Concurrent requests control how many downloads Scrapy runs in parallel, which directly affects crawl speed, resource usage, and how much load gets placed on target sites. Concurrency tuning is a direct way to trade throughput for politeness and stability during crawls.
Scrapy uses an asynchronous downloader (via Twisted) and keeps multiple requests in flight at the same time. The CONCURRENT_REQUESTS setting caps total in-progress requests across the crawler, while CONCURRENT_REQUESTS_PER_DOMAIN limits parallelism per hostname to prevent a single site from consuming all downloader slots. The CONCURRENT_REQUESTS_PER_IP setting can cap parallelism by IP address instead, and overrides the per-domain limit when non-zero.
High concurrency can trigger throttling, temporary blocks, and more retries or timeouts when the remote side cannot keep up. Concurrency settings are typically tuned alongside DOWNLOAD_DELAY or AutoThrottle to keep the crawl responsive and reduce 429 responses.
Related: How to set a download delay in Scrapy
Related: How to enable AutoThrottle in Scrapy
Steps to set concurrent requests in Scrapy:
- Open the Scrapy project settings file.
$ vi simplifiedguide/settings.py
- Set global and per-domain concurrency limits in settings.py.
CONCURRENT_REQUESTS = 8 CONCURRENT_REQUESTS_PER_DOMAIN = 4
Excessive concurrency can cause throttling, increased retry rates, or IP blocks from target sites.
- Print the effective concurrency values from the project.
$ scrapy settings --get CONCURRENT_REQUESTS 8 $ scrapy settings --get CONCURRENT_REQUESTS_PER_DOMAIN 4
- Run a spider with the updated settings.
$ scrapy crawl products 2026-01-01 08:22:14 [scrapy.crawler] INFO: Overridden settings: {'BOT_NAME': 'simplifiedguide', 'CONCURRENT_REQUESTS': 8, 'CONCURRENT_REQUESTS_PER_DOMAIN': 4, 'NEWSPIDER_MODULE': 'simplifiedguide.spiders', 'SPIDER_MODULES': ['simplifiedguide.spiders']} ##### snipped #####
Mohd Shakir Zakaria is a cloud architect with deep roots in software development and open-source advocacy. Certified in AWS, Red Hat, VMware, ITIL, and Linux, he specializes in designing and managing robust cloud and on-premises infrastructures.
