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Author SHA1 Message Date
Kamran Ahmed
38cbb06135 Frontend roadmaps changes 2025-09-08 15:47:58 +01:00
6021 changed files with 121287 additions and 31529 deletions

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@@ -3,6 +3,6 @@
"enabled": false
},
"_variables": {
"lastUpdateCheck": 1763378528944
"lastUpdateCheck": 1756224238932
}
}

2
.astro/types.d.ts vendored
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@@ -1,2 +1,2 @@
/// <reference types="astro/client" />
/// <reference path="content.d.ts" />
/// <reference path="content.d.ts" />

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@@ -0,0 +1,35 @@
name: "🙏 Submit a Project Idea"
description: Help us add project ideas to roadmaps.
labels: [project contribution]
assignees: []
body:
- type: markdown
attributes:
value: |
Thanks for taking the time to submit a project idea! Please fill out the information below and we'll get back to you as soon as we can.
- type: input
id: roadmap-title
attributes:
label: What Roadmap is this project for?
placeholder: e.g. Backend Roadmap
validations:
required: true
- type: dropdown
id: project-difficulty
attributes:
label: Project Difficulty
options:
- Beginner
- Intermediate
- Advanced
validations:
required: true
- type: textarea
id: roadmap-description
attributes:
label: Add Project Details
description: Please write a detailed description of the project in 3rd person e.g. "You are required to build a..."
placeholder: |
e.g. You are required to build a RESTful API...
validations:
required: true

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@@ -1,80 +0,0 @@
name: Cleanup Orphaned Content
on:
workflow_dispatch:
inputs:
roadmap_slug:
description: "The ID of the roadmap to clean up"
required: true
jobs:
cleanup-content:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Setup pnpm@v9
uses: pnpm/action-setup@v4
with:
version: 9
run_install: false
- name: Setup Node.js Version 20 (LTS)
uses: actions/setup-node@v4
with:
node-version: 20
cache: 'pnpm'
- name: Install Dependencies and Run Cleanup
run: |
echo "Installing Dependencies"
pnpm install
echo "Running Orphaned Content Cleanup"
npm run cleanup:orphaned-content -- --roadmap-slug=${{ inputs.roadmap_slug }}
- name: Read cleanup summary
id: read-summary
run: |
if [ -f .cleanup-summary.md ]; then
{
echo 'summary<<EOF'
cat .cleanup-summary.md
echo 'EOF'
} >> $GITHUB_OUTPUT
fi
- name: Check for changes
id: verify-changed-files
run: |
if [ -n "$(git status --porcelain)" ]; then
echo "changed=true" >> $GITHUB_OUTPUT
else
echo "changed=false" >> $GITHUB_OUTPUT
fi
- name: Delete summary file
if: steps.verify-changed-files.outputs.changed == 'true'
run: rm -f .cleanup-summary.md
- name: Create PR
if: steps.verify-changed-files.outputs.changed == 'true'
uses: peter-evans/create-pull-request@v7
with:
delete-branch: false
branch: "chore/cleanup-orphaned-content-${{ inputs.roadmap_slug }}"
base: "master"
labels: |
automated pr
reviewers: jcanalesluna,kamranahmedse
commit-message: "chore: cleanup orphaned content files"
title: "chore: cleanup orphaned content - ${{ inputs.roadmap_slug }}"
body: |
${{ steps.read-summary.outputs.summary }}
> [!IMPORTANT]
> This PR removes orphaned/duplicate content files for: ${{ inputs.roadmap_slug }}
>
> Commit: ${{ github.sha }}
> Workflow Path: ${{ github.workflow_ref }}
**Please review the changes and merge the PR if everything looks correct.**

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@@ -0,0 +1,52 @@
name: Refresh Roadmap Content JSON
on:
workflow_dispatch:
schedule:
- cron: '0 0 * * *'
jobs:
refresh-content:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Setup pnpm@v9
uses: pnpm/action-setup@v4
with:
version: 9
run_install: false
- name: Setup Node.js Version 20 (LTS)
uses: actions/setup-node@v4
with:
node-version: 20
cache: 'pnpm'
- name: Install Dependencies and Generate Content JSON
run: |
pnpm install
npm run generate:roadmap-content-json
- name: Create PR
uses: peter-evans/create-pull-request@v7
with:
delete-branch: false
branch: "chore/update-content-json"
base: "master"
labels: |
dependencies
automated pr
reviewers: kamranahmedse
commit-message: "chore: update roadmap content json"
title: "Updated Roadmap Content JSON - Automated"
body: |
## Updated Roadmap Content JSON
> [!IMPORTANT]
> This PR Updates the Roadmap Content JSON files stored in the `public` directory.
>
> Commit: ${{ github.sha }}
> Workflow Path: ${{ github.workflow_ref }}
**Please Review the Changes and Merge the PR if everything is fine.**

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@@ -1,17 +1,20 @@
name: Sync Repo to Database
name: Sync on Roadmap Changes
on:
workflow_dispatch:
inputs:
roadmap_slug:
description: "The slug of the roadmap to sync (e.g., frontend, backend)"
required: true
push:
branches:
- master
paths:
- 'src/data/roadmaps/**'
jobs:
sync-roadmap:
sync-on-changes:
runs-on: ubuntu-latest
if: github.actor != 'github-actions[bot]' && github.actor != 'dependabot[bot]'
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 2 # Fetch previous commit to compare changes
- name: Setup pnpm@v9
uses: pnpm/action-setup@v4
@@ -25,33 +28,40 @@ jobs:
node-version: 20
cache: 'pnpm'
- name: Get all roadmap files
id: roadmap-files
- name: Get changed files
id: changed-files
run: |
ROADMAP_DIR="src/data/roadmaps/${{ inputs.roadmap_slug }}"
if [ ! -d "$ROADMAP_DIR" ]; then
echo "Error: Roadmap directory '$ROADMAP_DIR' does not exist"
exit 1
echo "Getting changed files in /src/data/roadmaps/"
# Get changed files between HEAD and previous commit
CHANGED_FILES=$(git diff --name-only HEAD~1 HEAD -- src/data/roadmaps/)
if [ -z "$CHANGED_FILES" ]; then
echo "No changes found in roadmaps directory"
echo "has_changes=false" >> $GITHUB_OUTPUT
exit 0
fi
echo "Getting all files in $ROADMAP_DIR"
ALL_FILES=$(find "$ROADMAP_DIR" -type f | tr '\n' ',')
echo "Files to sync:"
echo "$ALL_FILES"
echo "files=$ALL_FILES" >> $GITHUB_OUTPUT
echo "Changed files:"
echo "$CHANGED_FILES"
# Convert to space-separated list for the script
CHANGED_FILES_LIST=$(echo "$CHANGED_FILES" | tr '\n' ',')
echo "has_changes=true" >> $GITHUB_OUTPUT
echo "changed_files=$CHANGED_FILES_LIST" >> $GITHUB_OUTPUT
- name: Install Dependencies
if: steps.changed-files.outputs.has_changes == 'true'
run: |
echo "Installing Dependencies"
pnpm install
- name: Run sync script
- name: Run sync script with changed files
if: steps.changed-files.outputs.has_changes == 'true'
run: |
echo "Running sync script for roadmap: ${{ inputs.roadmap_slug }}"
echo "Files: ${{ steps.roadmap-files.outputs.files }}"
npm run sync:repo-to-database -- --files="${{ steps.roadmap-files.outputs.files }}" --secret=${{ secrets.GH_SYNC_SECRET }}
echo "Running sync script for changed roadmap files"
echo "Changed files: ${{ steps.changed-files.outputs.changed_files }}"
# Run your script with the changed file paths
npm run sync:repo-to-database -- --files="${{ steps.changed-files.outputs.changed_files }}" --secret=${{ secrets.GH_SYNC_SECRET }}

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@@ -20,29 +20,10 @@ export default defineConfig({
status: 301,
destination: '/ai',
},
'/best-practices': {
status: 301,
destination: '/roadmaps',
},
'/best-practices/aws': {
status: 301,
destination: '/aws-best-practices',
},
'/best-practices/backend-performance': {
status: 301,
destination: '/backend-performance-best-practices',
},
'/best-practices/frontend-performance': {
status: 301,
destination: '/frontend-performance-best-practices',
},
'/best-practices/api-security': {
status: 301,
destination: '/api-security-best-practices',
},
'/best-practices/code-review': {
status: 301,
destination: '/code-review-best-practices',
},
vite: {
server: {
allowedHosts: ['roadmap.sh', 'port3k.kamranahmed.info'],
},
},
markdown: {
@@ -91,8 +72,5 @@ export default defineConfig({
ssr: {
noExternal: [/^@roadmapsh\/editor.*$/],
},
server: {
allowedHosts: ['roadmap.sh', 'port3k.kamranahmed.info'],
},
},
});

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@@ -6,10 +6,8 @@ First of all, thank you for considering to contribute. Please look at the detail
- [Existing Roadmaps](#existing-roadmaps)
- [Adding Projects](#adding-projects)
- [Adding Content](#adding-content)
- [How To Structure Content](#how-to-structure-content)
- [Guidelines](#guidelines)
- [Good vs. Not So Good Contributions](#good-vs-not-so-good-contributions)
- [Local Development](#local-development)
## New Roadmaps
@@ -23,7 +21,7 @@ For new roadmaps, you can either:
For the existing roadmaps, please follow the details listed for the nature of contribution:
- **Fixing Typos** — Make your changes in the [roadmap markdown file](https://github.com/kamranahmedse/developer-roadmap/tree/master/src/data/roadmaps) and submit a [PR](https://github.com/kamranahmedse/developer-roadmap/pulls).
- **Adding/Removing Nodes and Modifying Node Titles** — Please open an [issue](https://github.com/kamranahmedse/developer-roadmap/issues) with your suggestion.
- **Adding or Removing Nodes** — Please open an [issue](https://github.com/kamranahmedse/developer-roadmap/issues) with your suggestion.
**Note:** Please note that our goal is **not to have the biggest list of items**. Our goal is to list items or skills most relevant today.
@@ -55,7 +53,6 @@ Find [the content directory inside the relevant roadmap](https://github.com/kamr
- Content must be in English.
- Maximum of 8 links per topic.
- **No GeeksforGeeks links** — Links to geeksforgeeks.org are not accepted.
- Follow the below style guide for content.
Please note that we are intentionally keeping the content under the topic popup concise. You MUST always aim to explain the topic simply in a **single paragraph** or so and provide external resources where users can learn more about the topic.

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@@ -10,3 +10,10 @@ conditions do not apply to the readonly GitHub forks created using the Fork butt
GitHub with the whole purpose of contributing to the project.
Copyright © 2017 - Present. Kamran Ahmed <kamranahmed.se@gmail.com>
Please note that I am really flexible with allowing the usage of the content in this
repository. If you reach out to me with a brief detail of why and how you would like
to use this content, there is a good chance that I will allow you to use it. The reason
behind this strictness in the license is to stop the people who have been using these
roadmaps in ill manners e.g. ripping people off with suggesting random affiliate links,
redistributing these roadmaps just for the sake of monetizing the traffic.

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@@ -31,10 +31,7 @@
"migrate:editor-roadmaps": "tsx ./scripts/migrate-editor-roadmap.ts",
"sync:content-to-repo": "tsx ./scripts/sync-content-to-repo.ts",
"sync:repo-to-database": "tsx ./scripts/sync-repo-to-database.ts",
"sync:roadmap": "tsx ./scripts/sync-roadmap-to-database.ts",
"migrate:content-repo-to-database": "tsx ./scripts/migrate-content-repo-to-database.ts",
"cleanup:orphaned-content": "tsx ./scripts/cleanup-orphaned-content.ts",
"official:roadmap-assets": "tsx ./scripts/official-roadmap-assets.ts",
"test:e2e": "playwright test"
},
"dependencies": {

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@@ -0,0 +1,414 @@
{
"aStaDENn5PhEa-cFvNzXa": {
"title": "Mathematics",
"description": "Mathematics is the foundation of AI and Data Science. It is essential to have a good understanding of mathematics to excel in these fields.",
"links": []
},
"4WZL_fzJ3cZdWLLDoWN8D": {
"title": "Statistics",
"description": "Statistics is the science of collecting, analyzing, interpreting, presenting, and organizing data. It is a branch of mathematics that deals with the collection, analysis, interpretation, presentation, and organization of data. It is used in a wide range of fields, including science, engineering, medicine, and social science. Statistics is used to make informed decisions, to predict future events, and to test hypotheses. It is also used to summarize data, to describe relationships between variables, and to make inferences about populations based on samples.",
"links": []
},
"gWMvD83hVXeTmCuHGIiOL": {
"title": "Linear Algebra, Calculus, Mathematical Analysis",
"description": "",
"links": [
{
"title": "Mathematics for Machine Learning Specialization",
"url": "https://imp.i384100.net/baqMYv",
"type": "article"
},
{
"title": "Explore top posts about Math",
"url": "https://app.daily.dev/tags/math?ref=roadmapsh",
"type": "article"
},
{
"title": "Linear Algebra Youtube Course",
"url": "https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab",
"type": "video"
}
]
},
"mwPJh33MEUQ4Co_LiVEOb": {
"title": "Differential Calculus ",
"description": "",
"links": [
{
"title": "Algebra and Differential Calculus for Data Science",
"url": "https://imp.i384100.net/LX5M7M",
"type": "article"
},
{
"title": "Calculus Youtube Course",
"url": "https://www.youtube.com/playlist?list=PLZHQObOWTQDMsr9K-rj53DwVRMYO3t5Yr",
"type": "video"
}
]
},
"Y9YJdARIRqqCBCy3GVYdA": {
"title": "Statistics, CLT",
"description": "",
"links": [
{
"title": "Introduction to Statistics",
"url": "https://imp.i384100.net/3eRv4v",
"type": "article"
}
]
},
"XJXIkWVDIrPJ-bVIvX0ZO": {
"title": "Hypothesis Testing",
"description": "",
"links": [
{
"title": "Introduction to Statistical Analysis: Hypothesis Testing",
"url": "https://imp.i384100.net/vN0JAA",
"type": "article"
},
{
"title": "Explore top posts about Testing",
"url": "https://app.daily.dev/tags/testing?ref=roadmapsh",
"type": "article"
}
]
},
"jxJtwbiCvxHqmkWkE7zdx": {
"title": "Probability and Sampling",
"description": "",
"links": [
{
"title": "Probability and Statistics: To p or not to p?",
"url": "https://imp.i384100.net/daDM6Q",
"type": "article"
},
{
"title": "Explore top posts about Statistics",
"url": "https://app.daily.dev/tags/statistics?ref=roadmapsh",
"type": "article"
}
]
},
"mJq9b50MJM9o9dLhx40iN": {
"title": "AB Testing",
"description": "",
"links": [
{
"title": "Practitioners Guide to Statistical Tests",
"url": "https://vkteam.medium.com/practitioners-guide-to-statistical-tests-ed2d580ef04f#1e3b",
"type": "article"
},
{
"title": "Step by Step Process for Planning an A/B Test",
"url": "https://medium.com/data-science/step-by-step-for-planning-an-a-b-test-ef3c93143c0b",
"type": "article"
},
{
"title": "Explore top posts about A/B Testing",
"url": "https://app.daily.dev/tags/ab-testing?ref=roadmapsh",
"type": "article"
}
]
},
"v68nwX914qCwHDSwY_ZhG": {
"title": "Increasing Test Sensitivity",
"description": "",
"links": [
{
"title": "Minimum Detectable Effect (MDE)",
"url": "https://splitmetrics.com/resources/minimum-detectable-effect-mde/",
"type": "article"
},
{
"title": "Improving the Sensitivity of Online Controlled Experiments: Case Studies at Netflix",
"url": "https://kdd.org/kdd2016/papers/files/adp0945-xieA.pdf",
"type": "article"
},
{
"title": "Improving the Sensitivity of Online Controlled Experiments by Utilizing Pre-Experiment Data",
"url": "https://exp-platform.com/Documents/2013-02-CUPED-ImprovingSensitivityOfControlledExperiments.pdf",
"type": "article"
},
{
"title": "How Booking.com increases the power of online experiments with CUPED",
"url": "https://booking.ai/how-booking-com-increases-the-power-of-online-experiments-with-cuped-995d186fff1d",
"type": "article"
},
{
"title": "Improving Experimental Power through Control Using Predictions as Covariate — CUPAC",
"url": "https://doordash.engineering/2020/06/08/improving-experimental-power-through-control-using-predictions-as-covariate-cupac/",
"type": "article"
},
{
"title": "Improving the Sensitivity of Online Controlled Experiments: Case Studies at Netflix",
"url": "https://www.researchgate.net/publication/305997925_Improving_the_Sensitivity_of_Online_Controlled_Experiments_Case_Studies_at_Netflix",
"type": "article"
}
]
},
"n2JFGwFxTuOviW6kHO1Uv": {
"title": "Ratio Metrics",
"description": "",
"links": [
{
"title": "Applying the Delta Method in Metric Analytics: A Practical Guide with Novel Ideas",
"url": "https://arxiv.org/pdf/1803.06336.pdf",
"type": "article"
},
{
"title": "Approximations for Mean and Variance of a Ratio",
"url": "https://www.stat.cmu.edu/~hseltman/files/ratio.pdf",
"type": "article"
}
]
},
"Gd2egqKZPnbPW1W2jw4j8": {
"title": "Econometrics",
"description": "Econometrics is the application of statistical methods to economic data. It is a branch of economics that aims to give empirical content to economic relations. More precisely, it is \"the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inference.\" Econometrics can be described as something that allows economists \"to sift through mountains of data to extract simple relationships.\"",
"links": []
},
"y6xXsc-uSAmRDnNuyhqH2": {
"title": "Pre-requisites of Econometrics",
"description": "",
"links": [
{
"title": "10 Fundamental Theorems for Econometrics",
"url": "https://bookdown.org/ts_robinson1994/10EconometricTheorems/",
"type": "article"
}
]
},
"h19k9Fn5XPh3_pKEC8Ftp": {
"title": "Regression, Timeseries, Fitting Distributions",
"description": "",
"links": [
{
"title": "Blockchain.com Data Scientist TakeHome Test",
"url": "https://github.com/stalkermustang/bcdc_ds_takehome",
"type": "opensource"
},
{
"title": "10 Fundamental Theorems for Econometrics",
"url": "https://bookdown.org/ts_robinson1994/10EconometricTheorems/",
"type": "article"
},
{
"title": "Dougherty Intro to Econometrics 4th edition",
"url": "https://www.academia.edu/33062577/Dougherty_Intro_to_Econometrics_4th_ed_small",
"type": "article"
},
{
"title": "Econometrics: Methods and Applications",
"url": "https://imp.i384100.net/k0krYL",
"type": "article"
},
{
"title": "Kaggle - Learn Time Series",
"url": "https://www.kaggle.com/learn/time-series",
"type": "article"
},
{
"title": "Time series Basics : Exploring traditional TS",
"url": "https://www.kaggle.com/code/jagangupta/time-series-basics-exploring-traditional-ts#Hierarchical-time-series",
"type": "article"
},
{
"title": "How to Create an ARIMA Model for Time Series Forecasting in Python",
"url": "https://machinelearningmastery.com/arima-for-time-series-forecasting-with-python",
"type": "article"
},
{
"title": "11 Classical Time Series Forecasting Methods in Python",
"url": "https://machinelearningmastery.com/time-series-forecasting-methods-in-python-cheat-sheet/",
"type": "article"
},
{
"title": "Linear Regression for Business Statistics",
"url": "https://imp.i384100.net/9g97Ke",
"type": "article"
}
]
},
"XLDWuSt4tI4gnmqMFdpmy": {
"title": "Coding",
"description": "Programming is a fundamental skill for data scientists. You need to be able to write code to manipulate data, build models, and deploy solutions. The most common programming languages used in data science are Python and R. Python is a general-purpose programming language that is easy to learn and has a large number of libraries for data manipulation and machine learning. R is a programming language and free software environment for statistical computing and graphics. It is widely used for statistical analysis and data visualization.",
"links": []
},
"MVrAqizgkoAs2aghN8TgV": {
"title": "Learn Python Programming Language",
"description": "",
"links": [
{
"title": "Kaggle — Python",
"url": "https://www.kaggle.com/learn/python",
"type": "article"
},
{
"title": "Google's Python Class",
"url": "https://developers.google.com/edu/python",
"type": "article"
},
{
"title": "Explore top posts about Python",
"url": "https://app.daily.dev/tags/python?ref=roadmapsh",
"type": "article"
}
]
},
"StBCykpzpM4g9PRFeSNXa": {
"title": "Data Structures and Algorithms (Python)",
"description": "",
"links": [
{
"title": "Learn Algorithms",
"url": "https://leetcode.com/explore/learn/",
"type": "article"
},
{
"title": "Leetcode - Study Plans",
"url": "https://leetcode.com/studyplan/",
"type": "article"
},
{
"title": "Algorithms Specialization",
"url": "https://imp.i384100.net/5gqv4n",
"type": "article"
}
]
},
"Im0tXXn3GC-FUq2aMHgwm": {
"title": "Learn SQL",
"description": "",
"links": [
{
"title": "SQL Tutorial",
"url": "https://www.sqltutorial.org/",
"type": "article"
},
{
"title": "Explore top posts about SQL",
"url": "https://app.daily.dev/tags/sql?ref=roadmapsh",
"type": "article"
}
]
},
"l1027SBZxTHKzqWw98Ee-": {
"title": "Exploratory Data Analysis",
"description": "Exploratory Data Analysis (EDA) is an approach to analyzing data sets to summarize their main characteristics, often with visual methods. EDA is used to understand what the data can tell us beyond the formal modeling or hypothesis testing task. It is a crucial step in the data analysis process.",
"links": []
},
"JaN8YhMeN3whAe2TCXvw9": {
"title": "Data understanding, Data Analysis and Visualization",
"description": "",
"links": [
{
"title": "Exploratory Data Analysis With Python and Pandas",
"url": "https://imp.i384100.net/AWAv4R",
"type": "article"
},
{
"title": "Exploratory Data Analysis for Machine Learning",
"url": "https://imp.i384100.net/GmQMLE",
"type": "article"
},
{
"title": "Python for Data Visualization: Matplotlib & Seaborn",
"url": "https://imp.i384100.net/55xvzn",
"type": "article"
}
]
},
"kBdt_t2SvVsY3blfubWIz": {
"title": "Machine Learning",
"description": "Machine learning is a field of artificial intelligence that uses statistical techniques to give computer systems the ability to \"learn\" (e.g., progressively improve performance on a specific task) from data, without being explicitly programmed. The name machine learning was coined in 1959 by Arthur Samuel. Evolved from the study of pattern recognition and computational learning theory in artificial intelligence, machine learning explores the study and construction of algorithms that can learn from and make predictions on data such algorithms overcome following strictly static program instructions by making data-driven predictions or decisions, through building a model from sample inputs. Machine learning is employed in a range of computing tasks where designing and programming explicit algorithms with good performance is difficult or infeasible; example applications include email filtering, detection of network intruders, and computer vision.",
"links": []
},
"FdBih8tlGPPy97YWq463y": {
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