GarrettMooney

Schemas in QA but not in Prod

WITH qa AS (
    SELECT TABLE_CATALOG, TABLE_SCHEMA, TABLE_NAME
    FROM qa_edw_pstg.information_schema.tables
),
prod AS (
    SELECT TABLE_CATALOG, TABLE_SCHEMA, TABLE_NAME
    FROM prd_edw_pstg.information_schema.tables

GarrettMooney

import uuid

import streamlit as st

#########
# Helpers
#########


def get_completion(question, session_id):

GarrettMooney

# /// script
# requires-python = ">=3.12"
# dependencies = [
#     "boto3",
#     "sagemaker",
# ]
# ///
import subprocess
import time
from time import gmtime, strftime

GarrettMooney

# /// script
# requires-python = ">=3.12"
# dependencies = [
#     "duckdb",
#     "polars",
#     "pyarrow",
#     "pyathena",
#     "s3fs",
# ]
# ///

GarrettMooney

"""View remote jobs in a 3 day interval."""

BASE_URL = "https://www.linkedin.com/jobs/search/"

def get_linkedin_jobs(search, n_days=3, remote=True):
    # time
    seconds_in_day = 86400
    n_seconds = n_days * seconds_in_day
    query = BASE_URL + "?f_TPR=r" + str(n_seconds)

GarrettMooney

from typing import Union

import numpy as np
import pandas as pd

def create_sample_weights(
    y_train: np.ndarray, 
    X_train: Union[np.ndarray, pd.DataFrame]
) -> pd.Series:
    y_series = pd.DataFrame({"y": y_train})["y"]

GarrettMooney

from numpy import log, exp
from scipy.special import betaln as logbeta


def probability_B_beats_A(α_A, β_A, α_B, β_B):
    total = 0.0
    for i in range(α_B):
        total += exp(
            logbeta(α_A + i, β_B + β_A)
            - log(β_B + i)

GarrettMooney

%pip install "whatlies[sentence_tfm]"  # quotes for my fellow zsh users

import numpy as np
from whatlies.language import SentenceTFMLanguage
from sklearn.pipeline import Pipeline
from sklearn.linear_model import LogisticRegression

pipe = Pipeline([
 ("embed", SentenceTFMLanguage('distilbert-base-nli-stsb-mean-tokens')),

GarrettMooney

# venv
# usage:
#   $ venv .recsys
function venv {
    default_envdir=".env"
    envdir=${1:-$default_envdir}

    if [ ! -d $envdir ]; then
        python3.7 -m virtualenv -p python3.7 $envdir
        echo -e "\x1b[38;5;2m✔ Created virtualenv $envdir\x1b[0m"

GarrettMooney

#!/bin/bash
flag=$1
if [[ $flag == 'DL' ]]; then
	# -------------
	# Deep Learning
	# -------------
	echo "Configuring GPU for Deep Learning..."
	sudo apt-get install -y libnvidia-common-440
	sudo apt-get install -y cuda
	sudo apt-get install -y cuda-drivers