def card(node: pipelines.Node) -> str:
"""A card that shows the system stats, the time line and output for the last runs or a node"""
return bootstrap.card(
id='last-runs-card',
header_left=[
'Last runs ',
_.div(style='display:inline-block;margin-left:20px;')[
html.asynchronous_content(
flask.url_for('mara_pipelines.last_runs_selector',
path=node.url_path()))]
],
body=[
html.spinner_js_function(),
html.asynchronous_content(url=flask.url_for(
'mara_pipelines.system_stats',
path=node.url_path(),
run_id=None),
div_id='system-stats'),
html.asynchronous_content(url=flask.url_for(
'mara_pipelines.timeline_chart',
path=node.url_path(),
run_id=None),
div_id='timeline-chart'),
html.asynchronous_content(url=flask.url_for(
'mara_pipelines.run_output',
path=node.url_path(),
run_id=None,
limit=True),
div_id='run-output')
])
def index_page() -> response.Response:
"""Renders the overview page"""
from ..config import data_sets
return response.Response(html=[
bootstrap.card(header_left='Entities & their relations',
body=html.asynchronous_content(
flask.url_for('mara_schema.overview_graph'))),
bootstrap.card(
header_left='Data sets',
body=bootstrap.table(['Name', 'Description'], [
_.tr[_.td[_.a(
href=flask.
url_for('mara_schema.data_set_page', id=data_set.id()
))[escape(data_set.name)]],
_.td[_.i[escape(data_set.entity.description)]], ]
for data_set in data_sets()
]),
)
],
title='Data sets documentation',
css_files=[
flask.url_for('mara_schema.static',
filename='schema.css')
])
def __(pipeline: pipelines.Pipeline):
return bootstrap.card(
header_left='Nodes',
header_right=[
bootstrap.button(
id='run-with-upstreams-button',
label='Run with upstreams',
icon='play',
url=flask.url_for('data_integration.run_page',
path=pipeline.url_path(),
with_upstreams=True),
title=
f'Run selected nodes with all their upstreams in pipeline "{pipeline.id}"'
), ' ',
bootstrap.button(id='run-button',
label='Run ',
icon='play',
url=flask.url_for('data_integration.run_page',
path=pipeline.url_path(),
with_upstreams=False),
title='Run selected nodes')
] if config.allow_run_from_web_ui() else [],
body=html.asynchronous_content(
url=flask.url_for('data_integration.pipeline_children_table',
path=pipeline.url_path())))
def card(node: pipelines.Pipeline):
return bootstrap.card(body=[
_.p[_.em[node.description]],
(_.p[views.format_labels(node)] if node.labels else ''),
html.asynchronous_content(
flask.url_for('data_integration.dependency_graph',
path=node.url_path()))
])
def index_page():
return response.Response(
html=[bootstrap.card(
header_left=_.a(href=flask.url_for('mara_data_explorer.data_set_page', data_set_id=ds.id))[ds.name],
body=[html.asynchronous_content(flask.url_for('mara_data_explorer.data_set_preview', data_set_id=ds.id))])
for i, ds in enumerate(config.data_sets())],
title='Data sets',
js_files=[flask.url_for('mara_data_explorer.static', filename='data-sets.js')],
css_files=[flask.url_for('mara_data_explorer.static', filename='data-sets.css')])
def index_page(db_alias: str):
"""A page that visiualizes the schemas of a database"""
if db_alias not in config.databases():
flask.abort(404, f'unkown database {db_alias}')
return response.Response(
title=f'Schema of database {db_alias}',
html=[bootstrap.card(sections=[
html.asynchronous_content(flask.url_for('mara_db.schema_selection', db_alias=db_alias)),
[_.div(id='schema-container')]]),
html.spinner_js_function()],
js_files=[flask.url_for('mara_db.static', filename='schema-page.js')],
action_buttons=[response.ActionButton(
action='javascript:schemaPage.downloadSvg()', label='SVG',
title='Save current chart as SVG file', icon='download')]
)
def start_page():
import mara_pipelines.config
from mara_data_explorer.data_set import find_data_set
data_set_for_preview = find_data_set('order_items')
assert (data_set_for_preview)
return response.Response(
title='MyCompany BI',
html=_.div(class_='row')[_.div(
class_='col-lg-6'
)[bootstrap.
card(header_left=_.b['Welcome'],
body=[
_.
p['This is the first thing that users of your data warehouse will see. ',
'Please add links to relevant documentation, tutorials & other ',
'data tools in your organization.'], _.p[
_.a(href='https://github.com/mara/mara-example-project-1/blob/master/app/ui/start_page.py'
)[
'Here'],
' is the source code for this page, and here is a picture of a ',
_.a(href='https://en.wikipedia.org/wiki/Mara_(mammal)'
)[
'mara'], ':'],
_.
img(src=flask.url_for('ui.static', filename='mara.jpg'),
style
='width:40%; margin-left: auto; margin-right:auto; display:block;'
)
]),
bootstrap.card(header_left=[
_.b[_.a(href=flask.url_for('mara_metabase.metabase'))[_.span(
class_='fa fa-bar-chart')[''], ' Metabase']], ' & ', _.
b[_.a(href=flask.url_for('mara_mondrian.saiku'))[_.span(
class_='fa fa-bar-chart')[''], ' Saiku']],
': Company wide dashboards, pivoting & ad hoc analysis'
],
body=[
_.
p['Metabase tutorial: ',
_.
a(href=
'https://www.metabase.com/docs/latest/getting-started.html'
)
['https://www.metabase.com/docs/latest/getting-started.html']],
_.
p['Saiku introduction: ',
_.
a(href=
'https://saiku-documentation.readthedocs.io/en/latest/'
)
['https://saiku-documentation.readthedocs.io/en/latest/']]
]),
bootstrap.card(header_left=[
_.b[_.a(href=flask.url_for('mara_data_explorer.index_page'))[
_.span(class_='fa fa-table')[''],
' Explore']], ': Raw data access & segmentation'
],
body=[
_.p[_.a(
href=flask.
url_for('mara_data_explorer.data_set_page',
data_set_id=data_set_for_preview.id
))[data_set_for_preview.name], ':',
html.asynchronous_content(
flask.url_for(
'mara_data_explorer.data_set_preview',
data_set_id=data_set_for_preview.id)
)], _.
p['Other data sets: ', ', '.join([
str(
_.a(href=flask.url_for(
'mara_data_explorer.data_set_page',
data_set_id=ds.id))[ds.name])
for ds in mara_data_explorer.config.data_sets(
) if ds.id != data_set_for_preview.id
])]
])],
_.div(class_='col-lg-6')
[bootstrap.
card(header_left=[
_.b[_.a(href=flask.url_for(
'mara_schema.index_page'))[_.span(
class_='fa fa-book'
)[''], ' Data sets']],
': Documentation of attributes and metrics of all data sets'
],
body=html.asynchronous_content(
url=flask.
url_for('mara_schema.overview_graph'
))),
bootstrap.card(header_left=[
_.b[_.a(
href=flask.
url_for('mara_pipelines.node_page')
)[_.span(class_='fa fa-wrench')[''],
' Pipelines']],
': The data integration pipelines that create the DWH'
],
body=html.
asynchronous_content(
flask.url_for(
'mara_pipelines.dependency_graph',
path='/'))),
bootstrap.card(header_left=[
_.b[_.a(href=flask.
url_for('mara_db.index_page')
)[_.span(
class_='fa fa-database')[''],
' Database Schemas']],
': Schemas of all databases connections'
],
body=[
html.asynchronous_content(
flask.url_for(
'mara_db.draw_schema',
db_alias=
mara_pipelines.
config.
default_db_alias(
),
schemas='ec_dim'
) +
'?hide-columns=True')
])]])
def data_set_page(id: str) -> response.Response:
"""Renders the pages for individual data sets"""
from ..config import data_sets
data_set = next(
(data_set for data_set in data_sets() if data_set.id() == id), None)
if not data_set:
flask.flash(f'Could not find data set "{id}"', category='warning')
return flask.redirect(flask.url_for('mara_schema.index_page'))
base_url = flask.url_for('mara_schema.data_set_sql_query',
id=data_set.id())
def attribute_rows(data_set: DataSet) -> []:
rows = []
for path, attributes in data_set.connected_attributes().items():
if path:
rows.append(_.tr[_.td(
colspan=3, style='border-top:none; padding-top: 20px;'
)[[[
'→ ',
_.a(
href=data_set_url(entity.data_set)
)[link_title] if entity.data_set else link_title, ' '
] for entity, link_title in [(
entity_link.target_entity,
entity_link.prefix or entity_link.target_entity.name)
for entity_link in path]],
[' ', _.
i[path[-1].description]] if path[-1].description else '']])
for prefixed_name, attribute in attributes.items():
rows.append(_.tr[_.td[escape(prefixed_name)], _.td[_.i[escape(
attribute.description
)]], _.td[_.tt[escape(
f'{path[-1].target_entity.table_name + "." if path else ""}{attribute.column_name}'
)]]])
return rows
return response.Response(
html=[
bootstrap.card(
header_left=_.i[escape(data_set.entity.description)],
body=[
_.p['Entity table: ', _.code[escape(
f'{data_set.entity.schema_name}.{data_set.entity.table_name}'
)]],
html.asynchronous_content(
flask.url_for('mara_schema.data_set_graph',
id=data_set.id())),
]),
bootstrap.card(
header_left='Metrics',
body=[
html.asynchronous_content(
flask.url_for('mara_schema.metrics_graph',
id=data_set.id())),
bootstrap.table(['Name', 'Description', 'Computation'], [[
_.tr[_.td[escape(metric.name)],
_.td[_.i[escape(metric.description)]],
_.td[_.code[escape(metric.display_formula())]]]
for metric in data_set.metrics.values()
]]),
]),
bootstrap.card(header_left='Attributes',
body=bootstrap.table(
["Name", "Description", "Column name"],
attribute_rows(data_set))),
bootstrap.card(
header_left=[
'Data set sql query: ',
[
_.div(class_='form-check form-check-inline')
[" ",
_.label(class_='form-check-label')[
_.input(class_="form-check-input param-checkbox",
type="checkbox",
value=param)[''], ' ', param]]
for param in [
'human readable columns',
'pre-computed metrics',
'star schema',
'personal data',
'high cardinality attributes',
]
]
],
body=[
_.div(id='sql-container')[html.asynchronous_content(
base_url, 'sql-container')], _.script['''
document.addEventListener('DOMContentLoaded', function() {
DataSetSqlQuery("''' + base_url + '''");
});
''']
])
],
title=f'Data set "{data_set.name}"',
js_files=[
flask.url_for('mara_schema.static',
filename='data-set-sql-query.js')
],
)
def card(node: pipelines.Node):
"""A card that shows the duration of the node and its top children over time"""
return bootstrap.card(header_left='Run times',
body=html.asynchronous_content(
flask.url_for('mara_pipelines.run_time_chart',
path=node.url_path())))
def view_plots():
return response.Response(
html=[
_.div(id='forecast-container')[_.div(class_="")[[
[
_.div(class_='row')[_.div(class_='col-xl-12')[_.div(
class_='section-header')[forecast.metric_name]]],
_.div(class_='row')[_.div(class_='col-xl-12')[
_.p()['Number of days: ' +
str(forecast.number_of_days),
_.br(), 'Time-series query: ',
html.highlight_syntax(forecast.time_series_query,
language='postgresql')],
bootstrap.card(
header_left='Forecast plot of "' +
forecast.metric_name + '"',
header_right=_.div()[
# config.forecast_table_name
# _.a(class_='query-control', style='margin-right: 10px',
# href='#')[
# _.span(class_='fa fa-download')[' ']],
_.
a(class_='query-control',
href=f"javascript:showQueryDetails('"
f"{flask.url_for('forecasts.query_details', name=forecast.metric_name)}')"
)[_.span(class_='fa fa-eye')[' ']]],
body=[
html.asynchronous_content(
flask.url_for('forecasts.get_plot_image',
name=forecast.metric_name.
lower().replace(' ', '_').
replace('-', '_'),
components='False')),
_.br(),
_.br(),
_.div(class_='modal fade',
id='query-details-dialog',
tabindex="-1"
)[_.div(class_='modal-dialog modal-lg',
role='document')[_.div(
class_='modal-content'
)[_.div(
class_='modal-header'
)[_.h5(class_='modal-title'
)['Time-series query'],
_.button(
**{
'type': "button",
'class': "close",
'data-dismiss': "modal",
'aria-label': "Close"
}
)[_.span(
**{'aria-hidden': 'true'}
)['×']]],
_.div(class_='modal-body',
id='query-details'
)['']]]],
])],
_.
div(class_='col-xl-12')[bootstrap.card(
header_left=
'Forecast components (trend, holidays, seasonality) of "{}"'
.format(forecast.metric_name),
header_right='',
body=[
html.asynchronous_content(
flask.url_for(
'forecasts.get_plot_image',
name=forecast.
metric_name.lower(
).replace(' ', '_').
replace('-', '_'),
components='True')),
])],
_.hr()]
] for forecast in config.forecasts()
]]],
_.script['''''']
],
title='Forecasts',
css_files=[
'https://fonts.googleapis.com/css?family=Open+Sans:300,400,700',
flask.url_for('forecasts.static', filename='forecast.css')
],
js_files=[
flask.url_for('forecasts.static', filename='forecast.js'),
'https://www.gstatic.com/charts/loader.js'
])
