Project: Custom Indian Business Utility Package (indialib)0%

Working with Context Managers (with statement)

Project: Custom Indian Business Utility Package (indialib)

Intermediate16 min read•Updated: 2026-10-01

Project: Custom Indian Business Utility Package (indialib)

Welcome to the Chapter 3 Capstone Project! Over the preceding lessons, you mastered module creation, search hierarchies, __name__ == '__main__', package structures, and standard library tools.

Now, you will synthesize all these disciplines by engineering a reusable, production-ready Python package named indialib. This package solves everyday computational challenges for Indian digital enterprises:

1
Indian Currency Formatter (currency.py): Converts numbers to traditional South Asian comma-separated formats (Thousands, Lakhs, Crores: ₹12,34,567.89).
2
Identity & Tax Validator (validators.py): Validates 10-character Indian PAN cards, 12-digit Aadhaar numbers, and 15-character GSTIN tax identifiers.
3
Data Masking & Security (security.py): Masks sensitive customer credentials for compliance (XXXX-XXXX-5678).
4
Package Facade (__init__.py): Curates clean public exports and governs access via __all__.

Real-World Analogy: Building a Reusable Zoho/Tally Business SDK

Imagine building a shared internal toolkit for a financial technology startup in Bengaluru:

Visual Architecture Blueprint

+-------------------------------------------------------------------------+
|                    INDIALIB BUSINESS SDK ARCHITECTURE                   |
+-------------------------------------------------------------------------+
|                                                                         |
|   Consumer Application (billing_service.py)                             |
|          │                                                              |
|          ▼                                                              |
|   Package Facade: indialib/__init__.py                                  |
|   ├── Exposes: format_inr, validate_pan, mask_aadhaar                    |
|   └── Enforces __all__ boundary & version stamping                      |
|          │                                                              |
|          ├──────────────────────┼──────────────────────┐                |
|          ▼                      ▼                      ▼                |
|   [ currency.py ]        [ validators.py ]      [ security.py ]         |
|   Lakhs/Crores Engine    PAN & GSTIN Regex      Aadhaar Data Masker     |
|                                                                         |
+-------------------------------------------------------------------------+

Any engineering team within your company can install or import indialib and immediately format financial ledgers or sanitize customer KYC inputs with zero code duplication.

Indian Numbering System Formatting Rule

Unlike the Western numbering system (groups of 3 digits: 1,000,000), the Indian numbering system groups the last 3 digits together, and every subsequent group by 2 digits:

1Number:       1 2 3 4 5 6 7 8
2Western:      12,345,678  (12 Million, 345 Thousand, 678)
3Indian:       1,23,45,678 (1 Crore, 23 Lakh, 45 Thousand, 678)

Complete Production-Grade Implementation

Here is the modular, fully runnable codebase for the indialib package:

Visual Architecture & Process Flow

How data and code flow step-by-step

Flowchart

Step 1

def format_inr

amount: float, symbol: str = "₹"

Step 2

str:

Expected Output

1=== Running indialib Business SDK Verification (v1.2.0) ===
2 
3--- Indian Currency Formatting (Lakhs & Crores) ---
4  Raw:       450.00  ➔  Formatted: ₹450.00
5  Raw:     1,500.00  ➔  Formatted: ₹1,500.00
6  Raw:    95,000.00  ➔  Formatted: ₹95,000.00
7  Raw: 1,234,567.89  ➔  Formatted: ₹12,34,567.89
8  Raw: 50,000,000.00  ➔  Formatted: ₹5,00,00,000.00
9 
10--- Identity & Tax Format Validation ---
11  PAN 'ABCDE1234F    ': VALID ✅
12  PAN 'abcde1234f    ': VALID ✅
13  PAN '12345ABCDE    ': INVALID ❌
14  PAN 'TOOLONG12345F ': INVALID ❌
15  GST '27AAPFU0939F1ZV ': VALID ✅
16  GST '07AAAAA0000A1Z5 ': VALID ✅
17  GST 'INVALID_GST_SAMPLE': INVALID ❌
18 
19--- Compliance Aadhaar Data Masking ---
20  Raw Aadhaar   : 9876 5432 1098
21  Masked Output : XXXX-XXXX-1098
22  Audit Ref ID  : KYC-3B8A9F1C

Best Practices & Comparison: Do's and Don'ts

Practice	Bad Implementation	Gold-Standard Implementation
Number Formatting	Using Western thousands commas for Indian rupees	Custom grouping for thousands, lakhs, and crores
Security Masking	Storing plain raw Aadhaar numbers	Store masked Aadhaar `XXXX-XXXX-1234` for UIDAI compliance
Random IDs	Using `random.randint()` for financial references	Use `secrets.token_hex()` for tamper-proof reference tokens
Package Exports	Leaving `__all__` empty in `__init__.py`	Explicitly define `__all__` to govern public API surface
Input Sanitization	Assuming user won't pass spaces in PAN or Aadhaar	Clean whitespace and normalize case with `.strip().upper()`

Quick Revision Summary Cheat Sheet

Lakhs & Crores Rule: Rightmost 3 digits group first, then all subsequent numbers group in pairs of 2.
PAN Format: ^[A-Z]{5}[0-9]{4}[A-Z]{1}$ (exactly 10 uppercase characters).
Aadhaar Masking: Keep only the last 4 digits visible for regulatory compliance.
Package Architecture: Submodules handle distinct logic (currency.py, validators.py); __init__.py aggregates them into an intuitive facade.
Version Tracking: Always define __version__ = "X.Y.Z" at the package root for dependency tracking.

Practice Challenge

Scenario: Indian Bank IFSC Code Validator & Normalizer

Add an IFSC (Indian Financial System Code) validator to the indialib package:

1
Create a function validate_ifsc(ifsc_code):

Must consist of exactly 11 characters.
The first 4 characters must be uppercase letters (Bank Code).
The 5th character must be strictly the number 0 (reserved for future use).
The last 6 characters can be letters or numbers (Branch Code).
Standard regex: ^[A-Z]{4}0[A-Z0-9]{6}$.

1
Create a function normalize_mobile(mobile_str):

Strips spaces, hyphens, and leading +91 or 0.
Returns a clean 10-digit mobile number if valid, or None if invalid.

Starter Code

1import re
2 
3def validate_ifsc(ifsc_code):
4    pass
5 
6def normalize_mobile(mobile_str):
7    pass

Complete Solution

Visual Architecture & Process Flow

How data and code flow step-by-step

Flowchart

Step 1

def validate_ifsc

ifsc_code: str

Step 2

bool:

Expected Output

1=== IFSC Code Validation ===
IFSC 'SBIN0001010 ': VALID ✅
IFSC 'HDFC0000452 ': VALID ✅
IFSC 'PUNB0123456 ': VALID ✅
IFSC 'INVALID123  ': INVALID ❌
IFSC 'SBIN1001010 ': INVALID ❌
7 
8=== Indian Mobile Normalization ===
Raw: +91 98765-43210    ➔ Normalized: 9876543210
Raw: 09811223344        ➔ Normalized: 9811223344
Raw: 9444556677         ➔ Normalized: 9444556677
Raw: 1234567890         ➔ Normalized: [INVALID]
Raw: +91 8877665544     ➔ Normalized: 8877665544

Interactive Quiz• Knowledge Check

Practice Quiz

Question 1

In the Indian numbering system, how is the number 1234567.89 correctly formatted?

Question 2

What is the standard structure of a valid 10-character Indian PAN number?

Question 3

Why is data masking (e.g. XXXX-XXXX-1098) applied to Aadhaar numbers in software systems?

Question 4

What is the role of secrets.token_hex(4).upper() in generating transaction references?

Question 5

Why should a package's __init__.py explicitly define an __all__ list?

🚀 What's Next?

In the next lesson, we will continue your intermediate Python journey with Working with Context Managers (with statement) (4: File Handling Advanced).

👉 Continue to Next Lesson: Working with Context Managers (with statement) →

Next Lesson

Working with Context Managers (with statement)

Continue learning with hands-on practice, examples, and exercises in the upcoming topic.

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Previous Lesson	Next Lesson
Popular Python Modules Overview	Working with Context Managers (with statement)

Practice Quiz

Test your understanding of this lesson with 5 questions. Each question has one correct answer.

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Working with Context Managers (with statement)

Project: Custom Indian Business Utility Package (indialib)

Intermediate16 min read•Updated: 2026-10-01

Study Materials Cheatsheet

Project: Custom Indian Business Utility Package (indialib)

Welcome to the Chapter 3 Capstone Project! Over the preceding lessons, you mastered module creation, search hierarchies, __name__ == '__main__', package structures, and standard library tools.

1
Indian Currency Formatter (currency.py): Converts numbers to traditional South Asian comma-separated formats (Thousands, Lakhs, Crores: ₹12,34,567.89).
2
Identity & Tax Validator (validators.py): Validates 10-character Indian PAN cards, 12-digit Aadhaar numbers, and 15-character GSTIN tax identifiers.
3
Data Masking & Security (security.py): Masks sensitive customer credentials for compliance (XXXX-XXXX-5678).
4
Package Facade (__init__.py): Curates clean public exports and governs access via __all__.

Real-World Analogy: Building a Reusable Zoho/Tally Business SDK

Imagine building a shared internal toolkit for a financial technology startup in Bengaluru:

Visual Architecture Blueprint

+-------------------------------------------------------------------------+
|                    INDIALIB BUSINESS SDK ARCHITECTURE                   |
+-------------------------------------------------------------------------+
|                                                                         |
|   Consumer Application (billing_service.py)                             |
|          │                                                              |
|          ▼                                                              |
|   Package Facade: indialib/__init__.py                                  |
|   ├── Exposes: format_inr, validate_pan, mask_aadhaar                    |
|   └── Enforces __all__ boundary & version stamping                      |
|          │                                                              |
|          ├──────────────────────┼──────────────────────┐                |
|          ▼                      ▼                      ▼                |
|   [ currency.py ]        [ validators.py ]      [ security.py ]         |
|   Lakhs/Crores Engine    PAN & GSTIN Regex      Aadhaar Data Masker     |
|                                                                         |
+-------------------------------------------------------------------------+

Any engineering team within your company can install or import indialib and immediately format financial ledgers or sanitize customer KYC inputs with zero code duplication.

Indian Numbering System Formatting Rule

Unlike the Western numbering system (groups of 3 digits: 1,000,000), the Indian numbering system groups the last 3 digits together, and every subsequent group by 2 digits:

1Number:       1 2 3 4 5 6 7 8
2Western:      12,345,678  (12 Million, 345 Thousand, 678)
3Indian:       1,23,45,678 (1 Crore, 23 Lakh, 45 Thousand, 678)

Complete Production-Grade Implementation

Here is the modular, fully runnable codebase for the indialib package:

Visual Architecture & Process Flow

How data and code flow step-by-step

Flowchart

Step 1

def format_inr

amount: float, symbol: str = "₹"

Step 2

str:

Expected Output

1=== Running indialib Business SDK Verification (v1.2.0) ===
2 
3--- Indian Currency Formatting (Lakhs & Crores) ---
4  Raw:       450.00  ➔  Formatted: ₹450.00
5  Raw:     1,500.00  ➔  Formatted: ₹1,500.00
6  Raw:    95,000.00  ➔  Formatted: ₹95,000.00
7  Raw: 1,234,567.89  ➔  Formatted: ₹12,34,567.89
8  Raw: 50,000,000.00  ➔  Formatted: ₹5,00,00,000.00
9 
10--- Identity & Tax Format Validation ---
11  PAN 'ABCDE1234F    ': VALID ✅
12  PAN 'abcde1234f    ': VALID ✅
13  PAN '12345ABCDE    ': INVALID ❌
14  PAN 'TOOLONG12345F ': INVALID ❌
15  GST '27AAPFU0939F1ZV ': VALID ✅
16  GST '07AAAAA0000A1Z5 ': VALID ✅
17  GST 'INVALID_GST_SAMPLE': INVALID ❌
18 
19--- Compliance Aadhaar Data Masking ---
20  Raw Aadhaar   : 9876 5432 1098
21  Masked Output : XXXX-XXXX-1098
22  Audit Ref ID  : KYC-3B8A9F1C

Best Practices & Comparison: Do's and Don'ts

Practice	Bad Implementation	Gold-Standard Implementation
Number Formatting	Using Western thousands commas for Indian rupees	Custom grouping for thousands, lakhs, and crores
Security Masking	Storing plain raw Aadhaar numbers	Store masked Aadhaar `XXXX-XXXX-1234` for UIDAI compliance
Random IDs	Using `random.randint()` for financial references	Use `secrets.token_hex()` for tamper-proof reference tokens
Package Exports	Leaving `__all__` empty in `__init__.py`	Explicitly define `__all__` to govern public API surface
Input Sanitization	Assuming user won't pass spaces in PAN or Aadhaar	Clean whitespace and normalize case with `.strip().upper()`

Quick Revision Summary Cheat Sheet

Lakhs & Crores Rule: Rightmost 3 digits group first, then all subsequent numbers group in pairs of 2.
PAN Format: ^[A-Z]{5}[0-9]{4}[A-Z]{1}$ (exactly 10 uppercase characters).
Aadhaar Masking: Keep only the last 4 digits visible for regulatory compliance.
Package Architecture: Submodules handle distinct logic (currency.py, validators.py); __init__.py aggregates them into an intuitive facade.
Version Tracking: Always define __version__ = "X.Y.Z" at the package root for dependency tracking.

Practice Challenge

Scenario: Indian Bank IFSC Code Validator & Normalizer

Add an IFSC (Indian Financial System Code) validator to the indialib package:

1
Create a function validate_ifsc(ifsc_code):

Must consist of exactly 11 characters.
The first 4 characters must be uppercase letters (Bank Code).
The 5th character must be strictly the number 0 (reserved for future use).
The last 6 characters can be letters or numbers (Branch Code).
Standard regex: ^[A-Z]{4}0[A-Z0-9]{6}$.

1
Create a function normalize_mobile(mobile_str):

Strips spaces, hyphens, and leading +91 or 0.
Returns a clean 10-digit mobile number if valid, or None if invalid.

Starter Code

1import re
2 
3def validate_ifsc(ifsc_code):
4    pass
5 
6def normalize_mobile(mobile_str):
7    pass

Complete Solution

Visual Architecture & Process Flow

How data and code flow step-by-step

Flowchart

Step 1

def validate_ifsc

ifsc_code: str

Step 2

bool:

Expected Output

1=== IFSC Code Validation ===
IFSC 'SBIN0001010 ': VALID ✅
IFSC 'HDFC0000452 ': VALID ✅
IFSC 'PUNB0123456 ': VALID ✅
IFSC 'INVALID123  ': INVALID ❌
IFSC 'SBIN1001010 ': INVALID ❌
7 
8=== Indian Mobile Normalization ===
Raw: +91 98765-43210    ➔ Normalized: 9876543210
Raw: 09811223344        ➔ Normalized: 9811223344
Raw: 9444556677         ➔ Normalized: 9444556677
Raw: 1234567890         ➔ Normalized: [INVALID]
Raw: +91 8877665544     ➔ Normalized: 8877665544

Interactive Quiz• Knowledge Check

Practice Quiz

Question 1

In the Indian numbering system, how is the number 1234567.89 correctly formatted?

Question 2

What is the standard structure of a valid 10-character Indian PAN number?

Question 3

Why is data masking (e.g. XXXX-XXXX-1098) applied to Aadhaar numbers in software systems?

Question 4

What is the role of secrets.token_hex(4).upper() in generating transaction references?

Question 5

Why should a package's __init__.py explicitly define an __all__ list?

🚀 What's Next?

In the next lesson, we will continue your intermediate Python journey with Working with Context Managers (with statement) (4: File Handling Advanced).

👉 Continue to Next Lesson: Working with Context Managers (with statement) →

Next Lesson

Working with Context Managers (with statement)

Continue learning with hands-on practice, examples, and exercises in the upcoming topic.

Related Lessons

Previous Lesson	Next Lesson
Popular Python Modules Overview	Working with Context Managers (with statement)

Practice Quiz

Test your understanding of this lesson with 5 questions. Each question has one correct answer.

Previous Next