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": [

luisdelatorre012

import motor.motor_asyncio
import asyncio
from typing import List, Dict, Any
import logging
from urllib.parse import quote_plus
from contextlib import asynccontextmanager

# Set up logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

luisdelatorre012

import subprocess
from dynaconf import Dynaconf
from typing import Dict
from sqlalchemy import create_engine
from sqlalchemy.engine import Engine
import pandas as pd

# Assume get_keeper_secrets_by_title and query_to_pandas are defined elsewhere
# from your_module import get_keeper_secrets_by_title, query_to_pandas

luisdelatorre012

Prompt:

undefined

Response:

undefined

Prompt:

Use python for this. Whatever packags you wwant.

I have a graph. Each node has location label, and all nodes have edges between them.

luisdelatorre012

import httpx
from msal import ConfidentialClientApplication
from typing import Optional, List, Dict, Any
from dynaconf import Dynaconf

# Initialize Dynaconf
settings = Dynaconf(
    settings_files=["settings.toml", ".secrets.toml"],
    environments=True,
    load_dotenv=True,

luisdelatorre012

import json
import signal
import asyncio
from confluent_kafka import Consumer, KafkaError, Message
from fastavro import reader
import io
from sqlalchemy.ext.asyncio import create_async_engine, AsyncEngine
from sqlalchemy import Table, Column, Integer, TIMESTAMP, MetaData
from sqlalchemy.dialects.postgresql import JSONB
from sqlalchemy.exc import SQLAlchemyError