luisdelatorre012

def prorate_proportionally(df: pd.DataFrame, group: pd.DataFrame):
    # Get the total tonnage values from the first row
    total_tonnage_moved_contract = group.iloc[0]["tonnage_moved_contract"]
    total_tonnage_moved_spot = group.iloc[0]["tonnage_moved_spot"]
    total_tonnage_moved_unknown = group.iloc[0]["tonnage_moved_unknown"]

    # Calculate the total commitment
    total_commitment = group["tonnage_committed"].sum()

    # Compute proration factors for each row

luisdelatorre012

import msal
import httpx
from dynaconf import Dynaconf

# Load configuration
config = Dynaconf(
    settings_files=['settings.toml', '.secrets.toml'],
    environments=True,
    load_dotenv=True,
)

luisdelatorre012

import json
import pyodbc
import re
from datetime import date, datetime
from typing import Any, Dict, Optional, List

def load_json(file_path: str) -> Any:
    with open(file_path, 'r') as file:
        return json.load(file)

luisdelatorre012

import subprocess
import json

def run_powershell_command(command):
    completed_process = subprocess.run(
        ["powershell", "-Command", command],
        capture_output=True,
        text=True
    )
    if completed_process.returncode != 0:

luisdelatorre012

import json
import logging
import os
from typing import Any, Dict, Optional, Type, List, Tuple

import jsonref  # Library for resolving JSON schema references
from jsonschema import Draft7Validator
from sqlalchemy import (
    JSON,
    Boolean,

luisdelatorre012

import json
import uuid
from sqlalchemy import create_engine, Column, Integer, String, Float, Boolean, DateTime, ForeignKey
from sqlalchemy.orm import declarative_base, sessionmaker, relationship
from sqlalchemy.dialects.mssql import UNIQUEIDENTIFIER
from datetime import datetime

Base = declarative_base()

class Product(Base):

luisdelatorre012

import json
import re

def convert_json_schema_to_sql(schema: dict[str, any]) -> list[str]:
    tables = []
    foreign_keys = []
    indexes = []
    definitions = schema.get('definitions', {})
    
    # Handle top-level properties

luisdelatorre012

import json
from pathlib import Path
from genson import SchemaBuilder

def generate_schema_from_files(directory):
    builder = SchemaBuilder()
    directory_path = Path(directory)
    
    for file_path in directory_path.glob('*.json'):
        with file_path.open('r') as f:

luisdelatorre012

SELECT 
    t.Category,
    MIN(j.eventRecordedTime) AS MinEventTime,
    MAX(j.eventRecordedTime) AS MaxEventTime,
    AVG(j.someNumericValue) AS AvgValue
FROM 
    t
    CROSS APPLY OPENJSON(CAST(CAST(t.message AS varchar(max)) AS nvarchar(max)))
    WITH (
        eventRecordedTime datetime2 '$.eventRecordedTime',

luisdelatorre012

#Use explicit comparison in aggregation:
#Let's try using the aggregation framework with explicit type checking:

rom bson import Int64

pipeline = [
    {
        "$match": {
            "$expr": {
                "$and": [