- Popup Mode
- Conditional formatting
- Number Formatting (for tooltip)
- Measure based on category, only Numeric Filter
- Saved Filters
- Alphanumeric filter*
- Filter Context support
- Single select for month / Day
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| ┌────────────────────────────────────┐ | |
| │ Teams Email Bridge [?] [Settings]│ | |
| ├─────────────────────────────────────┤ | |
| │ 📧 Quick Compose │ | |
| │ 📋 Templates │ | |
| │ 👥 Recent Contacts │ | |
| │ 📝 Sent History │ | |
| └─────────────────────────────────────┘ |
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| mkdir -p chapter1/1.{1,2,3,4,5,6} |
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| { | |
| "type": "module", | |
| "dependencies": { | |
| "@coinpaprika/api-nodejs-client": "^2.0.0", | |
| "@modelcontextprotocol/sdk": "^1.7.0", | |
| "ws": "^8.18.1", | |
| "zod": "^3.24.2" | |
| } | |
| } |
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| <!DOCTYPE html> | |
| <html lang="en"> | |
| <head> | |
| <meta charset="UTF-8" /> | |
| <meta name="viewport" content="width=device-width, initial-scale=1.0" /> | |
| <title>LinkedIn Resume Builder</title> | |
| <link | |
| href="https://fonts.googleapis.com/css2?family=Open+Sans:wght@300;400;600;700&family=Poppins:wght@400;500;600&display=swap" | |
| rel="stylesheet" | |
| /> |
nsdevaraj
/ decision_types.py
Last active
March 18, 2025 11:30
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| """ | |
| Business Simulation Decision Types | |
| ================================= | |
| This module defines the various decision types available in the business simulation | |
| and their specific parameters and effects. | |
| """ | |
| from typing import Dict, Any, List, Optional | |
| from enum import Enum |
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| { | |
| "privileges": [ | |
| { | |
| "name": "ExportContent", | |
| "essential": true | |
| }, | |
| { | |
| "name": "LocalStorage", | |
| "essential": true | |
| }, |
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| // Example with nested conditionals (harder to read) | |
| function processUserRegistration(user) { | |
| if (user.hasValidEmail) { | |
| if (user.isMinimumAge) { | |
| if (user.hasAcceptedTerms) { | |
| if (user.hasProvidedValidPassword) { | |
| // Perform registration | |
| return { | |
| success: true, | |
| userId: generateUserId(), |
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| input | |
| 1 - 2 | |
| 1 - 3 | |
| 2 - 3 | |
| 2 - 4 | |
| 3 - 1 | |
| 3 - 2 | |
| 4 - 1 | |
| 4 - 2 |
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| import sqlite3 | |
| import torch | |
| from transformers import AutoTokenizer, AutoModel | |
| from tqdm import tqdm | |
| import gc | |
| #python3 -m venv path/to/venv | |
| #source path/to/venv/bin/activate | |
| # Connect to the SQLite database | |
| conn = sqlite3.connect('data.sqlite') |
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