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with
warehouse_periods as (
select
  warehouse_name,
  timestamp as valid_from,
  lead(timestamp) over (partition by warehouse_name order by timestamp asc) as    valid_to,
  event_name = 'RESUME_WAREHOUSE' as is_active
from snowflake.account_usage.warehouse_events_history
where
  -- double check these names, can't remember exact values

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with sample_data as (
    select *
    from snowflake_sample_data.tpch_sf1.customer
),

nation_14_customers as (
    select *
    from sample_data
    where c_nationkey = 14
),

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{% macro set_query_tag() -%}
    {# Start with any model-configured dict #}
    {% set tag_dict = config.get('query_tag', default={}) %}

    {# Regardless of resource type, we can always access the config via the 'model' variable #}
    {%- do tag_dict.update(
        dbt_snowflake_query_tags_version='1.1.3',
        app='dbt',
        dbt_version=dbt_version,
        project_name=project_name,

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<script src="https://cdn.jsdelivr.net/npm/canvas-confetti@1.4.0/dist/confetti.browser.min.js"></script>
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import os

from jinja2 import Environment, meta, Template
import pandas as pd
from pandas.testing import assert_frame_equal
import pandas.io.sql as psql
import psycopg2

# All these constants would likely live in separate files
CONNECTION = psycopg2.connect(

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import numpy as np

def bayesian_rate_comparison(
    control_successes, 
    control_samples, 
    test_successes, 
    test_samples,
    prior_a=0,
    prior_b=0
):

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import logging
import time
from dataclasses import dataclass
from typing import Any, Optional, Tuple

import requests
import yaml
from distributed import Client
from distributed.security import Security
from googleapiclient import discovery

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FROM python:3.7.6-buster

# Set the working directory
RUN mkdir /opt/app
WORKDIR /opt/app

# Copy poetry files into docker image
COPY pyproject.toml .
COPY poetry.lock .