def schema_selection(db_alias: str):
"""Asynchronously computes the list of schemas with foreign key constraints"""
schemas_with_fk_constraints = schemas_with_foreign_key_constraints(db_alias)
if not schemas_with_fk_constraints or len(schemas_with_fk_constraints) == 0:
return str(_.i['No schemas with foreign key constraints found'])
return ''.join(xml.render([
[_.div(class_='form-check form-check-inline')[
_.label(class_='form-check-label')[
_.input(class_="form-check-input schema-checkbox", type="checkbox", value=schema_name)[
''], ' ', schema_name]]
for schema_name in sorted(schemas_with_fk_constraints)],
'   ',
_.div(class_='form-check form-check-inline')[
_.label(class_='form-check-label')[
_.input(class_="form-check-input", id='hide-columns-checkbox', type="checkbox")[
''], ' ', 'hide columns']],
'   ',
_.div(class_='form-check form-check-inline')[
_.label(class_='form-check-label')[
'graphviz engine ',
_.select(id='engine', style='border:none;background-color:white;')[
[_.option(value=engine)[engine] for engine in ['neato', 'dot', 'twopi', 'fdp']]
]]],
_.script['''
var schemaPage = SchemaPage("''' + flask.url_for('mara_db.index_page', db_alias=db_alias) + '''", "''' + db_alias + '''");
''']]))
def pipeline_children_table(path: str):
"""Creates a table that documents all child nodes of a table"""
pipeline, __ = pipelines.find_node(path.split('/'))
assert (isinstance(pipeline, pipelines.Pipeline))
node_durations_and_run_times = node_cost.node_durations_and_run_times(pipeline.path())
rows = []
for node in pipeline.nodes.values():
[avg_duration, avg_run_time] = node_durations_and_run_times.get(tuple(node.path()), ['', ''])
rows.append(
_.tr[_.td[_.a(href=views.node_url(node))[node.id.replace('_', '_<wbr>')]],
_.td[node.description],
_.td[views.format_labels(node)],
_.td[node_cost.format_duration(avg_duration)],
_.td(style='color:#bbb' if avg_duration == avg_run_time else '')[
node_cost.format_duration(avg_run_time)],
_.td[node_cost.format_duration(
node_cost.compute_cost(node, node_durations_and_run_times))],
_.td[(_.input(class_='pipeline-node-checkbox', type='checkbox',
value=node.id, name='ids[]', onchange='runButtons.update()')
if config.allow_run_from_web_ui() else '')]])
return \
str(_.script['var runButtons = new PipelineRunButtons();']) \
+ str(bootstrap.table(['ID', 'Description', '', 'Avg duration', 'Avg run time', 'Cost', ''], rows)) \
+ str(_.script['floatMaraTableHeaders();'])
def schema_selection(db_alias: str):
"""Asynchronously computes the list of schemas with foreign key constraints"""
schemas_with_fk_constraints = []
with mara_db.postgresql.postgres_cursor_context(db_alias) as cursor:
cursor.execute('''
SELECT
array_cat(array_agg(DISTINCT constrained_table_schema.nspname), array_agg(DISTINCT referenced_table_schema.nspname))
FROM pg_constraint
JOIN pg_class constrained_table ON constrained_table.oid = pg_constraint.conrelid
JOIN pg_namespace constrained_table_schema ON constrained_table.relnamespace = constrained_table_schema.oid
JOIN pg_class referenced_table ON referenced_table.oid = pg_constraint.confrelid
JOIN pg_namespace referenced_table_schema ON referenced_table.relnamespace = referenced_table_schema.oid'''
)
result = cursor.fetchone()
if result != (None, ):
schemas_with_fk_constraints = sorted(list(set(result[0])))
if len(schemas_with_fk_constraints) == 0:
return str(_.i['No schemas with foreign key constraints found'])
return ''.join(
xml.render(
[[
_.div(class_='form-check form-check-inline')[_.label(
class_='form-check-label')[
_.input(class_="form-check-input schema-checkbox",
type="checkbox",
value=schema_name)[''], ' ', schema_name]]
for schema_name in sorted(schemas_with_fk_constraints)
], '   ',
_.div(class_='form-check form-check-inline')[_.label(
class_='form-check-label')[_.input(class_="form-check-input",
id='hide-columns-checkbox',
type="checkbox")[''], ' ',
'hide columns']], '   ',
_.div(class_='form-check form-check-inline')[_.label(
class_='form-check-label'
)['graphviz engine ',
_.select(id='engine',
style='border:none;background-color:white;')[[
_.option(value=engine)[engine]
for engine in ['neato', 'dot', 'twopi', 'fdp']
]]]], _.script['''
var schemaPage = SchemaPage("''' + flask.url_for('mara_db.index_page',
db_alias=db_alias) +
'''", "''' + db_alias + '''");
''']]))
def data_set_page(data_set_id, query_id):
from .data_set import find_data_set
ds = find_data_set(data_set_id)
if not ds:
flask.flash(f'Data set "{data_set_id}" does not exist anymore', category='danger')
return flask.redirect(flask.url_for('mara_data_explorer.index_page'))
action_buttons = []
action_buttons.append(response.ActionButton(action='javascript:dataSetPage.downloadCSV()',
icon='download',
label='CSV', title='Download as CSV'))
if config.google_sheet_oauth2_client_config():
action_buttons.append(response.ActionButton(action='javascript:dataSetPage.exportToGoogleSheet()',
icon='cloud-upload',
label='Google sheet', title='Export to a Google sheet'))
action_buttons.append(response.ActionButton(action='javascript:dataSetPage.load()',
icon='folder-open',
label='Load', title='Load previously saved query'))
action_buttons.append(response.ActionButton(action='javascript:dataSetPage.save()',
icon='save',
label='Save', title='Save query'))
action_buttons.append(response.ActionButton(action='javascript:dataSetPage.displayQuery()',
icon='eye',
label='SQL', title='Display query'))
if query_id:
action_buttons.insert(1, response.ActionButton(
action=flask.url_for('mara_data_explorer._delete_query', data_set_id=data_set_id, query_id=query_id),
icon='trash', label='Delete', title='Delete query'))
return response.Response(
title=f'Query "{query_id}" on "{ds.name}"' if query_id else f'New query on "{ds.name}"',
html=[_.div(class_='row')[
_.div(class_='col-md-3')[
bootstrap.card(header_left='Query', body=_.div(id='query-details')[html.spinner()]),
bootstrap.card(header_left='Columns',
header_right=_.a(id='select-all', href='#')[' Select all'],
body=[_.div(class_="form-group")[
_.input(type="search", class_="columns-search form-control",
value="", placeholder="Filter")],
_.div(id='columns-list')[html.spinner()]])],
_.div(class_='col-md-9')[
bootstrap.card(
id='filter-card',
header_left=[_.div(class_="dropdown")[
_.a(**{'class': 'dropdown-toggle', 'data-toggle': 'dropdown', 'href': '#'})[
_.span(class_='fa fa-plus')[' '], ' Add filter'],
_.div(class_="dropdown-menu", id='filter-menu')[
_.div(class_="dropdown-item")[
_.input(type="text", class_="columns-search form-control", value="",
placeholder="Filter")]]]],
fixed_header_height=False,
body=_.div(id='filters')[html.spinner()]),
bootstrap.card(header_left=_.div(id='row-counts')[html.spinner()],
header_right=_.div(id='pagination')[html.spinner()],
body=_.div(id='preview')[html.spinner()]),
_.div(class_='row', id='distribution-charts')['']
]], _.script[f"""
var dataSetPage = null;
document.addEventListener('DOMContentLoaded', function() {{
dataSetPage = DataSetPage('{flask.url_for('mara_data_explorer.index_page')}',
{json.dumps(
{'data_set_id': data_set_id, 'query_id': query_id, 'query': flask.request.get_json()})},
15, '{config.charts_color()}');
}});
"""],
html.spinner_js_function(),
_.div(class_='col-xl-4 col-lg-6', id='distribution-chart-template', style='display: none')[
bootstrap.card(header_left=html.spinner(), body=_.div(class_='chart-container google-chart')[
html.spinner()])],
_.div(class_='modal fade', id='load-query-dialog', tabindex="-1")[
_.div(class_='modal-dialog', role='document')[
_.div(class_='modal-content')[
_.div(class_='modal-header')[
_.h5(class_='modal-title')['Load query'],
_.button(**{'type': "button", 'class': "close", 'data-dismiss': "modal",
'aria-label': "Close"})[
_.span(**{'aria-hidden': 'true'})['×']]],
_.div(class_='modal-body', id='query-list')['']
]
]
],
_.div(class_='modal fade', id='display-query-dialog', tabindex="-1")[
_.div(class_='modal-dialog', role='document')[
_.div(class_='modal-content')[
_.div(class_='modal-header')[
_.h5(class_='modal-title')['Query statement'],
_.button(**{'type': "button", 'class': "close", 'data-dismiss': "modal",
'aria-label': "Close"})[
_.span(**{'aria-hidden': 'true'})['×']]],
_.div(class_='modal-body', id='query-display')['']
]
]
],
_.form(action=flask.url_for('mara_data_explorer.download_csv', data_set_id=data_set_id), method='post')[
_.div(class_="modal fade", id="download-csv-dialog", tabindex="-1")[
_.div(class_="modal-dialog", role='document')[
_.div(class_="modal-content")[
_.div(class_="modal-header")[
_.h5(class_='modal-title')['Download as CSV'],
_.button(**{'type': "button", 'class': "close", 'data-dismiss': "modal",
'aria-label': "Close"})[
_.span(**{'aria-hidden': 'true'})['×']]],
_.div(class_="modal-body")[
'Delimiter:  ',
_.input(type="radio", value="\t", name="delimiter",
checked="checked"), ' tab   ',
_.input(type="radio", value=";", name="delimiter"), ' semicolon   ',
_.input(type="radio", value=",", name="delimiter"), ' comma   ',
_.hr,
'Number format:  ',
_.input(type="radio", value=".", name="decimal-mark",
checked="checked"), ' 42.7   ',
_.input(type="radio", value=",", name="decimal-mark"), ' 42,7   ',
_.input(type="hidden", name="query")],
_.div(class_="modal-footer")[
_.button(id="csv-download-button", type="submit", class_="btn btn-primary")[
'Download']]]]]],
_.form(action=flask.url_for('mara_data_explorer.oauth2_export_to_google_sheet', data_set_id=data_set_id),
method='post',
target="_blank")[
_.div(class_="modal fade", id="google-sheet-export-dialog", tabindex="-1")[
_.div(class_="modal-dialog", role='document')[
_.div(class_="modal-content")[
_.div(class_="modal-header")[
_.h5(class_='modal-title')['Google sheet export'],
_.button(**{'type': "button", 'class': "close", 'data-dismiss': "modal",
'aria-label': "Close"})[
_.span(**{'aria-hidden': 'true'})['×']]],
_.div(class_="modal-body")[
'Number format:  ',
_.input(type="radio", value=".", name="decimal-mark",
checked="checked"), ' 42.7   ',
_.input(type="radio", value=",", name="decimal-mark"), ' 42,7   ',
_.hr,
'Array format:  ',
_.input(type="radio", value="curly", name="array-format",
checked="checked"), ' {"a", "b"}   ',
_.input(type="radio", value="normal", name="array-format"), ' ["a", "b"]   ',
_.input(type="radio", value="tuple", name="array-format"), ' ("a", "b")   ',
_.hr,
'By clicking Export below:',
_.br,
_.ul[
_.li['Google authentication will be required.'],
_.li['A maximum limit of 100.000 rows will be applied.'],
_.li['A maximum limit of 50.000 characters per cell will be applied.'],
_.li['A Google sheet with the selected data will be available in a new tab.']
],
_.input(type="hidden", name="query")
],
_.div(class_="modal-footer")[
_.button(id="export-to-google-sheet", type="submit", class_="btn btn-primary")[
'Export']]]]]]
],
action_buttons=action_buttons,
js_files=['https://www.gstatic.com/charts/loader.js',
flask.url_for('mara_data_explorer.static', filename='tagsinput.js'),
flask.url_for('mara_data_explorer.static', filename='typeahead.js'),
flask.url_for('mara_data_explorer.static', filename='data-sets.js')],
css_files=[flask.url_for('mara_data_explorer.static', filename='tagsinput.css'),
flask.url_for('mara_data_explorer.static', filename='data-sets.css')])
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 data_set_page(data_set_id, query_id):
ds = find_data_set(data_set_id)
if not ds:
flask.flash(f'Data set "{data_set_id}" does not exist anymore',
category='danger')
return flask.redirect(flask.url_for('data_sets.index_page'))
action_buttons = [
response.ActionButton(action='javascript:dataSetPage.downloadCSV()',
icon='download',
label='CSV',
title='Download as CSV'),
response.ActionButton(action='javascript:dataSetPage.load()',
icon='folder-open',
label='Load',
title='Load previously saved query'),
response.ActionButton(action='javascript:dataSetPage.save()',
icon='save',
label='Save',
title='Save query')
]
if query_id:
action_buttons.insert(
1,
response.ActionButton(action=flask.url_for(
'data_sets._delete_query',
data_set_id=data_set_id,
query_id=query_id),
icon='trash',
label='Delete',
title='Delete query'))
return response.Response(
title=f'Query "{query_id}" on "{ds.name}"'
if query_id else f'New query on "{ds.name}"',
html=[
_.div(
class_='row')[_.div(
class_='col-md-3'
)[bootstrap.card(header_left='Query',
body=_.div(
id='query-details')[html.spinner()]),
bootstrap.
card(header_left='Columns',
body=[
_.div(
class_="form-group"
)[_.input(type="search",
class_="columns-search form-control",
value="",
placeholder="Filter")],
_.div(id='columns-list')[html.spinner()]
])],
_.div(class_='col-md-9')[bootstrap.card(
id='filter-card',
header_left=[
_.div(class_="dropdown")[_.a(
**{
'class': 'dropdown-toggle',
'data-toggle': 'dropdown',
'href': '#'
}
)[_.span(
class_='fa fa-plus')[' '],
' Add filter'],
_.
div(class_=
"dropdown-menu",
id=
'filter-menu'
)
[_.div(
class_
="dropdown-item"
)[_.input(
type
="text",
class_=
"columns-search form-control",
value="",
placeholder=
"Filter")]]]
],
fixed_header_height=False,
body=_.div(id='filters')[html.spinner()]),
bootstrap.
card(header_left=_.div(
id='row-counts'
)[html.spinner()],
header_right=_.div(
id='pagination'
)[html.spinner()],
body=_.div(
id='preview'
)[html.spinner()]),
_.
div(class_='row',
id=
'distribution-charts'
)['']]],
_.script[f"""
var dataSetPage = null;
document.addEventListener('DOMContentLoaded', function() {{
dataSetPage = DataSetPage('{flask.url_for('data_sets.index_page')}',
{json.dumps({'data_set_id': data_set_id, 'query_id': query_id, 'query': flask.request.get_json()})},
15, '{config.charts_color()}');
}});
"""],
html.spinner_js_function(),
_.div(class_='col-xl-4 col-lg-6',
id='distribution-chart-template',
style='display: none')[bootstrap.card(
header_left=html.spinner(),
body=_.div(class_='chart-container google-chart')[
html.spinner()])],
_.div(
class_='modal fade', id='load-query-dialog',
tabindex="-1")[_.div(
class_='modal-dialog', role='document')[_.div(
class_='modal-content')[_.div(class_='modal-header')[
_.h5(class_='modal-title')['Load query'],
_.button(
**{
'type': "button",
'class': "close",
'data-dismiss': "modal",
'aria-label': "Close"
})[_.span(
**{'aria-hidden': 'true'})['×']]],
_.div(class_='modal-body',
id='query-list')['']]]],
_.form(
action=flask.url_for('data_sets.download_csv'),
method='post')[_.div(
class_="modal fade",
id="download-csv-dialog",
tabindex="-1"
)[_.div(class_="modal-dialog", role='document')[_.div(
class_="modal-content"
)[_.div(class_="modal-header")
[_.h5(class_='modal-title')['Download as CSV'],
_.button(
**{
'type': "button",
'class': "close",
'data-dismiss': "modal",
'aria-label': "Close"
})[_.span(
**{'aria-hidden': 'true'})['×']]],
_.div(class_="modal-body")[
'Delimiter:  ',
_.input(type="radio",
value="\t",
name="delimiter",
checked="checked"),
' tab   ',
_.input(type="radio", value=";", name="delimiter"),
' semicolon   ',
_.input(type="radio", value=",", name="delimiter"),
' comma   ', _.hr, 'Number format:  ',
_.input(type="radio",
value=".",
name="decimal-mark",
checked="checked"), ' 42.7   ',
_.input(type="radio", value=",", name="decimal-mark"),
' 42,7   ',
_.input(type="hidden", name="query")],
_.div(class_="modal-footer"
)[_.button(id="csv-download-button",
type="submit",
class_="btn btn-primary")['Download']]]]]]
],
action_buttons=action_buttons,
js_files=[
'https://www.gstatic.com/charts/loader.js',
flask.url_for('data_sets.static', filename='tagsinput.js'),
flask.url_for('data_sets.static', filename='typeahead.js'),
flask.url_for('data_sets.static', filename='data-sets.js')
],
css_files=[
flask.url_for('data_sets.static', filename='tagsinput.css'),
flask.url_for('data_sets.static', filename='data-sets.css')
])