Stiivi

from flask import Flask, render_template, request
import cubes
import json

app = Flask(__name__)

#
# Data we aregoing to browse and logical model of the data
#
MODEL_PATH = "model.json"

Stiivi

from flask import Flask, render_template, request
import cubes

app = Flask(__name__)

#
# Data we aregoing to browse and logical model of the data
#
MODEL_PATH = "model.json"
DB_URL = "sqlite:///data.sqlite"

Stiivi

# Run this script in cubes/examples/hello_world

import cubes

model = cubes.load_model("model.json")
workspace = cubes.create_workspace("sql", model,
                                   url='sqlite:///data.sqlite')

cube = model.cube("irbd_balance")

Stiivi

import brewery

stream = brewery.Stream()

main = stream.fork()
main.csv_source("examples/data2.csv")
main.field_filter(drop=["category_code", "subcategory_code", "line_item"])
main.pretty_printer()

stream.run()

Stiivi

import sqlalchemy
import carray
from sqlalchemy.types import *

BUFFER_SIZE = 100

dtype_map = [
	(BigInteger, "i"),
	(SmallInteger, "i"),
	(Boolean, "i"),

Stiivi

[
	{ "keys": ["ctrl+q"], "command": "wrap_lines" },
	{ "keys": ["super+shift+v"], "command": "paste" },
	{ "keys": ["super+v"], "command": "paste_and_indent" }
]

Stiivi

{
    "cubes": [
        {
            "name": "example",
            "measures": ["amount"],
            "dimensions": ["date"],
            "mappings": {
              "date.year": {"column":"date", "extract":"year"},
              "date.month": {"column":"date", "extract":"month"},
              "date.day": {"column":"date", "extract":"day"}

Stiivi

import sqlalchemy
import cubes
import cubes.tutorial.sql as tutorial

DATA = "../examples/hello_world/data.csv"
MODEL = "../examples/hello_world/model.json"

engine = sqlalchemy.create_engine('sqlite:///:memory:')
tutorial.create_table_from_csv(engine, 
                      DATA, 

Stiivi

[server]
debug=yes
log_level=debug
reload=yes
backend = sql.star
prettyprint = true

[workspace]
url = postgres://postgres@localhost/openspending

Stiivi

from sqlalchemy import create_engine, MetaData, Table
import json

OS_DATASET = "de-bund"

def get_os_metadata(dataset_name):
    engine = create_engine("postgres://postgres@localhost/openspending")
    md = MetaData(bind=engine)

    table = Table("dataset", md, autoload=True)