def create_app(**config):
app = Flask(__name__, static_folder='../spendb.ui')
app.config.from_object(default_settings)
app.config.from_envvar('SPENDB_SETTINGS', silent=True)
app.config.update(config)
app.jinja_options['extensions'].extend([
formencode_jinja2.formfill,
'jinja2.ext.i18n'
])
db.init_app(app)
babel.init_app(app)
cache.init_app(app)
mail.init_app(app)
assets.init_app(app)
login_manager.init_app(app)
data_manager.init_app(app)
pages.init_app(app)
migrate.init_app(app, db, directory=app.config.get('ALEMBIC_DIR'))
cors.init_app(app, resources=r'/api/*', supports_credentials=True,
methods=['GET', 'HEAD', 'OPTIONS'])
ws = Workspace()
ext.model_provider("spending", metadata={})
ext.store("spending")
ws.register_default_store('spending', model_provider='spending')
app.cubes_workspace = ws
return app
def create_browser():
#workspace = Workspace(config="slicer.ini")
print("Creating Workspace and model")
workspace = Workspace()
workspace.register_default_store("sql", url="sqlite:///data.sqlite")
workspace.import_model("movie_ratings_model.json")
browser = workspace.browser("ratings")
return browser
def __init__(self):
print("Creating Workspace and model")
workspace = Workspace()
workspace.register_default_store("sql", url="sqlite:///data.sqlite")
workspace.import_model("movie_ratings_model.json")
browser = workspace.browser("ratings")
self.browser = browser
def setUp(self):
super(SlicerModelTestCase, self).setUp()
ws = Workspace()
ws.register_default_store("sql", url=TEST_DB_URL)
self.ws = ws
self.slicer.cubes_workspace = ws
# Satisfy browser with empty tables
# TODO: replace this once we have data
store = ws.get_store("default")
table = Table("sales", store.metadata)
table.append_column(Column("id", Integer))
table.create()
ws.import_model(self.model_path("model.json"))
ws.import_model(self.model_path("sales_no_date.json"))
def setUp(self):
super(SlicerModelTestCase, self).setUp()
ws = Workspace()
ws.register_default_store("sql", url=TEST_DB_URL)
self.ws = ws
self.slicer.cubes_workspace = ws
# Satisfy browser with empty tables
# TODO: replace this once we have data
store = ws.get_store("default")
table = Table("sales", store.metadata)
table.append_column(Column("id", Integer))
table.create()
ws.import_model(self.model_path("model.json"))
ws.import_model(self.model_path("sales_no_date.json"))
def create_workspace(self, store=None, model=None):
"""Create shared workspace. Add default store specified in `store` as
a dictionary and `model` which can be a filename relative to
``tests/models`` or a moel dictionary. If no store is provided but
class has an engine or `sql_engine` set, then the existing engine will
be used as the default SQL store."""
workspace = Workspace()
if store:
store = dict(store)
store_type = store.pop("type", "sql")
workspace.register_default_store(store_type, **store)
elif self.engine:
workspace.register_default_store("sql", engine=self.engine)
if model:
if isinstance(model, compat.string_type):
model = self.model_path(model)
workspace.import_model(model)
return workspace
from cubes import Workspace, Cell, PointCut
# 1. Create a workspace
workspace = Workspace()
workspace.register_default_store("sql", url="sqlite:///data.sqlite")
workspace.add_model("model.json")
# 2. Get a browser
browser = workspace.browser("irbd_balance")
# 3. Play with aggregates
result = browser.aggregate()
print "Total\n" \
"----------------------"
print "Record count: %8d" % result.summary["record_count"]
print "Total amount: %8d" % result.summary["amount_sum"]
#
# 4. Drill-down through a dimension
#
print "\n" \
"Drill Down by Category (top-level Item hierarchy)\n" \
"================================================="
#
result = browser.aggregate(drilldown=["item"])
#
print ("%-20s%10s%10s\n"+"-"*40) % ("Category", "Count", "Total")
#
import os.path
BASE = os.path.dirname(os.path.abspath(__file__))
from cubes import Workspace, Cell, PointCut
from datetime import datetime, timedelta
import sys
import json
from django.http import JsonResponse
#-------------------------------------------------------------#
workspace = Workspace()
workspace.register_default_store("sql", url="sqlite:///"+os.path.join(BASE,"myData.sqlite"))
workspace.import_model(os.path.join(BASE,"modal.json"))
browser = workspace.browser("FB_POSTS_DATA")
#-------------------------------------------------------------#
d = datetime.now() - timedelta(days=1)
cut = PointCut("pub_date", [d.year, d.month, d.day-6], None)
cell = Cell(browser.cube, cuts = [cut])
#-------------------------------------------------------------#
def get_post_by_shares():
result = browser.aggregate(cell, drilldown=["name"])
shares = []
from cubes import StaticModelProvider
from cubes import Workspace
workspace = Workspace()
workspace.register_default_store("sql", url="sqlite:///BI.db")
dicc = {
"cubes": [{
"name": "clase",
"label": "Clases",
"dimensions": ["franja", "seccion", "salon", "curso"]
}],
"dimensions": [{
"name":
"franja",
"label":
"Franja",
"attributes": [{
"name": "dia",
"label": "Dia"
}, {
"name": "hora_inicio",
"label": "Hora de inicio",
}, {
"name": "minuto_inicio",
"label": "Minuto de inicio",
}, {
"name": "hora_fin",
"label": "Hora de finalizacion",
}, {
"name": "minuto_fin",
"label": "Minuto de finalizacion",
# table_name="ibrd_balance",
# fields=[
# ("category", "string"),
# ("category_label", "string"),
# ("subcategory", "string"),
# ("subcategory_label", "string"),
# ("line_item", "string"),
# ("year", "integer"),
# ("amount", "integer")],
# create_id=True
# )
from cubes import Workspace, PointCut, Cell
workspace = Workspace()
workspace.register_default_store(
"sql", url="postgresql://*****:*****@localhost/willowood")
workspace.import_model("SalesTable.json")
browser = workspace.browser("salestable")
result = browser.aggregate()
print(result.summary["record_count"])
print(result.summary["Qty"])
print(result.summary["Value"])
cube = browser.cube
# result = browser.aggregate(drilldown=["billing_date"])
#
# for record in result:
# print(' record: ', record)
from __future__ import print_function
from cubes import Workspace, Cell, PointCut
workspace = Workspace()
workspace.register_default_store("sql", url="sqlite:///data_sqlite/f1.sqlite")
workspace.import_model("models/model.json")
browser = workspace.browser("qualifying")
cut1 = PointCut("drivers", [])
cut2 = PointCut("races", [])
cell = Cell(browser.cube, cuts=[cut1, cut2])
result = browser.aggregate(cell, drilldown=["drivers", "races"])
list_res = [row for row in result]
def filter_racer(data, name, year):
temp = list(
filter(
lambda x: x['drivers.surname'] == name and x['races.year'] == year,
data))
return sorted(temp, key=lambda x: x['position_min'])
for line in filter_racer(list_res, 'Hamilton', 2009):
print(line)
from cubes import Workspace, Cell
# 1. Create a workspace
workspace = Workspace()
workspace.register_default_store("sql",
url="sqlite:///vvo_data.sqlite",
dimension_prefix="dm_",
fact_prefix="ft_")
workspace.import_model("procurements.cubesmodel")
# 2. Get a browser
browser = workspace.browser("contracts")
cube = browser.cube
# workspace = cubes.create_workspace("sql", model, url="postgres://localhost/ep2012",
# schema="vvo",
# dimension_prefix="dm_",
# fact_prefix="ft_",
# denormalized_view_schema="views",
# use_denormalization=False,
# denormalized_view_prefix="mft_")
def drilldown(cell, dimension):
"""Drill-down and aggregate recursively through als levels of `dimension`.
This function is like recursively traversing directories on a file system
and aggregating the file sizes, for example.
* `cell` - cube cell to drill-down
* `dimension` - dimension to be traversed through all levels
"""
