Bundle size analysis in Angular - Step-by-Step Execution

Concept Flow - Bundle size analysis

Start Angular Build

↓

Build Produces Bundle Files

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Run Bundle Analyzer Tool

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Analyze Bundle Contents

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Identify Large Modules

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Optimize Code (Lazy Loading, Tree Shaking)

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Rebuild and Re-Analyze

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Repeat Until Bundle Size Acceptable

This flow shows how Angular builds bundles, analyzes their size, identifies large parts, optimizes, and repeats to reduce bundle size.

Execution Sample

Angular

ng build --prod --stats-json
npx source-map-explorer dist/main.js
// Analyze output and optimize

Build Angular app with stats, then use source-map-explorer to see bundle size details.

Execution Table

Step	Action	Input/Tool	Output/Result
1	Run Angular production build	ng build --prod --stats-json	Generates dist folder with bundles and stats.json
2	Run bundle analyzer	npx source-map-explorer dist/main.js	Visual report showing sizes of modules in main.js
3	Review report	Report with module sizes	Identify large modules like Angular core, third-party libs
4	Apply optimizations	Lazy loading, tree shaking, code splitting	Smaller bundle size after rebuild
5	Rebuild app	ng build --prod --stats-json	New bundles with reduced size
6	Re-run analyzer	npx source-map-explorer dist/main.js	Updated report showing size improvements
7	Repeat if needed	Analyze and optimize	Bundle size meets performance goals

💡 Stop when bundle size is optimized and meets performance targets

Variable Tracker

Variable	Start	After Step 4	After Step 5	Final
Bundle Size (MB)	10.5	7.2	6.8	6.8
Large Modules Count	5	3	3	3
Lazy Loaded Modules	0	2	2	2

Key Moments - 3 Insights

Why does the bundle size not reduce immediately after the first build?

The first build creates the bundles and stats.json but no optimizations are applied yet. See execution_table step 1 and 2 where analysis happens after build.

How does lazy loading affect the bundle size?

Lazy loading splits code into separate bundles loaded on demand, reducing initial bundle size. This is shown in variable_tracker where Lazy Loaded Modules increase after step 4.

Why run the analyzer multiple times?

Each time you optimize and rebuild, you run the analyzer again to verify improvements. This loop is shown in execution_table steps 6 and 7.

Visual Quiz - 3 Questions

Look at the execution_table, what tool is used to analyze the bundle size?

A webpack-dev-server

B ng serve

C source-map-explorer

D npm install

💡 Hint

Check execution_table step 2 for the tool used to analyze bundles.

According to variable_tracker, what happens to the bundle size after applying optimizations?

A It increases

B It decreases

C It stays the same

D It becomes zero

💡 Hint

Look at Bundle Size (MB) values from Start to After Step 5 in variable_tracker.

At which step in execution_table do you identify large modules?

A Step 3

B Step 1

C Step 5

D Step 7

💡 Hint

Step 3 in execution_table shows reviewing the report to identify large modules.

Concept Snapshot

Angular Bundle Size Analysis:
- Build with 'ng build --prod --stats-json' to get bundles and stats
- Use 'source-map-explorer' to visualize bundle contents
- Identify large modules and optimize with lazy loading and tree shaking
- Rebuild and re-analyze until bundle size is acceptable
- Repeat to keep app fast and small

Full Transcript

Bundle size analysis in Angular starts by building the app with production settings and generating a stats file. Then, a tool like source-map-explorer is run to visualize the sizes of different modules inside the bundle. This helps identify which parts of the code or libraries are large. Developers then apply optimizations such as lazy loading modules and tree shaking unused code. After rebuilding, the analysis is repeated to check if the bundle size has decreased. This process repeats until the bundle size is optimized for better app performance.