If you’re building scrapers—especially for platforms like Instagram—the “best” language depends on your target site, speed needs, and how you’ll scale. Here’s a concise guide to help you pick quickly (and a solid starter repo: https://github.com/Instagram-Automations/scraping-instagram).
Quick answer
Python for fastest prototyping and a huge scraping ecosystem.
Node.js (JavaScript) for modern, headless-browser automation and API-like flows.
Go for high-concurrency, low-memory crawlers at scale.
Java for enterprise-grade reliability and strong HTML/DOM tooling.
C#/.NET for Windows shops and robust, maintainable services.
Rust if you need max performance + safety (advanced teams).
For Instagram-focused workflows, see examples and patterns in the GitHub repo.
Python
Why it’s great
Rich libraries: requests, httpx, BeautifulSoup, lxml, Scrapy, Playwright, Selenium.
Fast to write, easy to debug, tons of tutorials.
Best for
Rapid POCs, data extraction pipelines, anti-bot experimentation (rotating proxies, headless browsers).
Tie-ins with data science notebooks.
Tip: Start from proven layouts in this repo for Instagram flows: scraping-instagram.
Node.js (JavaScript)
Why it’s great
First-class browser control: Puppeteer, Playwright.
Nonblocking I/O = good concurrency; easy to deploy as serverless functions.
Best for
Sites that need JS execution, login flows, and stealth browser automation.
Real-time workers and webhook-driven pipelines.
Hint: Map your Playwright steps to patterns shown in https://github.com/Instagram-Automations/scraping-instagram.
Go (Golang)
Why it’s great
Concurrency with goroutines; small static binaries.
Libraries: colly, rod, native HTTP with timeouts/retries.
Best for
High-throughput crawlers, microservices, and distributed scraping clusters.
Environments where memory and CPU efficiency matter.
Java
Why it’s great
Mature libraries: Jsoup, Selenium, Playwright for JVM.
Strong typing and stability for long-running jobs.
Best for
Enterprise teams, large codebases, compliance-heavy environments.
C#/.NET
Why it’s great
HtmlAgilityPack, AngleSharp, Playwright for .NET; great tooling on Windows.
Easy background services with Worker Service templates.
Best for
Windows/Azure ecosystems, teams standardized on .NET.
Rust (advanced)
Why it’s great
Performance + memory safety; great for parsers and custom fetchers.
Crates like reqwest, scraper, headless_chrome.
Best for
Ultra-fast, resource-tight crawlers and bespoke parsing at scale.
Choosing by scenario
I need results today: Python or Node.js.
Millions of pages, low cost: Go.
Strict reliability + big team: Java or C#.
Hardcore performance niche: Rust.
For Instagram scraping specifics (session handling, headless tactics, pacing, proxies), review patterns here: GitHub repo.
Must-have features regardless of language
Rotating proxies & backoff to reduce blocks.
Headless browser fallback when static HTML fails.
Session/cookie management for authenticated routes.
Structured output (NDJSON/Parquet) and retries with idempotency.
Observability (logs, metrics, alerting) for long runs.
You can adapt these building blocks from https://github.com/Instagram-Automations/scraping-instagram and plug them into your stack.
Next step: Explore the code, folder structure, and usage examples in the repo to kickstart your scraper: scraping-instagram on GitHub.
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