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superset2/superset/data/birth_names.py
Maxime Beauchemin 7b3095d6ff Fix examples charts/dashboards and refactor (#5881) 
* Fix examples charts/dashboards and refactor

* pylinting

* Fix pylint

* Lint the refactor

* Rebased
2018-10-31 15:29:04 -07:00

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import gzip
import json
import os
import textwrap
import pandas as pd
from sqlalchemy import DateTime, String
from superset import db
from superset.connectors.sqla.models import TableColumn
from superset.utils.core import get_or_create_main_db
from .helpers import (
config,
Dash,
DATA_FOLDER,
get_slice_json,
merge_slice,
Slice,
TBL,
update_slice_ids,
)
def load_birth_names():
"""Loading birth name dataset from a zip file in the repo"""
with gzip.open(os.path.join(DATA_FOLDER, 'birth_names.json.gz')) as f:
pdf = pd.read_json(f)
pdf.ds = pd.to_datetime(pdf.ds, unit='ms')
pdf.to_sql(
'birth_names',
db.engine,
if_exists='replace',
chunksize=500,
dtype={
'ds': DateTime,
'gender': String(16),
'state': String(10),
'name': String(255),
},
index=False)
print('Done loading table!')
print('-' * 80)
print('Creating table [birth_names] reference')
obj = db.session.query(TBL).filter_by(table_name='birth_names').first()
if not obj:
obj = TBL(table_name='birth_names')
obj.main_dttm_col = 'ds'
obj.database = get_or_create_main_db()
obj.filter_select_enabled = True
if not any(col.column_name == 'num_california' for col in obj.columns):
obj.columns.append(TableColumn(
column_name='num_california',
expression="CASE WHEN state = 'CA' THEN num ELSE 0 END",
))
db.session.merge(obj)
db.session.commit()
obj.fetch_metadata()
tbl = obj
defaults = {
'compare_lag': '10',
'compare_suffix': 'o10Y',
'limit': '25',
'granularity_sqla': 'ds',
'groupby': [],
'metric': 'sum__num',
'metrics': ['sum__num'],
'row_limit': config.get('ROW_LIMIT'),
'since': '100 years ago',
'until': 'now',
'viz_type': 'table',
'where': '',
'markup_type': 'markdown',
}
print('Creating some slices')
slices = [
Slice(
slice_name='Girls',
viz_type='table',
datasource_type='table',
datasource_id=tbl.id,
params=get_slice_json(
defaults,
groupby=['name'],
filters=[{
'col': 'gender',
'op': 'in',
'val': ['girl'],
}],
row_limit=50,
timeseries_limit_metric='sum__num')),
Slice(
slice_name='Boys',
viz_type='table',
datasource_type='table',
datasource_id=tbl.id,
params=get_slice_json(
defaults,
groupby=['name'],
filters=[{
'col': 'gender',
'op': 'in',
'val': ['boy'],
}],
row_limit=50)),
Slice(
slice_name='Participants',
viz_type='big_number',
datasource_type='table',
datasource_id=tbl.id,
params=get_slice_json(
defaults,
viz_type='big_number', granularity_sqla='ds',
compare_lag='5', compare_suffix='over 5Y')),
Slice(
slice_name='Genders',
viz_type='pie',
datasource_type='table',
datasource_id=tbl.id,
params=get_slice_json(
defaults,
viz_type='pie', groupby=['gender'])),
Slice(
slice_name='Genders by State',
viz_type='dist_bar',
datasource_type='table',
datasource_id=tbl.id,
params=get_slice_json(
defaults,
adhoc_filters=[
{
'clause': 'WHERE',
'expressionType': 'SIMPLE',
'filterOptionName': '2745eae5',
'comparator': ['other'],
'operator': 'not in',
'subject': 'state',
},
],
viz_type='dist_bar',
metrics=[
{
'expressionType': 'SIMPLE',
'column': {
'column_name': 'sum_boys',
'type': 'BIGINT(20)',
},
'aggregate': 'SUM',
'label': 'Boys',
'optionName': 'metric_11',
},
{
'expressionType': 'SIMPLE',
'column': {
'column_name': 'sum_girls',
'type': 'BIGINT(20)',
},
'aggregate': 'SUM',
'label': 'Girls',
'optionName': 'metric_12',
},
],
groupby=['state'])),
Slice(
slice_name='Trends',
viz_type='line',
datasource_type='table',
datasource_id=tbl.id,
params=get_slice_json(
defaults,
viz_type='line', groupby=['name'],
granularity_sqla='ds', rich_tooltip=True, show_legend=True)),
Slice(
slice_name='Average and Sum Trends',
viz_type='dual_line',
datasource_type='table',
datasource_id=tbl.id,
params=get_slice_json(
defaults,
viz_type='dual_line',
metric={
'expressionType': 'SIMPLE',
'column': {
'column_name': 'num',
'type': 'BIGINT(20)',
},
'aggregate': 'AVG',
'label': 'AVG(num)',
'optionName': 'metric_vgops097wej_g8uff99zhk7',
},
metric_2='sum__num',
granularity_sqla='ds')),
Slice(
slice_name='Title',
viz_type='markup',
datasource_type='table',
datasource_id=tbl.id,
params=get_slice_json(
defaults,
viz_type='markup', markup_type='html',
code="""\
<div style='text-align:center'>
<h1>Birth Names Dashboard</h1>
<p>
The source dataset came from
<a href='https://github.com/hadley/babynames' target='_blank'>[here]</a>
</p>
<img src='/static/assets/images/babytux.jpg'>
</div>
""")),
Slice(
slice_name='Name Cloud',
viz_type='word_cloud',
datasource_type='table',
datasource_id=tbl.id,
params=get_slice_json(
defaults,
viz_type='word_cloud', size_from='10',
series='name', size_to='70', rotation='square',
limit='100')),
Slice(
slice_name='Pivot Table',
viz_type='pivot_table',
datasource_type='table',
datasource_id=tbl.id,
params=get_slice_json(
defaults,
viz_type='pivot_table', metrics=['sum__num'],
groupby=['name'], columns=['state'])),
Slice(
slice_name='Number of Girls',
viz_type='big_number_total',
datasource_type='table',
datasource_id=tbl.id,
params=get_slice_json(
defaults,
viz_type='big_number_total', granularity_sqla='ds',
filters=[{
'col': 'gender',
'op': 'in',
'val': ['girl'],
}],
subheader='total female participants')),
Slice(
slice_name='Number of California Births',
viz_type='big_number_total',
datasource_type='table',
datasource_id=tbl.id,
params=get_slice_json(
defaults,
metric={
'expressionType': 'SIMPLE',
'column': {
'column_name': 'num_california',
'expression': "CASE WHEN state = 'CA' THEN num ELSE 0 END",
},
'aggregate': 'SUM',
'label': 'SUM(num_california)',
},
viz_type='big_number_total',
granularity_sqla='ds')),
Slice(
slice_name='Top 10 California Names Timeseries',
viz_type='line',
datasource_type='table',
datasource_id=tbl.id,
params=get_slice_json(
defaults,
metrics=[{
'expressionType': 'SIMPLE',
'column': {
'column_name': 'num_california',
'expression': "CASE WHEN state = 'CA' THEN num ELSE 0 END",
},
'aggregate': 'SUM',
'label': 'SUM(num_california)',
}],
viz_type='line',
granularity_sqla='ds',
groupby=['name'],
timeseries_limit_metric={
'expressionType': 'SIMPLE',
'column': {
'column_name': 'num_california',
'expression': "CASE WHEN state = 'CA' THEN num ELSE 0 END",
},
'aggregate': 'SUM',
'label': 'SUM(num_california)',
},
limit='10')),
Slice(
slice_name='Names Sorted by Num in California',
viz_type='table',
datasource_type='table',
datasource_id=tbl.id,
params=get_slice_json(
defaults,
groupby=['name'],
row_limit=50,
timeseries_limit_metric={
'expressionType': 'SIMPLE',
'column': {
'column_name': 'num_california',
'expression': "CASE WHEN state = 'CA' THEN num ELSE 0 END",
},
'aggregate': 'SUM',
'label': 'SUM(num_california)',
})),
Slice(
slice_name='Num Births Trend',
viz_type='line',
datasource_type='table',
datasource_id=tbl.id,
params=get_slice_json(
defaults,
viz_type='line')),
]
for slc in slices:
merge_slice(slc)
print('Creating a dashboard')
dash = db.session.query(Dash).filter_by(dashboard_title='Births').first()
if not dash:
dash = Dash()
js = textwrap.dedent("""\
{
"CHART-0dd270f0": {
"meta": {
"chartId": 51,
"width": 2,
"height": 50
},
"type": "CHART",
"id": "CHART-0dd270f0",
"children": []
},
"CHART-a3c21bcc": {
"meta": {
"chartId": 52,
"width": 2,
"height": 50
},
"type": "CHART",
"id": "CHART-a3c21bcc",
"children": []
},
"CHART-976960a5": {
"meta": {
"chartId": 53,
"width": 2,
"height": 25
},
"type": "CHART",
"id": "CHART-976960a5",
"children": []
},
"CHART-58575537": {
"meta": {
"chartId": 54,
"width": 2,
"height": 25
},
"type": "CHART",
"id": "CHART-58575537",
"children": []
},
"CHART-e9cd8f0b": {
"meta": {
"chartId": 55,
"width": 8,
"height": 38
},
"type": "CHART",
"id": "CHART-e9cd8f0b",
"children": []
},
"CHART-e440d205": {
"meta": {
"chartId": 56,
"width": 8,
"height": 50
},
"type": "CHART",
"id": "CHART-e440d205",
"children": []
},
"CHART-59444e0b": {
"meta": {
"chartId": 57,
"width": 3,
"height": 38
},
"type": "CHART",
"id": "CHART-59444e0b",
"children": []
},
"CHART-e2cb4997": {
"meta": {
"chartId": 59,
"width": 4,
"height": 50
},
"type": "CHART",
"id": "CHART-e2cb4997",
"children": []
},
"CHART-e8774b49": {
"meta": {
"chartId": 60,
"width": 12,
"height": 50
},
"type": "CHART",
"id": "CHART-e8774b49",
"children": []
},
"CHART-985bfd1e": {
"meta": {
"chartId": 61,
"width": 4,
"height": 50
},
"type": "CHART",
"id": "CHART-985bfd1e",
"children": []
},
"CHART-17f13246": {
"meta": {
"chartId": 62,
"width": 4,
"height": 50
},
"type": "CHART",
"id": "CHART-17f13246",
"children": []
},
"CHART-729324f6": {
"meta": {
"chartId": 63,
"width": 4,
"height": 50
},
"type": "CHART",
"id": "CHART-729324f6",
"children": []
},
"COLUMN-25a865d6": {
"meta": {
"width": 4,
"background": "BACKGROUND_TRANSPARENT"
},
"type": "COLUMN",
"id": "COLUMN-25a865d6",
"children": [
"ROW-cc97c6ac",
"CHART-e2cb4997"
]
},
"COLUMN-4557b6ba": {
"meta": {
"width": 8,
"background": "BACKGROUND_TRANSPARENT"
},
"type": "COLUMN",
"id": "COLUMN-4557b6ba",
"children": [
"ROW-d2e78e59",
"CHART-e9cd8f0b"
]
},
"GRID_ID": {
"type": "GRID",
"id": "GRID_ID",
"children": [
"ROW-8515ace3",
"ROW-1890385f",
"ROW-f0b64094",
"ROW-be9526b8"
]
},
"HEADER_ID": {
"meta": {
"text": "Births"
},
"type": "HEADER",
"id": "HEADER_ID"
},
"MARKDOWN-00178c27": {
"meta": {
"width": 5,
"code": "<div style=\\"text-align:center\\">\\n <h1>Birth Names Dashboard</h1>\\n <p>\\n The source dataset came from\\n <a href=\\"https://github.com/hadley/babynames\\" target=\\"_blank\\">[here]</a>\\n </p>\\n <img src=\\"/static/assets/images/babytux.jpg\\">\\n</div>\\n",
"height": 38
},
"type": "MARKDOWN",
"id": "MARKDOWN-00178c27",
"children": []
},
"ROOT_ID": {
"type": "ROOT",
"id": "ROOT_ID",
"children": [
"GRID_ID"
]
},
"ROW-1890385f": {
"meta": {
"background": "BACKGROUND_TRANSPARENT"
},
"type": "ROW",
"id": "ROW-1890385f",
"children": [
"CHART-e440d205",
"CHART-0dd270f0",
"CHART-a3c21bcc"
]
},
"ROW-8515ace3": {
"meta": {
"background": "BACKGROUND_TRANSPARENT"
},
"type": "ROW",
"id": "ROW-8515ace3",
"children": [
"COLUMN-25a865d6",
"COLUMN-4557b6ba"
]
},
"ROW-be9526b8": {
"meta": {
"background": "BACKGROUND_TRANSPARENT"
},
"type": "ROW",
"id": "ROW-be9526b8",
"children": [
"CHART-985bfd1e",
"CHART-17f13246",
"CHART-729324f6"
]
},
"ROW-cc97c6ac": {
"meta": {
"background": "BACKGROUND_TRANSPARENT"
},
"type": "ROW",
"id": "ROW-cc97c6ac",
"children": [
"CHART-976960a5",
"CHART-58575537"
]
},
"ROW-d2e78e59": {
"meta": {
"background": "BACKGROUND_TRANSPARENT"
},
"type": "ROW",
"id": "ROW-d2e78e59",
"children": [
"MARKDOWN-00178c27",
"CHART-59444e0b"
]
},
"ROW-f0b64094": {
"meta": {
"background": "BACKGROUND_TRANSPARENT"
},
"type": "ROW",
"id": "ROW-f0b64094",
"children": [
"CHART-e8774b49"
]
},
"DASHBOARD_VERSION_KEY": "v2"
}
""")
pos = json.loads(js)
# dashboard v2 doesn't allow add markup slice
dash.slices = [slc for slc in slices if slc.viz_type != 'markup']
update_slice_ids(pos, dash.slices)
dash.dashboard_title = 'Births'
dash.position_json = json.dumps(pos, indent=4)
dash.slug = 'births'
db.session.merge(dash)
db.session.commit()
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