Module 2: Build Sprint 1

Understanding Your First Ticket

Learn how to approach your first ticket in the Labs project and understand the development workflow.

Approaching Your First Feature

Learn how to implement database operations and data generation for your first Data Science Labs ticket.

# Example Database Interface Implementation

from os import getenv
from typing import Dict, Optional
import pandas as pd
from pymongo import MongoClient
from dotenv import load_dotenv
from certifi import where
from monster_lab import generate_monster  # Hypothetical monster generation library

class MonsterDatabase:
    """Interface for monster database operations."""
    
    def __init__(self):
        """Initialize database connection using environment variables."""
        load_dotenv()
        self.client = MongoClient(getenv("DB_URL"), tlsCAFile=where())
        self.db = self.client["monster_database"]
        self.collection = self.db["monsters"]
    
    def seed(self, num_monsters: int) -> bool:
        """Seed the database with specified number of monsters."""
        try:
            monsters = [generate_monster() for _ in range(num_monsters)]
            self.collection.insert_many(monsters)
            return True
        except Exception as e:
            print(f"Error seeding database: {e}")
            return False
    
    def reset(self) -> bool:
        """Delete all monsters from the collection."""
        try:
            self.collection.delete_many({})
            return True
        except Exception as e:
            print(f"Error resetting database: {e}")
            return False
    
    def count(self) -> int:
        """Return the number of monsters in the collection."""
        return self.collection.count_documents({})
    
    def dataframe(self) -> Optional[pd.DataFrame]:
        """Return a DataFrame of all monsters in the collection."""
        data = list(self.collection.find({}, {'_id': 0}))
        return pd.DataFrame(data) if data else None
    
    def html_table(self) -> Optional[str]:
        """Return HTML table representation of monster data."""
        df = self.dataframe()
        return df.to_html() if df is not None else None

Submit your Sprint 1 Deliverables: Loom and Code

Technical Interview Simulation

You're in the middle of your first technical interview. The interviewer is going through your resume and stops at the section describing your Labs project. They turn to you and ask:

“How would you describe the project you built in BloomTech Labs and the contributions you had on it?”

Using Loom, record a video articulating to a hiring manager the product you'll be working on in Labs. Feel free to reference your code and ticket.

You should concisely answer the following questions:

• What were the deliverables for your ticket?
• What requirements did you have to keep in mind? Think tech stack, constraints, etc.
• How did you go about shipping your ticket?
• Why did you take the approach you took?

The video should be no longer than 5 minutes, and you must demo the project in the video.

Submission Details

Submit the links to your Loom video and code on GitHub using the form below.

You can access the submission form in the Portal.

Note: If any one link is missing, the assignment will not be graded and you will have to resubmit.

Your code should:

• be on a forked version of the project repo.
• meet all the requirements listed on the ticket in the README file for this build sprint.

In your Loom video, you must:

• demo the code you created for this ticket.
• articulate how you coded this ticket and why you took that approach.
• showcase your workflow and what steps you took to code this ticket.

All submissions will be graded based on criteria set forth in the rubric below.

Never used Loom before?

How to get started with Loom:
https://youtu.be/eSMiGNzJwtg

How to use the Loom Chrome Extension:
https://youtu.be/tR_t9owJpRA

Need support? Open a support ticket in the Hub!

Points

100

Submitting

Nothing

Rubric

Build Sprint Grading Criteria