javascript-learning-labs

🧱 Object Manipulation Labs

📝 Description

This folder contains JavaScript exercises focused on working with objects — including accessing properties, comparing object structures, and applying rule-based matching. These labs emphasize how objects store related data and how key/value relationships are evaluated programmatically.

More object-focused practice labs will be added here as learning progresses.

🔑 Matching Object Filter

This lab filters an array of objects and returns only those that contain all key/value pairs specified in a source object. It demonstrates how structured data can be evaluated using dynamic property comparison.

📌 Example Behavior (Matching Object Filter)

whatIsInAName(
  [{ first: "Romeo", last: "Montague" }, { first: "Tybalt", last: "Capulet" }],
  { last: "Capulet" }
)
→ [{ first: "Tybalt", last: "Capulet" }]

whatIsInAName(
  [{ apple: 1, bat: 2 }, { bat: 2 }],
  { apple: 1, bat: 2 }
)
→ [{ apple: 1, bat: 2 }]

🛠️ Concepts Practiced (Matching Object Filter)

Accessing object properties dynamically
Using Object.keys() to extract property names
Comparing object values using key matching
Combining array filtering with object logic
Evaluating structured data based on rule sets

💡 Reflection (Matching Object Filter)

This lab introduces deeper interaction with structured data by moving beyond simple values to key/value relationships. Instead of transforming array elements, the function evaluates whether objects meet a set of property requirements. This mirrors real-world tasks such as data filtering, query matching, and record validation.

🗳️ Voting System

This lab implements a poll system that tracks votes for different options using structured collections. It ensures that each voter can only vote once per option and maintains a count of votes for each choice.

📌 Example Behavior (Voting System)

addOption("Turkey")
→ Option "Turkey" added to the poll.

vote("Turkey", 1)
→ Voter 1 voted for "Turkey".

vote("Turkey", 1)
→ Voter 1 has already voted for "Turkey".

displayResults()
→
Poll Results:
Turkey: 2 votes
Morocco: 1 votes
Japan: 0 votes

🛠️ Concepts Practiced (Voting System)

Using Map to associate options with voters
Using Set to enforce unique values
Preventing duplicate actions through data structure constraints
Iterating over Map entries
Managing state in a controlled data system

💡 Reflection (Voting System)

This lab demonstrates how combining Map and Set can enforce real-world constraints such as one vote per user. Instead of relying on conditional logic alone, the data structures themselves help maintain integrity. This approach reflects practical patterns used in applications that require uniqueness, tracking, and controlled state updates.

🌿 Plant Nursery Catalog

This lab models a plant inventory system using object-based records and keyed collections. It tracks plant varieties and their inventory counts by size, allowing updates such as selling items, removing plants, and displaying catalog data.

📌 Example Behavior (Plant Nursery Catalog)

sellPlants(ballerina, "small", 5)
→ "Catalog successfully updated."

sellPlants(willowVale, "large", 1)
→ "Not enough large size pots for Lavandula stoechas 'Willow Vale'. Only 0 left."

removePlant(royalCrown)
→ true

🛠️ Concepts Practiced (Plant Nursery Catalog)

Modeling structured data with objects
Using Map for key-based data storage
Managing inventory state through object mutation
Iterating over Map entries with forEach
Using Set to extract unique values
Combining multiple data structures (Object, Map, Set)

💡 Reflection (Plant Nursery Catalog)

This lab expands object usage into real-world data modeling by combining objects with specialized collection types like Map and Set. Instead of working with isolated objects, the system manages relationships between data entities and their associated state. This mirrors practical scenarios such as inventory systems, databases, and application state management.

💡 Topic Reflection

These labs focus on how objects organize related data and how programs reason about that structure. Working with keys and values builds an understanding of how JavaScript represents complex information, laying the foundation for handling APIs, configuration objects, and real application data models.