def gen_report_with_files(datadir: Path,
single_file: bool = False) -> dp.Report:
# Asset tests
lis = [1, 2, 3]
df = gen_df(10000)
md_block = dp.Markdown(
text="# Test markdown block <hello/> \n Test **content**")
list_asset = dp.File(data=lis, name="List Asset", is_json=True)
img_asset = dp.File(file=datadir / "datapane-logo.png")
plot_asset = dp.Plot(data=alt.Chart(gen_df()).mark_line().encode(x="x",
y="y"),
caption="Plot Asset")
df_asset = dp.Table(df=df, caption="Test Dataframe Table")
pivot_asset = dp.Table(df=df,
caption="Test Dataframe PivotTable",
can_pivot=True)
if single_file:
return dp.Report(dp.Blocks([md_block, plot_asset]))
else:
return dp.Report(list_asset, img_asset, df_asset, md_block, plot_asset,
pivot_asset)
def test_full_report(tmp_path: Path):
df = gen_df()
name = gen_name()
description = gen_description()
source_url = "https://github.com/datapane/datapane"
# create a basic report
m = dp.Text("hello world!!")
# Asset tests
lis = [1, 2, 3]
json_list: str = json.dumps(lis)
plot = gen_plot()
# create the DP
fn = tmp_path / "json_list.json"
fn.write_text(data=json_list)
file_asset = dp.File(file=fn)
json_asset = dp.File(data=json_list, is_json=True)
plot_asset = dp.Plot(data=plot)
list_asset = dp.File(data=lis, is_json=True)
df_asset = dp.DataTable(df=df, caption="Our Dataframe")
dp_report = dp.Report(m, file_asset, df_asset, json_asset, plot_asset, list_asset)
dp_report.upload(name=name, description=description, source_url=source_url)
with deletable(dp_report):
# are the fields ok
check_name(dp_report, name)
assert dp_report.description == description
assert dp_report.source_url == source_url
assert len(dp_report.pages[0].blocks[0].blocks) == 6
def test_report(tmp_path: Path):
df = gen_df()
name = gen_name()
headline = gen_headline()
# create a basic report
m = dp.Markdown("hello world!!")
# Asset tests
lis = [1, 2, 3]
json_list: str = json.dumps(lis)
plot = alt.Chart(df).mark_line().encode(x="x", y="y")
# create the DP
fn = tmp_path / "json_list.json"
fn.write_text(data=json_list)
file_asset = dp.File(file=fn)
json_asset = dp.File(data=json_list, is_json=True)
plot_asset = dp.Plot(data=plot)
list_asset = dp.File(data=lis, is_json=True)
df_asset = dp.Table(df=df, caption="Our Dataframe")
dp_report = api.Report(m, file_asset, df_asset, json_asset, plot_asset, list_asset)
dp_report.publish(name=name, headline=headline)
with deletable(dp_report):
# are the fields ok
assert dp_report.headline == headline
assert len(dp_report.top_block.blocks) == 6
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,
)
go.Scatter(
x=[0, 1, 2, 3, 4, 5],
y=[1.5, 1, 1.3, 0.7, 0.8, 0.9]
))
fig.add_trace(
go.Bar(
x=[0, 1, 2, 3, 4, 5],
y=[1, 0.5, 0.7, -1.2, 0.3, 0.4]
))
plotly_asset = dp.Plot(data=fig)
# Markdown
md_block = dp.Markdown(text="# Test markdown block \n Test **content**")
# In-line JSON
list_asset = dp.File(data=lis, is_json=True)
# Downloadable file
file_asset = dp.File(data=lis)
# In-line image
img_asset = dp.File(file=Path("./datapane-logo.png"))
# Vega
vega_asset = dp.Plot(data=alt.Chart(gen_df()).mark_line().encode(x="x", y="y"))
# Table
df_asset = dp.DataTable(df, can_pivot=False)
# Pivot table
pv_asset = dp.DataTable(gen_df(10), can_pivot=True)
most_positive_sites[:-2] + [", and ".join(most_positive_sites[-2:])])
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(
