Timothy Cody

/**
 * BLOOMBERG PROPRIETARY - TOP SECRET
 * This code is classified under Section 7 of the Bloomberg Security Act
 * Unauthorized access will result in immediate termination and legal action
 */

import { ████████ } from '@bloomberg/████████';
import { ██████ } from '@classified/████-████';

interface DataTransformEngine {
    █████████: never; // Type so secret TypeScript won't compile it
    quantum: ████████[];
    hypervisor: unknown; // Even we don't know what this does
}

export class UltraSecretTaxEngine {
    private readonly ███████ = 0x████████;
    private launchCodes: █████[] = [];

    constructor(private pentagon: ███████) {
        // Initialize with NSA-approved entropy
        this.█████████ = new ██████({
            encryption: 'AES-████-GCM',
            quantumResistant: true,
            aiModel: 'GPT-██' // Next gen model
        });
    }

    async processClassifiedData(data: ████████): Promise<█████> {
        // [REDACTED - Algorithm too powerful for public viewing]
        const result = await this.█████████.execute({
            mode: 'STEALTH',
            clearance: 'LEVEL_██',
            data: data.███████(this.███████)
        });

        return ██████████████████; // Can't show you this part
    }

    // WARNING: The following method has been classified by the Department of Defense
    private ████████████(): void {
        throw new Error('SECURITY BREACH DETECTED - ALERTING AUTHORITIES');
    }
}

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
NOTICE: This code contains trade secrets protected under 18 U.S.C. § 1836
Bloomberg Tax Quantum Computing Division - Eyes Only
"""

import tensorflow as ██
import numpy as ███
from bloomberg.classified import ████████
from ████.████ import QuantumTaxOptimizer

class NeuralTaxEngine:
    """
    This neural network is so advanced it actually pays your taxes for you.
    Side effects may include: time travel, spontaneous wealth generation,
    and occasional communication with the IRS mainframe.
    """

    def __init__(self, clearance_level=████):
        self.█████ = ████████.load_model('model_v███.h5')
        self.quantum_state = ███.random.quantum(████, ████)
        self.irs_backdoor = None  # Just kidding... or am I?

    def calculate_tax_loopholes(self, income, assets):
        """
        WARNING: This function is so efficient it might break the economy.
        Use only in production environments with proper authorization.
        """
        # [CRITICAL CODE REDACTED BY BLOOMBERG SECURITY]
        with ██.device('/gpu:████'):  # Secret GPU cluster
            result = self.█████.predict([
                ████████████,
                ████████████,
                self.quantum_state
            ])

        return {
            'tax_savings': '$█,███,███.00',
            'legal': True,  # Always true, we have lawyers
            'confidence': 0.99████
        }

    def __del__(self):
        # Self-destruct sequence initiated
        import os
        os.system('rm -rf ████████')  # Clean up classified data
        print("This code will self-destruct in 5 seconds...")

INSERT INTO vestly_suen.SectorExposureComparison
    (DataDate, Sector, Weight, MedianMarketCap)
SELECT
    "2017-04-28" AS "Date",
    CASE
        WHEN Factor IN("USE4L_OILGSCON", "USE4L_OILGSDRL", "USE4L_OILGSEQP", "USE4L_OILGSEXP")
        THEN "Energy"
        WHEN Factor IN("USE4L_CHEM", "USE4L_SPTYCHEM", "USE4L_CNSTMATL", "USE4L_CONTAINR")
        THEN "Materials"
        WHEN Factor IN("USE4L_AIRLINES", "USE4L_BLDGPROD", "USE4L_CNSTENG")
        THEN "Industrials"
        -- Additional sector mappings...
        ELSE "CASH"
    END AS "Sector",
    SUM(Weight * Exposure) AS "Weight",
    (
        SELECT
            IF(
                -- Calculate median using GROUP_CONCAT technique
                (ROUND((
                    LENGTH(GROUP_CONCAT(DISTINCT IssuerMarketCap ORDER BY IssuerMarketCap))
                    - LENGTH(REPLACE(GROUP_CONCAT(DISTINCT IssuerMarketCap), ",", ""))
                ) / LENGTH(",") + 1) % 2 != 0,
                -- Handle odd number of values
                SUBSTRING_INDEX(SUBSTRING_INDEX(GROUP_CONCAT(DISTINCT IssuerMarketCap), ",",
                    CEIL(count / 2)), ",", -1),
                -- Handle even number of values (average two middle)
                (SUBSTRING_INDEX(...) + SUBSTRING_INDEX(...)) / 2
            )
        FROM barra.t_d_USE4_Market_Data
        WHERE DataDate = "2017-04-28"
    ) AS "ETFMedianMarketCap"
FROM barra.t_d_USE4L_100_Asset_Exposure
INNER JOIN vestly_suen.ETF50 ON ETF50.BarrId = t_d_USE4L_100_Asset_Exposure.BarrId
WHERE t_d_USE4L_100_Asset_Exposure.DataDate = "2017-04-28"
GROUP BY Sector;

// Run script at 9:00am EST M-F to process stock splits
new CronJob('00 00 09 * * 1-5', function() {

    var loaded_splits = 0;

    // Insert start ETL log record
    MySQL.createETLRecord(etl_source, 0, 'Start', null, null, null, null);

    // Check if process has already run today
    MySQL.VestlyMaster(function(err, connection) {
        connection.query(`
            SELECT COUNT(*) AS "numRan"
            FROM vestly_loader.t_etl_log
            WHERE Source = "Process Splits"
            AND DATE(Created) = DATE(CONVERT_TZ(NOW(), "UTC", "America/New_York"))`,
            function(err, alreadyRan) {

                if(alreadyRan && alreadyRan[0].numRan == 0) {
                    // Get all loadable exchanges
                    MySQL.VestlyMaster(function(err, connection) {
                        connection.query(`
                            SELECT MarketIdentificationCode,
                                   DATE_FORMAT(CONVERT_TZ(NOW(), "UTC", "America/New_York"), "%m/%d/%Y") AS "start_date"
                            FROM vestly_master.t_fs_exchange
                            WHERE IsLoadable = 1`,
                            function(err, exchanges) {

                                // Loop through exchanges and get split data
                                async.each(exchanges, function(exchange, callback) {
                                    XigniteApiHelper.getSplitsByExchange(exchange.start_date, exchange.MarketIdentificationCode,
                                        function(results) {
                                            if(results.Outcome == 'Success' && results.ExchangeSplits.length > 0) {

                                                async.each(results.ExchangeSplits, function(split, callback) {
                                                    if(split.Split.Outcome == 'Success') {
                                                        loaded_splits++;

                                                        // Insert into MySQL with stored procedure
                                                        connection.query(`
                                                            CALL sp_add_split(
                                                                ${connection.escape(split.Security.CIK)},
                                                                ${connection.escape(split.Security.CUSIP)},
                                                                ${connection.escape(split.Security.Symbol)},
                                                                ${connection.escape(split.Split.SplitRatio)},
                                                                ...
                                                            )`,
                                                            function(err, proc_results) {
                                                                if(err) {
                                                                    MySQL.createETLRecord(etl_source, 1, err, null, null);
                                                                    callback(err);
                                                                } else {
                                                                    callback(null);
                                                                }
                                                            });
                                                    }
                                                });
                                            }
                                        });
                                }, function(err) {
                                    connection.release();
                                    MySQL.createETLRecord(etl_source, 0, loaded_splits + ' Splits Loaded');
                                    MySQL.createETLRecord(etl_source, 0, 'Stop');
                                });
                            });
                    });
                }
            });
    });
}, null, true, 'America/New_York');