eternal-flame-ad/mafengwo — explained in plain English
Analysis updated 2026-07-19 · repo last pushed 2018-07-17
Collect a large dataset of travel routes from Mafengwo user profiles for analysis.
Identify which cities are most frequently visited together to inform a trip-planning app.
Study domestic travel patterns in China using raw user itinerary data.
Discover trending travel destinations based on real user footprints.
| eternal-flame-ad/mafengwo | alibaba/omnidoc-tokenbench | arccalc/dwmfix | |
|---|---|---|---|
| Stars | 43 | 43 | 43 |
| Language | Python | Python | Python |
| Last pushed | 2018-07-17 | — | — |
| Maintenance | Dormant | — | — |
| Setup difficulty | easy | moderate | easy |
| Complexity | 2/5 | 3/5 | 2/5 |
| Audience | developer | researcher | general |
Figures from each repo's GitHub metadata at analysis time.
Install Python dependencies and run a single Scrapy command, the target site uses plain HTTP so no special configuration is needed.
This project is a tool for collecting travel itinerary data from Mafengwo, a popular Chinese travel website where users share their trip routes and footprints. In plain terms, it lets you automatically gather records of where people have traveled, pulling down a large dataset of user travel paths. The tool works by systematically browsing Mafengwo's public pages and extracting travel route information from each user profile it visits. It uses Scrapy, a well-known Python library designed specifically for this kind of web data collection. The README notes that the core logic is surprisingly compact, under 50 lines of code. To run it, you install the required dependencies, then execute a single command that tells the tool to start collecting data and save the results into a JSON file. The author mentions successfully scraping 250,000 user travel records in a single day. Someone building a travel-related product could use this dataset to understand popular destinations, identify trending routes, or analyze where certain types of travelers tend to go. For example, a founder creating a trip-planning app might want to know which cities are most frequently visited together, or a researcher studying domestic travel patterns in China could use the raw data as a starting point. The project is straightforward about its limitations and ethics. The author notes that Mafengwo still uses unencrypted HTTP, which makes the data easier to access, but they deliberately built in a small delay of 0.1 seconds between requests to avoid overwhelming the site's servers. Beyond that, the README doesn't go into further detail about data format, filtering options, or error handling, so you'd likely need to look at the code itself to understand exactly what fields are captured and how the output is structured.
A Python tool that automatically collects travel itinerary data from Mafengwo, a Chinese travel website. It uses Scrapy to browse public user profiles and extract travel route records into a JSON file.
Mainly Python. The stack also includes Python, Scrapy.
Dormant — no commits in 2+ years (last push 2018-07-17).
The explanation does not mention a license, so the terms of use are unclear.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.