def gen_report_complex_no_files() -> dp.Report:
"""Generate a complex layout report with simple elements"""
select = dp.Select(blocks=[md_block, md_block], type=dp.SelectType.TABS)
group = dp.Group(md_block, md_block, columns=2)
return dp.Report(
dp.Page(
blocks=[
dp.Group(md_block, md_block, columns=2),
dp.Select(blocks=[md_block, group],
type=dp.SelectType.DROPDOWN),
],
title="Page Uno",
),
dp.Page(
blocks=[
dp.Group(select, select, columns=2),
dp.Select(blocks=[md_block, md_block, md_block],
type=dp.SelectType.TABS),
],
title="Page Duo",
),
dp.Page(
blocks=[
dp.Group(group, group, columns=2),
dp.Select(blocks=[select, select], type=dp.SelectType.TABS),
],
title="Page Tres",
),
)
def test_gen_failing_reports():
# local reports with unsupported elements
with pytest.raises(DPError):
r = dp.Report(dp.DataTable(gen_df()))
r._gen_report(embedded=True, title="TITLE", description="DESCRIPTION")
# nested pages
with pytest.raises((DocumentInvalid, DPError)):
r = dp.Report(dp.Page(dp.Page(md_block)))
r._gen_report(embedded=False, title="TITLE", description="DESCRIPTION")
with pytest.raises((DocumentInvalid, DPError)):
r = dp.Report(dp.Group(dp.Page(md_block)))
r._gen_report(embedded=False, title="TITLE", description="DESCRIPTION")
# group with 0 object
with pytest.raises((DocumentInvalid, DPError)):
r = dp.Report(dp.Page(dp.Group(blocks=[])))
r._gen_report(embedded=False, title="TITLE", description="DESCRIPTION")
# select with 1 object
with pytest.raises((DocumentInvalid, DPError)):
r = dp.Report(dp.Page(dp.Select(blocks=[md_block])))
r._gen_report(embedded=False, title="TITLE", description="DESCRIPTION")
# empty text block
with pytest.raises((AssertionError, DocumentInvalid, DPError)):
r = dp.Report(dp.Text(" "))
r._gen_report(embedded=False, title="TITLE", description="DESCRIPTION")
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 test_gen_report_nested_blocks():
s = "# Test markdown block <hello/> \n Test **content**"
report = dp.Report(blocks=[
dp.Group(dp.Text(s, name="test-id-1"),
"Simple string Markdown",
label="test-group-label"),
dp.Select(
blocks=[
dp.Text(s, name="test-id-2", label="test-block-label"),
"Simple string Markdown",
],
label="test-select-label",
),
])
# No additional wrapper block
assert len(report.pages[0].blocks) == 2
assert isinstance(report.pages[0].blocks[0], dp.Group)
assert isinstance(report.pages[0].blocks[1], dp.Select)
assert isinstance(report.pages[0].blocks[1].blocks[1], dp.Text)
assert glom(report, ("pages.0.blocks", ["_attributes.label"])) == [
"test-group-label", "test-select-label"
]
assert glom(report, "pages.0.blocks.0.blocks.0.name") == "test-id-1"
assert glom(
report,
"pages.0.blocks.1.blocks.0._attributes.label") == "test-block-label"
assert_report(report, 0)
def test_gen_failing_reports():
# nested pages
with pytest.raises((DocumentInvalid, DPError)):
r = dp.Report(dp.Page(dp.Page(md_block)))
r._gen_report(embedded=False, title="TITLE", description="DESCRIPTION")
with pytest.raises((DocumentInvalid, DPError)):
r = dp.Report(dp.Group(dp.Page(md_block)))
r._gen_report(embedded=False, title="TITLE", description="DESCRIPTION")
# group with 0 object
with pytest.raises((DocumentInvalid, DPError)):
r = dp.Report(dp.Page(dp.Group(blocks=[])))
r._gen_report(embedded=False, title="TITLE", description="DESCRIPTION")
# select with 1 object
with pytest.raises((DocumentInvalid, DPError)):
r = dp.Report(dp.Page(dp.Select(blocks=[md_block])))
r._gen_report(embedded=False, title="TITLE", description="DESCRIPTION")
# empty text block
with pytest.raises((AssertionError, DocumentInvalid, DPError)):
r = dp.Report(dp.Text(" "))
r._gen_report(embedded=False, title="TITLE", description="DESCRIPTION")
# empty df
with pytest.raises((AssertionError, DocumentInvalid, DPError)):
r = dp.Report(dp.DataTable(pd.DataFrame()))
r._gen_report(embedded=False, title="TITLE", description="DESCRIPTION")
# invalid names
with pytest.raises(DocumentInvalid):
r = dp.Report(dp.Text("a", name="my-name"), dp.Text("a",
name="my-name"))
r._gen_report(embedded=False, title="TITLE", description="DESCRIPTION")
with pytest.raises(DPError):
dp.Report(dp.Text("a", name="3-invalid-name"))
def test_gen_report_nested_mixed():
report = dp.Report(
dp.Group(
md_block_id,
str_md_block,
),
"Simple string Markdown #2",
)
assert_report(report, 0)
assert len(glom(report, "pages.0.blocks")) == 1
assert isinstance(glom(report, "pages.0.blocks.0"), dp.Group)
assert isinstance(report.pages[0].blocks[0].blocks[0], dp.Group)
assert isinstance(report.pages[0].blocks[0].blocks[1], dp.Text)
assert report.pages[0].blocks[0].blocks[0].blocks[0].name == "test-id-1"
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',
blocks=[f'### Kernel Density Plot ',
dp.Plot(exams_kdp)]),
response_rate = "80%"
nps_score = "52%"
report = dp.Report(
dp.Text(executive_summary_pt1).format(
# nps_score=nps_score,
# responce_rate=response_rate,
most_positive=most_positive_answers,
most_negative=most_negative_answers,
),
dp.Text("#### Trend Charts"),
dp.Group(
dp.File(file="images/largest_since_fy18_plot.png"),
dp.File(file="images/smallest_since_fy18_plot.png"),
columns=2,
),
dp.Group(
dp.File(file="images/largest_since_fy20_plot.png"),
dp.File(file="images/smallest_since_fy20_plot.png"),
columns=2,
),
dp.Text(file="text/executive_summary_pt2.md").format(
ct_site_plot=dp.File(file="images/ct_site_section_plot.png"),
academic_affairs_plot=dp.File(
file="images/academic_affairs_section_plot.png"),
student_life_plot=dp.File(file="images/student_life_section_plot.png"),
college_prep_plot=dp.File(file="images/college_prep_section_plot.png"),
coaching_plot=dp.File(
file="images/coaching_programming_section_plot.png"),
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)**.
""", chart_final
],
label='Interactive Plot'),
nflx = nflx[['Open', 'Close', 'Volume']]
nflx["index"] = np.arange(len(nflx))
fig8 = go.Figure(
ff.create_scatterplotmatrix(nflx,
diag='box',
index='index',
size=3,
height=600,
width=1150,
colormap='RdBu',
title={
'text':
"Netflix Stock Price (Scatterplot Matrix)",
'x': 0.5,
'xanchor': 'center'
}))
dp.Report(
dp.Group(dp.Plot(fig0),
dp.Plot(fig1),
dp.Plot(fig2),
dp.Plot(fig3),
dp.Plot(fig4),
dp.Plot(fig5),
dp.Plot(fig6),
dp.Plot(fig7),
columns=2,
rows=4), dp.Plot(fig8)).publish(name='stock_report', open=True)
