='black',
legend_borderwidth=2,
barmode='group',
bargap=.3)
# Create report
r = dp.Report(
dp.Page(
label='Introduction',
blocks=[
dp.HTML(html),
"The data has been compiled over 3 semesters, for the introductory computer science class CSE 1223.",
dp.Group(dp.BigNumber(heading="Number of Students",
value=num_students),
dp.BigNumber(heading="Class Average",
value=str(class_average) + "%",
change="2%",
is_upward_change=True),
columns=2),
dp.BigNumber(heading="Pass Rate", value=str(pass_rate) + "%"),
]),
dp.Page(label='Deliverables',
blocks=[
f'### Labs',
dp.Plot(lab_bar), f'### Homeworks',
dp.Plot(hw_bar), f'### Projects',
dp.Plot(project_bar)
]),
dp.Page(label='Exam Grades',
"""# Building a Datapane report
Now that we have a series of plots, we can create a report using Datapane.
In addition to the visualizations, this report includes Datapane's `BigNumber` component to display top level KPIs, and our `DataTable` component to allow our viewers to filter, explore, and download the data themselves.
Although we could create a linear list of all blocks (similar to how they are displayed in this notebook), we can build a more powerful and accessible report by using Datapane's [layout components](https://docs.datapane.com/reports/blocks/layout-pages-and-selects).
From these components, we are using `Group` to place the `BigNumber` blocks in two columns, have used the `Page` block to add multiple pages to our report, and are using the `Select` block to create tabs where users can choose their dataset. This results in a beautiful, interactive document which we can publish and share.
"""
dp.Report(
"# Finance Model",
dp.Group(blocks=[
dp.BigNumber(value=f"${round(burn)}", heading="Monthly outgoings"),
dp.BigNumber(value=f"${CURRENT_CASH_GBP}",
heading="Cash in bank",
is_upward_change=True,
change=7)
],
columns=2),
dp.Select(blocks=[
dp.Group(blocks=[
"""This plot models cash and revenue, dependent on various other growth scenarios and based on this month's burn.
- Blue area is cash remaining
- Orange line is the cumulative sum of all revenue
- Purple line is monthly revenue
> Drag the slider to adjust growth rate. The growth rate at which the blue area never crosses 0 is the growth you need to achieve **[Default Alive](http://paulgraham.com/aord.html)**.