Python HTTP Server on new websites

Python standard-library BaseHTTP development web server.

#19 of 140 in Server First seen: Jun 13, 2026 Last seen: Oct 16, 2026 Most recent launch: NETLEKSSS — интернет с вашим северным проводником, Oct 15, 2026 Website: docs.python.org

364 sites

359 found by StackScope, 5 via launch platforms

StackScope Wider Web 289 StackScope Discovery (Indie) 70 Product Hunt 2 Other 2 Hacker News 1
  • StackScope Wider Web 289
  • StackScope Discovery (Indie) 70
  • Product Hunt 2
  • Other 2
  • Hacker News 1

Python HTTP Server appeared on about 180 new sites in the last 30 days.

These figures cover websites that went live since April 2026, not the web as a whole.

Runs on
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182 new sites with Python HTTP Server first seen in the last 30 days.

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Share of new sites using Python HTTP Server

Each dot is one launch day. Line is the 7-day rolling average; weekly averages before July 2026. Chart starts at first detection.

0.0%
last 7 days
+0.0pp vs prior week
0.0%
30 days to Oct 16
+0.0pp vs 30 days before
364
sites all time
since Jun 2026
Python HTTP Server daily detection trend Before 8 July 2026: launch platforms only. We began crawling the wider web on this date, so the cohort this share is measured against changes here. 10 September 2026: we improved our infrastructure to index new sites much sooner, often on the day they go live, so the cohort this share is measured against changes here. 5% 2% 0% Jun Jul Aug Sep Oct Weekly averages before this point, daily after. Jul 19 · 1 / 27738 = 0.0% Jul 20 · 2 / 24053 = 0.0% Jul 21 · 1 / 22956 = 0.0% Jul 22 · 1 / 24375 = 0.0% Jul 23 · 1 / 18111 = 0.0% Jul 24 · 0 / 13984 = 0.0% Jul 25 · 1 / 9559 = 0.0% Jul 26 · 0 / 21760 = 0.0% Jul 27 · 2 / 37243 = 0.0% Jul 28 · 2 / 41893 = 0.0% Jul 29 · 1 / 53574 = 0.0% Jul 30 · 1 / 48278 = 0.0% Jul 31 · 2 / 56049 = 0.0% Aug 1 · 3 / 54898 = 0.0% Aug 2 · 1 / 53857 = 0.0% Aug 3 · 2 / 52620 = 0.0% Aug 4 · 2 / 40708 = 0.0% Aug 5 · 1 / 35352 = 0.0% Aug 6 · 2 / 39150 = 0.0% Aug 7 · 2 / 40251 = 0.0% Aug 8 · 2 / 42807 = 0.0% Aug 9 · 5 / 37786 = 0.0% Aug 10 · 0 / 32326 = 0.0% Aug 11 · 1 / 34562 = 0.0% Aug 12 · 2 / 37141 = 0.0% Aug 13 · 2 / 55477 = 0.0% Aug 14 · 2 / 56760 = 0.0% Aug 15 · 2 / 55912 = 0.0% Aug 16 · 2 / 56272 = 0.0% Aug 17 · 0 / 46231 = 0.0% Aug 18 · 2 / 57231 = 0.0% Aug 19 · 1 / 51782 = 0.0% Aug 20 · 4 / 69069 = 0.0% Aug 21 · 5 / 93894 = 0.0% Aug 22 · 4 / 94209 = 0.0% Aug 23 · 2 / 93619 = 0.0% Aug 24 · 2 / 81725 = 0.0% Aug 25 · 4 / 71550 = 0.0% Aug 26 · 4 / 66870 = 0.0% Aug 27 · 3 / 87846 = 0.0% Aug 28 · 4 / 87921 = 0.0% Aug 29 · 7 / 88078 = 0.0% Aug 30 · 3 / 100677 = 0.0% Aug 31 · 5 / 100259 = 0.0% Sep 1 · 3 / 103472 = 0.0% Sep 2 · 4 / 108918 = 0.0% Sep 3 · 6 / 103287 = 0.0% Sep 4 · 8 / 98545 = 0.0% Sep 5 · 3 / 102863 = 0.0% Sep 6 · 2 / 89278 = 0.0% Sep 7 · 6 / 86118 = 0.0% Sep 8 · 4 / 77974 = 0.0% Sep 9 · 4 / 75530 = 0.0% Sep 10 · 4 / 83704 = 0.0% Sep 11 · 3 / 85579 = 0.0% Sep 12 · 3 / 56773 = 0.0% Sep 13 · 10 / 57998 = 0.0% Sep 14 · 4 / 59235 = 0.0% Sep 15 · 2 / 58191 = 0.0% Sep 16 · 5 / 59080 = 0.0% Sep 17 · 6 / 56816 = 0.0% Sep 18 · 2 / 53087 = 0.0% Sep 19 · 2 / 45278 = 0.0% Sep 20 · 7 / 44764 = 0.0% Sep 21 · 5 / 51672 = 0.0% Sep 22 · 8 / 55411 = 0.0% Sep 23 · 5 / 58320 = 0.0% Sep 24 · 5 / 53474 = 0.0% Sep 25 · 2 / 50770 = 0.0% Sep 26 · 12 / 101523 = 0.0% Sep 27 · 4 / 52140 = 0.0% Sep 28 · 9 / 61128 = 0.0% Sep 29 · 2 / 77868 = 0.0% Sep 30 · 2 / 69725 = 0.0% Oct 1 · 2 / 69255 = 0.0% Oct 2 · 5 / 64812 = 0.0% Oct 3 · 3 / 53800 = 0.0% Oct 4 · 6 / 52066 = 0.0% Oct 5 · 5 / 63716 = 0.0% Oct 6 · 7 / 67612 = 0.0% Oct 7 · 3 / 67696 = 0.0% Oct 8 · 9 / 69360 = 0.0% Oct 9 · 7 / 70445 = 0.0% Oct 10 · 4 / 60708 = 0.0% Oct 11 · 3 / 65616 = 0.0% Oct 12 · 5 / 66683 = 0.0% Oct 13 · 5 / 71096 = 0.0% Oct 14 · 34 / 70819 = 0.0% Oct 15 · 11 / 93940 = 0.0% Oct 16 · 2 / 67022 = 0.0%
May 18, 2026 90 days Oct 16, 2026

The shaded areas were measured against a different set of sites, so the line can step there without Python HTTP Server itself changing.

Coverage details

Before the dashed line where the dots begin, the line is a weekly average. After it, the last 90 days are shown one day at a time.

Grey: before 8 July 2026, we only tracked launches from launch platforms. From that date we crawl the wider web as well.

Amber: 8 July to 10 September 2026, before we improved our infrastructure to index new sites much sooner, often on the day they go live. Sites found that early often haven't finished setting up, so anything usually added after launch reads lower from 10 September. We record each site as it was when we found it.

The share is a proportion of whatever we were tracking at the time. For a single continuous measure, switch to launch platforms.

How StackScope detects technologies

What kind of sites use Python HTTP Server

96 sites with a known type, all time

Finance
14.6%
Games
13.5%
Productivity
10.4%
AI
9.4%
Content
6.3%
Crypto
6.3%
Education
6.3%
Marketing
6.3%
Social
5.2%
Health
4.2%
E-commerce
3.1%
Design
1.0%

Domain endings using Python HTTP Server

364 sites, all time

  • .com 40.7%
  • .net 12.1%
  • .online 8.2%
  • .xyz 5.0%
  • .app 3.9%
  • .fr 3.9%
  • .site 3.6%
  • .tech 3.6%
  • .org 2.5%
  • .ai 2.2%
  • .cloud 1.9%
  • .uk 1.4%
  • .co 1.1%
  • .dev 1.1%

Country

Country likely for 35 of 364 sites (9.6%), all time.

How we know

Country comes from what each site says about itself, such as a company registration, legal terms or a phone number, not just its domain ending. Too few sites state their country plainly for the usual count, so this one also counts single signals: a country domain ending, a phone number (for North America, its area code), a location the site declares in its own page metadata, or a country-specific vendor stack and the page language where they agree and nothing contradicts them. Read these as likely rather than certain.

  • France France 37.1%
  • United Kingdom United Kingdom 14.3%
  • Brazil Brazil 11.4%
  • India India 5.7%
  • South Korea South Korea 5.7%
  • United States United States 5.7%
  • Vietnam Vietnam 5.7%
  • Australia Australia 2.9%
  • Belgium Belgium 2.9%
  • Germany Germany 2.9%
  • Mexico Mexico 2.9%
  • Sweden Sweden 2.9%

Server leaders

Tool % of sitesall time % of categoryall time
#1 – nginx 9.6% 37.4%
#2 – LiteSpeed Web Server 6.7% 26.0%
#3 – Apache 4.7% 18.3%
#4 – Caddy 3.0% 11.6%
#5 – OpenResty 0.9% 3.5%
…
#19 ▲4 Python HTTP Server Current page <0.1% <0.1%

Percentages show all-time adoption across the new sites we track: the share of all of them, and of the sites using any Server tool.Among September launches it ranked #18 in Server, up from #22 in August. All 140 in Server →

Often used with

Tool Sites vs all new sites
Caddy 274 25x
AWS Route 53 43 12x

Tools that turn up far more often on Python HTTP Server sites than on new sites in general, and how many times as common each one is there.

Something not look right? If a technology shown here is wrong or out of date, email [email protected] and we'll review it.