100% Free Forever
AI-Powered Learning
Industry Expert Content
Certificates & Badges
Learn At Your Own Pace
Python

Singleton and Factory Patterns

Learn how Singleton guarantees a single instance and how Factory Method delegates object creation to a central point.

Design Patterns — Creational & StructuralBeginner10 min readJul 8, 2026
Analogies

Introduction

Singleton and Factory Method are two of the most widely used Creational design patterns. Singleton ensures a class has only one instance and provides a global point of access to it. Factory Method defines an interface (or function) for creating an object but lets subclasses, or a parameterized creator function, decide which concrete class to instantiate. Both patterns exist to control 'how' and 'when' objects come into being, rather than leaving instantiation scattered throughout the codebase.

🏏

Cricket analogy: Singleton is like a team having exactly one official scorer whose scorecard is the single source of truth for the match, while Factory Method is like a selector function that decides which type of bowler to bring on, pacer, spinner, or all-rounder, based on the situation, without the captain hardcoding the choice.

Explanation

A Singleton is useful when exactly one object is needed to coordinate actions across a system — for example, a configuration manager, a logging service, or a connection pool. It typically works by making the constructor private (or restricted) and exposing a static/class-level accessor that creates the instance on first use and returns the cached instance thereafter. Overuse of Singleton is a common anti-pattern because it introduces global state, which makes unit testing harder and can hide dependencies.

🏏

Cricket analogy: A Singleton is useful for a single official scoreboard that coordinates runs and wickets across the ground; it works by restricting who can update it directly and exposing one official channel that creates the record on first ball and returns the same running total thereafter, though over-relying on one global scoreboard for local team stats makes independent analysis harder.

Factory Method, by contrast, addresses a different problem: a class cannot anticipate which concrete class of object it needs to create. Instead of littering the codebase with direct calls to concrete constructors (e.g., PDFExporter(), CSVExporter()), client code calls a factory with a parameter (e.g., create_exporter("csv")), and the factory encapsulates the decision of which concrete class to instantiate. This keeps object-creation logic in one place and makes it easy to add new types without modifying client code — an application of the Open/Closed Principle.

🏏

Cricket analogy: Factory Method addresses picking the right bowler for a situation: instead of the captain hardcoding 'bring on Bumrah' every time, they call a selector with a parameter like 'need a wicket' or 'need to save runs,' and the selector encapsulates which bowler type, pace or spin, actually gets the ball.

Example

python
import threading

# --- Singleton: thread-safe lazy instantiation ---
class ConfigManager:
    _instance = None
    _lock = threading.Lock()

    def __new__(cls):
        if cls._instance is None:
            with cls._lock:
                if cls._instance is None:
                    cls._instance = super().__new__(cls)
                    cls._instance.settings = {}
        return cls._instance

    def set(self, key, value):
        self.settings[key] = value


# --- Factory Method: delegate creation based on a parameter ---
class Exporter:
    def export(self, data):
        raise NotImplementedError

class CSVExporter(Exporter):
    def export(self, data):
        return ",".join(data)

class JSONExporter(Exporter):
    def export(self, data):
        import json
        return json.dumps(data)

def create_exporter(kind: str) -> Exporter:
    exporters = {"csv": CSVExporter, "json": JSONExporter}
    if kind not in exporters:
        raise ValueError(f"Unknown exporter: {kind}")
    return exporters[kind]()


if __name__ == "__main__":
    a = ConfigManager()
    b = ConfigManager()
    a.set("debug", True)
    print(a is b, b.settings)  # True {'debug': True}

    exporter = create_exporter("json")
    print(exporter.export(["x", "y", "z"]))

Analysis

In the Singleton example, __new__ is overridden so that only one instance is ever created; the lock guards against a race condition where two threads might otherwise both see _instance is None at the same time. In the Factory Method example, create_exporter is the single place that knows how to map a string to a concrete Exporter subclass — client code never calls CSVExporter() or JSONExporter() directly. Adding a new format, such as XML, means adding one class and one dictionary entry, without touching any code that calls create_exporter.

🏏

Cricket analogy: In the scoreboard Singleton, only one official record is ever created, guarded so two officials updating it at the exact same ball don't create conflicting totals; in the bowler-selector Factory, select_bowler is the single place mapping situation to bowler type, so adding a new bowling style, like a mystery spinner, means adding one class without touching the captain's calling code.

A common mistake is conflating Singleton with Factory: Singleton constrains 'how many' instances exist, while Factory Method constrains 'which class' gets instantiated. They can be combined (a Factory that itself is a Singleton) but they solve orthogonal problems. Another common mistake is implementing Singleton without thread safety, which in multi-threaded environments can accidentally create two 'singleton' instances.

🏏

Cricket analogy: Confusing Singleton with Factory is like confusing 'there is only one official scorer' with 'the selector decides pace or spin'; a scoring system could combine both, one Singleton scorer that internally uses a Factory to instantiate the right delivery-type record, but they solve different problems, and a scorer implemented without safeguards against simultaneous updates from two officials can produce two conflicting 'official' totals.

Key Takeaways

  • Singleton guarantees exactly one instance of a class and a global access point to it.
  • Factory Method centralizes the decision of which concrete class to instantiate based on input.
  • Singleton controls instance count; Factory Method controls instance type — they are independent concerns.
  • Overusing Singleton introduces hidden global state that complicates testing.
  • Factory Method supports the Open/Closed Principle by letting new types be added without modifying client code.

Practice what you learned

Was this page helpful?

Topics covered

#Python#SoftwareEngineeringStudyNotes#SoftwareEngineering#SingletonAndFactoryPatterns#Singleton#Factory#Patterns#Explanation#StudyNotes#SkillVeris

Frequently Asked Questions

21 categories · pick one to explore

Where can I get free study notes for programming and tech subjects?
SkillVeris offers completely free study notes covering programming and tech subjects, with no signup fees or paywalls. The notes are structured by course and topic, written for quick understanding, and enriched with the Learn Through Hobbies analogy method, so you can revise concepts through cricket, music, gaming, cooking and more.
Are SkillVeris study notes good for exam revision?
Yes, the study notes are designed for efficient revision: each topic answers its heading immediately, keeps explanations concise, and links to related glossary terms and cheat sheets. Students preparing for university exams or certification tests use them as quick revision notes because they distil concepts without the padding of full textbooks.
What subjects do the free study notes cover?
The study notes span the platform's main domains, including AI and machine learning, Python and programming, web development, DevOps, cloud, security and databases. Coverage mirrors the 37 live courses, so notes exist for the topics you are actually studying, and new note sets are added as courses launch.
How are SkillVeris study notes different from regular textbooks?
The notes are answer-first, concise and free, whereas textbooks are long and often expensive. Each section explains one concept directly, then reinforces it through selectable hobby analogies like cricket or cooking. Notes also cross-link to the glossary, blog and cheat sheets, letting you jump to related material instantly instead of flipping pages.
Can I use the developer study material without creating an account?
The study notes are free to access, and SkillVeris does not charge anything for its developer study material at any point. Browsing notes is straightforward from the Study Notes section, and if you want progress tracking, certificates and AI Mentor conversations tied to your learning, a free account unlocks those extras.
Do the study notes explain concepts with analogies?
Yes, this is a signature SkillVeris feature. Study notes use the Learn Through Hobbies method, explaining technical concepts through analogies from twelve domains including cricket, music, gaming, photography, travel, movies, fitness, chess, cooking, finance, business and sports. You can switch the analogy domain instantly to whichever hobby makes the concept click.
Are the revision notes suitable for last-minute exam preparation?
Yes, revision notes on SkillVeris work well for last-minute preparation because every section states the answer in its first sentences, so skimming is genuinely effective. Pair them with the relevant cheat sheet for formulas and syntax, and use the glossary for any unfamiliar term you meet while cramming.
Is there free study material for AI and machine learning?
Yes, SkillVeris provides free study notes across its AI and ML catalogue, covering Python for AI, deep learning frameworks like PyTorch and TensorFlow, Hugging Face Transformers, Large Language Models, RAG, AI agents and MLOps. All of it is free, making it a strong resource for Indian students and global learners alike.
Can beginners understand the study notes, or are they for experts?
Beginners can absolutely use them. The notes are written in plain language, define terms as they appear, and lean on hobby analogies to make abstract ideas concrete. Difficulty scales with the underlying course level, so beginner-course notes stay gentle while advanced-course notes go deeper, and the glossary supports you throughout.
How do study notes connect with SkillVeris courses?
Study notes are organised by course and topic, so they map directly to the structured courses and their 24–40-lesson curriculum. Many learners study a lesson first, then use the matching notes for revision before module assessments and the final exam, where 80 percent is required to pass and earn the certificate.
Are there study notes for Python specifically?
Yes, Python is well covered through notes tied to the Python-focused courses, including Python for AI and ML. Topics span fundamentals through applied machine learning usage. You can reinforce the notes with Python practice in Code Lab, which runs code in your browser with no installation required.
Do the study notes include code examples?
Yes, study notes include code examples wherever a concept is best shown in code, alongside explanations, key points and analogies. Reading a snippet in the notes and then reproducing it yourself in Code Lab is an effective loop, since Code Lab lets you run code in the browser across six languages.
How often is new study material added to SkillVeris?
Study material grows alongside the course catalogue. Whenever new courses join the platform's 37 live courses, matching study notes, glossary entries and cheat sheets are added so the resources stay in sync. Existing notes are also refined over time, so it is worth revisiting topics you studied earlier.
Can I use SkillVeris notes to prepare for technical interviews?
Yes, the notes make excellent interview revision because they compress each concept into direct, answer-first explanations, which mirrors how you should answer interview questions. Combine them with the SkillVeris interview questions feature, which includes readiness scoring, to test whether your revision has actually made you interview-ready.
Are the study notes mobile-friendly for studying on the go?
Yes, the study notes are built to load fast and read comfortably on mobile devices, so you can revise during a commute or between classes. Sections are short and answer-first, which suits small screens, and analogy switching works on mobile too, letting you study anywhere without carrying books.
What is the difference between study notes and cheat sheets?
Study notes explain concepts in depth with context, examples and analogies, making them ideal for learning and revision. Cheat sheets are compact quick-reference summaries of syntax, commands and key facts, ideal once you already understand a topic. Most learners study the notes first, then keep the cheat sheet handy while coding.
Do study notes help if I am stuck on a course lesson?
Yes, reading the matching study notes often clarifies a lesson because the same concept is explained from a different angle, frequently with a different analogy. If you are still stuck, ask the AI Mentor, which answers 24/7 at Quick, Detailed or Deep-dive depth until the idea genuinely makes sense.
Is there free study material for DevOps and cloud topics?
Yes, SkillVeris carries free study notes for DevOps and cloud topics as part of its coverage across 37 live courses. The material suits learners following the DevOps Engineer or Cloud Engineer paths, and it links to related glossary terms and cheat sheets so you can revise the whole toolchain in one place.
Can school or college students in India use these notes for projects?
Yes, students across India and worldwide use SkillVeris notes for coursework, projects and exam preparation, and everything is free, which matters for student budgets. The notes explain concepts clearly enough to cite in project reports, and Code Lab lets you prototype the project code directly in your browser.
How should I combine study notes with other SkillVeris resources?
A proven loop: learn from a course lesson, revise with the matching study notes, look up unfamiliar terms in the glossary, keep the cheat sheet open while practising in Code Lab, and quiz yourself with interview questions. The AI Mentor fills any remaining gaps 24/7, at whatever depth you need.

What Learners Say

Real journeys from the SkillVeris community — swipe for more.

SkillVeris taught me Python through Cricket. Now I’m building real projects and feeling confident!
Arjun S. · B.Tech Student
The best platform for hobby-based learning. Concepts finally stick.
Priya R. · Data Analyst
I went from zero coding to a portfolio of projects — all by learning through my love for gaming. Landed my first internship!
Kabir M. · CS Undergraduate
Trending Topics50 popular tags — tap to explore
Trending CoursesAll 37 free courses — tap to browse