快速入门
This guide covers every Firecrawl feature:
- 入门 — Create a firecrawl account and set your api key
- How to Use Scrape — Pull llm ready data from single web pages
- How to Use Crawl — Crawl entire websites and follow every link
- 如何使用搜索功能 — Search the web for real time web data
- How to Use Map — Run url discovery across individual pages
- How to Use Extract — Extract structured data with natural language prompts
所需时间： 每部影片 5 分钟
本指南还包含以下内容： 专业提示 | 常见错误 | 故障排除 | 定价 | 替代方案
为什么信任本指南
I have used Firecrawl for over a year and tested every feature covered here.
This tutorial on how to use Firecrawl comes from real hands-on web scraping work.
Firecrawl is an ai powered web crawler that turns websites into clean, llm ready data.
But most users only scratch the surface of what this versatile tool can do.
This guide shows you how to use every major feature, step by step, with screenshots.
Firecrawl Tutorial
This complete Firecrawl tutorial walks you through every feature, from your first api key to advanced batch operations that make you a power user.
火行者
Turn any website into clean, structured data with a single api. Firecrawl handles javascript rendering, rate limits, and url discovery so you get llm ready data fast. Start on the free plan — no credit card needed.
Getting Started with Firecrawl
使用任何功能之前，请先完成此一次性设置。
大约需要3分钟。
请先观看这段简短的概述：
现在让我们一步一步来。
第一步：创建您的帐户
Go to the Firecrawl website at https://www.firecrawl.dev.
Click “Sign Up” to open a firecrawl account on the free plan.
请输入您的电子邮件地址并创建密码。
✓ 检查点： 检查你的 收件箱 请发送确认邮件。
Step 2: Install and Set Your API Key
Run pip install firecrawl-py to add the api service to your project.
Copy your api key, then save it as an environment variable for 安全.
这就是仪表盘的样子：
✓ 检查点： You should see the main dashboard with your usage and api key.
Step 3: Make Your First Call
Import the FirecrawlApp class and create a firecrawl instance with your key.
Every request hits the base endpoint at https://api.firecrawl.dev/v2.
✅ 完成： You’re ready to scrape, crawl, search, map, and extract data.
How to Use Firecrawl Scraper
Scrape lets you pull clean, llm ready data from a single page with one single api call.
Scrape mode targets individual pages and is ideal for extracting specific details fast.
以下是使用步骤。
现在让我们逐一分析每个步骤。
步骤 1：获取您的 API 密钥
Create a firecrawl account, then copy your api key from the dashboard.
Store it as an environment variable so your api key stays out of your raw code.
Step 2: Call the Scrape Endpoint
Pass a single url to the .scrape_url() method on your firecrawl instance.
You can request markdown format, raw html, or structured json as the output.
这就是它的样子：
✓ 检查点： You should see clean markdown for the current page, ready for ai applications.
Step 3: Read the Clean Output
Firecrawl returns clean data with readable 文本, stripped of junk html tags.
✅ 结果： You turned one of the web pages into structured web data with a single api.
💡 专业提示： Set the max_age parameter to cache results and skip re-scraping a page that has not changed.
How to Use Firecrawl Crawler
Crawl lets you crawl entire websites and follow links automatically without a sitemap.
Crawl mode lets you crawl websites across multiple pages and collect every reachable page.
以下是使用步骤。
现在让我们逐一分析每个步骤。
Step 1: Point at a Root URL
Give the crawl endpoint a starting url such as https://example.com.
Firecrawl handles web crawling through links and follows pages on its own.
Step 2: Start the Crawl Job
Launch the crawl job and grab the returned job id to track progress.
Use the job id to poll status and pull crawled data as each page finishes.
这就是它的样子：
✓ 检查点： You should see scraped pages from across the site building into web data.
步骤 3：导出结果
Collect every page as markdown or structured json for your data pipelines.
✅ 结果： You captured an entire site, even complex websites with dynamic content.
💡 专业提示： Firecrawl uses batch processing and concurrent browsers, so large crawl operations stay fast.
How to Use Firecrawl Search Engine
搜索 lets you search the web and return clean results you can feed straight into ai agents.
Search lets you query the web and pull back real time web data as readable text.
以下是使用步骤。
现在让我们逐一分析每个步骤。
Step 1: Send a Query
Call the search endpoint with a plain natural language query.
Firecrawl can search the web across news websites, job boards, and review sites.
步骤 2：选择输出格式
Ask for markdown format or structured json for each result.
Every result arrives as clean data, not noisy raw html.
这就是它的样子：
✓ 检查点： You should see ranked web pages returned as structured web data.
Step 3: Pipe Into Your App
Feed the structured data into 人工智能助手 or ai workflows.
✅ 结果： You added live web content to your ai applications in a single api call.
💡 专业提示： Pair search with extract to gather news articles for market research or competitive intelligence.
How to Use Firecrawl Advanced Map
Map lets you run url discovery and turn one domain into a full map of individual pages.
Map mode retrieves every url on a site quickly for fast url discovery.
以下是使用步骤。
现在让我们逐一分析每个步骤。
Step 1: Submit the Domain
Pass a single root url to the map endpoint.
Firecrawl returns every link without needing a sitemap.
Step 2: Review the URL List
Scan the returned individual pages before you scrape them.
Save the list to a csv file to plan your data extraction.
这就是它的样子：
✓ 检查点： You should see a full sitemap of web pages from one single url.
Step 3: Select What to Scrape
Pick the pages you want, then send them to scrape or crawl.
✅ 结果： You mapped the whole site, ready for targeted web scraping.
💡 专业提示： Map first on dynamic websites and web apps to avoid wasting credits on pages you do not need.
How to Use Firecrawl Extractor
提炼 lets you extract structured data from any page using natural language prompts.
Extract uses ai powered parsing to pull exactly the fields you describe.
以下是使用步骤。
现在让我们逐一分析每个步骤。
Step 1: Define a Schema
Write a Pydantic model with: from pydantic import BaseModel.
Schema based extraction tells Firecrawl which fields to return as structured json.
Step 2: Describe the Data
Add natural language prompts for fields a schema cannot capture.
This is how you extract data from web pages without writing parsing rules.
这就是它的样子：
✓ 检查点： You should see tidy structured data instead of messy html tags.
Step 3: Receive Structured JSON
Firecrawl returns clean structured json ready for training data.
✅ 结果： You replaced fragile scrapers with one extract call and less data cleaning.
💡 专业提示： Use only_main_content, include_tags, and exclude_tags to keep the extracted web data focused.
Firecrawl Pro Tips and Shortcuts
After testing Firecrawl for over a year, here are my best tips for cleaner data extraction.
键盘快捷键
| 行动 | 捷径 |
|---|---|
| Run scrape in playground | Ctrl + Enter |
| Copy api key | Ctrl + C |
| Open docs | Ctrl + K |
| Switch output format | 标签页 |
大多数人错过的隐藏功能
- max_age caching: Reuse recent crawled data for faster, cheaper repeat scraping.
- Browser actions: Click, scroll, and type to reach content behind javascript rendering.
- Async batching: Process thousands of urls with batch processing without blocking your web apps.
Firecrawl Common Mistakes to Avoid
Mistake #1: Hardcoding your API key
❌ 错误： Pasting your api key directly into shared code or a public repo.
✅ 右图： Load the key from an environment variable so it stays private.
Mistake #2: Crawling before mapping
❌ 错误： Crawling entire websites blindly and burning credits on junk pages.
✅ 右图： Run url discovery with map first, then crawl only the pages you need.
Mistake #3: Parsing raw html yourself
❌ 错误： Writing brittle rules to clean raw html and strip html tags by hand.
✅ 右图： Use schema based extraction to get clean structured json directly.
Firecrawl Troubleshooting
Problem: 401 unauthorized errors
原因： Your api key is missing or not loaded from the environment variable.
使固定： Re-export the key, then recreate your firecrawl instance and retry.
Problem: Timeout errors on complex websites
原因： Heavy javascript rendering or dynamic content takes longer to load.
使固定： Add a wait action so the current page finishes loading before capture.
Problem: Hitting rate limits
原因： Too many requests at once on the free plan or a lower tier.
使固定： Slow batch operations or upgrade for more concurrent browsers.
📌 笔记： If none of these fix your issue, contact Firecrawl support.
什么是 Firecrawl？
火行者 is an ai powered web scraping tool that turns websites into clean, structured data.
Think of it as a web crawler that hands ai agents readable text instead of messy raw html.
Firecrawl was developed by Mendable.ai to reduce token waste for ai applications.
观看这段快速概览：
它包含以下主要特点：
- 刮： Extract data from single web pages as markdown format or structured json.
- 爬行： Crawl entire websites and follow links without a sitemap.
- 搜索： Search the web and return clean data from news websites and review sites.
- 地图： Fast url discovery that turns one domain into a full sitemap.
- Extract: Pull structured web data using natural language prompts and Pydantic schemas.
Firecrawl beats traditional web scraping by handling proxies, rate limits, and javascript rendering for you.
Unlike traditional tools that need Selenium, it serves data scientists and developers through one api service.
如需完整评测，请参阅我们的 Firecrawl review.
火爬行定价
Here’s what Firecrawl costs in 2026:
| 计划 | 价格 | 最适合 |
|---|---|---|
| 自由的 | 自由的 | Testing scrape and crawl on a few pages |
| 爱好 | 每月16美元 | Solo developers and small data pipelines |
| 标准 | 每月 83 美元 | Teams running regular web crawling jobs |
| 生长 | 每月 333 美元 | High-volume market research and monitoring |
免费试用： Yes — the free plan lets you scrape a limited number of pages.
退款保证： No formal guarantee, but you can downgrade anytime.
💰 性价比最高： Standard — best balance of credits and concurrent browsers for most teams.
Firecrawl 与其他方案的比较
How does Firecrawl compare? Here’s the competitive landscape:
| 工具 | 最适合 | 价格 | 等级 |
|---|---|---|---|
| 火行者 | AI-ready clean data | 每月16美元 | ⭐ 3.5 |
| Apify | Prebuilt actors | 每月 49 美元 | ⭐ 4.5 |
| 明亮数据 | Proxy scale | $ Custom | ⭐ 4.6 |
| Crawl4AI | 开源 | 自由的 | ⭐ 4.4 |
| Scrapy | Python control | 自由的 | ⭐ 4.5 |
| ScrapeGraphAI | LLM graph scraping | 每月 20 美元 | ⭐ 4.3 |
快速精选：
- 综合最佳： Firecrawl — cleanest llm ready data from a single api.
- 最佳预算： Crawl4AI — free and open source for hands-on data scientists.
- 最适合初学者： Firecrawl — natural language prompts hide the hard parts.
- Best for proxy scale: Bright Data — huge proxy pool for complex websites.
🎯 Firecrawl Alternatives
正在寻找 Firecrawl 的替代方案？以下是一些最佳选择：
- 🚀 Apify： Marketplace of prebuilt actors for web scraping, good when you want ready-made scrapers over a single api.
- 🏢 亮数据： Enterprise proxy network for huge crawl jobs and content monitoring at scale across dynamic websites.
- 💰 Crawl4AI： Free, open source crawler that outputs llm ready data, ideal for budget ai workflows and local runs.
- 🔧 Scrapy： Battle-tested Python framework giving developers full control over crawling, parsing, and data pipelines.
- 🧠 ScrapeGraphAI： Graph-based, ai powered extraction that maps page structure for schema based extraction of structured data.
完整列表请参见我们的 Firecrawl alternatives 指导。
⚔️ Firecrawl 对比
以下是Firecrawl与各竞争对手的对比：
- Firecrawl 对阵 Apify： Firecrawl wins on clean, llm ready output; Apify wins on its library of prebuilt scrapers.
- Firecrawl 对阵 Bright Data： Bright Data wins on proxy scale; Firecrawl wins on simpler structured data extraction.
- Firecrawl 对阵 Crawl4AI： Crawl4AI wins on price and self-hosting; Firecrawl wins on managed rate limits and reliability.
- Firecrawl 对阵 Scrapy： Scrapy wins on low-level control; Firecrawl wins on speed and zero proxy setup.
- Firecrawl 对比 ScrapeGraphAI： Both are ai powered; Firecrawl wins on crawl coverage, ScrapeGraphAI on graph logic.
Start Using Firecrawl Now
You learned how to use every major Firecrawl feature:
- ✅ Scrape
- ✅ Crawl
- ✅ 搜索
- ✅ Map
- ✅ Extract
下一步： 选择一项功能，立即试用。
Most people start with Scrape.
只需不到5分钟。
常见问题解答
Firecrawl是用来做什么的？
Firecrawl is an ai powered web scraping tool. It turns web pages into clean, llm ready data for ai agents, rag systems, market research, and price monitoring.
Firecrawl可以免费使用吗？
Yes. The free plan lets you scrape a limited number of pages with your api key, so you can test scrape, crawl, and extract before paying.
How do I install Firecrawl?
Run pip install firecrawl-py, then set your api key as an environment variable and create a firecrawl instance to start your first single api call.
How is Firecrawl different from traditional scraping?
Traditional web scraping needs Selenium and manual proxy setup. Firecrawl handles javascript rendering, rate limits, and clean data automatically through one api service.
Can Firecrawl extract structured data?
Yes. Use natural language prompts or a Pydantic schema for schema based extraction, and Firecrawl returns structured json instead of raw html.
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