# yhangf/PythonCrawler: Python Scripts for Web Crawling Tasks

> yhangf/PythonCrawler is a collection of Python 3 crawler examples for image collection, search-result retrieval, job data, weather records, and selected website APIs. It is best treated as a learning repository, not as a maintained crawler framework or a general-purpose scraping platform.

**yhangf/PythonCrawler** —  :heartpulse:用python编写的爬虫项目集合

- Repository: https://github.com/yhangf/PythonCrawler
- Stars: 1,836 · Forks: 492
- Language: Python
- License: MIT
- Published: 2026-10-16 · Updated: 2026-10-16 · Language: en
- Canonical page: https://hysenlabs.com/projects/yhangf-pythoncrawler

## What PythonCrawler Covers

yhangf/PythonCrawler solves the practical problem of showing how several web-crawling tasks can be expressed in Python. It is aimed at learners who want to inspect scripts rather than adopt one unified application. The README describes the project as a collection of Python crawlers, and its repository layout separates standalone scripts under `spiderFile/` from API-oriented modules under `spiderAPI/`.

The collection covers several distinct data sources. Image examples target Baidu photography and artistic imagery, a Baidu Tieba topic, an entire website, a photography site, and the One arts site. Other scripts search Baidu Baike, retrieve recruitment information from Lagou, collect GitHub popular-language project information, obtain JD product IDs and tags, and scrape campus recruitment pages from a school website. `ECUT_get_grade.py` is a more sensitive example because it simulates login to a school website and calculates an average grade from retrieved results. Weather and traffic-related scripts address fixed or domain-specific datasets rather than general-purpose crawling.

That breadth makes the repository useful for comparing approaches. A caller looking for a scraper with one defined input and one defined output can find a relevant starting point. A team looking for a reusable crawler engine, scheduling system, distributed execution model, or shared configuration layer will find much less in the documented project description. The scripts appear to be examples collected in one repository rather than components of a documented framework.

## How the spiderFile Scripts Are Organized

The `spiderFile/` directory contains task-specific scripts. According to the README, `baidu_sy_img.py` targets Baidu's high-definition photography results, while `baidu_wm_img.py` targets the artistic-imagery category. `get_photos.py` collects images associated with a Baidu Tieba topic. These scripts are separate entry points, so the repository does not present them as one application with a unified command-line interface.

Some scripts address page-oriented data. `lagou_position_spider.py` accepts a keyword and saves related recruitment information locally. `ECUT_pos_html.py` collects campus recruitment information and writes HTML with embedded images. `get_history_weather.py` targets Guangzhou weather data for the first quarter of 2019, which makes it a fixed historical-data example rather than a general weather query service. `get_tf_accident_info.py` combines synchronous and asynchronous programming to collect accident information from the Tianjin Emergency Management Bureau.

Other entries automate browser interaction. `fuckCTF.py` uses Selenium to simulate login and change an original password. That behavior is documented as an educational example, but it is also a sensitive account operation and should not be copied into automation without reviewing authorization, site terms, and credential handling. `student_img.py` is described as automating access to a student's identification photo. The README does not document credentials, browser setup, retries, rate limits, storage formats for most scripts, or rollback procedures, so those details cannot be assumed from the repository summary.

## Using the spiderAPI Modules in Python

The `spiderAPI/` directory contains modules aimed at selected websites. The README explicitly describes the interfaces as incomplete and invites further modification. The Dianping example offers functions for restaurant rankings, merchant lists, and restaurant searches. Its documented sample imports the module, calls `bestRestaurant(cityId=1, rankType='popscore')`, calls `dpindex(cityId=1, page=1)`, and passes a restaurant URL to `restaurantList()`.

The repository also documents a proxy-IP module, a Baidu Maps module, a GitHub login wrapper, and a Lagou search function. These are separate APIs with different assumptions. The proxy module calls `get_enableips()`, while the GitHub class exposes `login()` and `show_timeline()`. The README says the GitHub login step prompts for a username and password. Because each module targets a different service, compatibility with a target service cannot be inferred from the existence of the Python function.

The documented Baidu Maps flow has a visible dependency between calls. The caller obtains a city list and uses a city code in the subsequent search. This is a small data-flow pattern, but it is not a generalized connector model. There is no documented session manager, shared error format, pagination abstraction, retry policy, or logging standard across these modules.

## A First Use with Baidu Maps and Lagou

The API examples are the clearest documented path to a first real use because they expose Python functions directly rather than requiring a separate command name. The Lagou example accepts a search key and page number and is described as retrieving recruitment information. This is a narrower operation than a full recruitment platform, and the README does not state whether results are returned, printed, or saved by the underlying function.

The Baidu Maps example provides a clearer two-stage data flow. First, `citys()` obtains the city list. Second, `search()` receives a keyword, city code, and page. That sequence suggests that the caller first resolves a location identifier and then performs a paginated search. The documented usage is:

```python
from spiderAPI.baidumap import *

citys=citys()#获取城市列表
result=search(keyword="美食", citycode="257", page=1)#获取搜索结果
```

The reader should see the import complete, a city-list result assigned to `citys`, and a search result assigned to `result`. The README does not identify the exact return types or describe error handling, so it is not possible to say what a successful result looks like. For a more direct recruitment example, the documented call is:

```python
from spiderAPI.lagou import *

lagou_spider(key='数据挖掘', page=1) # 获取关键字为数据挖掘的招聘信息
```

This code is suitable for inspecting the documented API shape, not for estimating volume, reliability, or compliance.

## Installation Evidence and Missing Setup Details

The README does not give a repository installation command, a supported Python version range, a `requirements.txt`, a `pyproject.toml` file, or a container recipe. The top-level entries are `LICENSE`, `README.md`, `spiderAPI/`, and `spiderFile/`, which indicates a source collection rather than a packaged distribution. The repository's topics include `python3`, `scripts`, and `spiders`, but a topic label is not an installation instruction.

A reader can use the documented examples after obtaining the repository and making the project directory available to Python, but the exact mechanism is not specified by the README. It would be inaccurate to add `pip install .`, a browser-driver command, or a particular dependency version as though the project documented them. The examples span Selenium, asynchronous programming, and multiple websites, so their environments may differ.

The documented login-oriented API offers another caution. The GitHub module is instantiated with `GitHub()`, and `login()` prompts for a username and password. The README does not explain whether credentials are stored, how the prompt is implemented, or how sessions are closed. `show_timeline()` then retrieves the GitHub home timeline. Users evaluating this module should inspect the source before entering real credentials because the documentation does not establish a safe credential-handling model.

## When PythonCrawler Is the Wrong Tool

The collection is a poor fit for a production service that needs predictable crawling behavior. Individual scripts are tied to named sites, categories, historical periods, or account workflows. A selector change, rate limit, authentication change, or altered page structure can break a script without giving the caller a documented recovery path. The repository does not state that it handles these cases.

It is also unsuitable as a foundation when the requirement is broad site coverage with consistent policy. The examples have different goals and output types, including local files, HTML, images, recruitment information, and API results. There is no documented common interface for retries, concurrency limits, storage schemas, observability, or test fixtures. Replacing those omissions requires building the surrounding system yourself.

The login and credential-related examples need particular care. The README lists `student_img.py`, `ECUT_get_grade.py`, and `fuckCTF.py`, including a Selenium-based password-change operation. The documentation does not provide authorization checks or safe test-account instructions. Those examples should be treated as code-reading material unless the operator has explicit permission to automate the relevant account and the target service permits it.

A web crawler framework is a real alternative when the requirement is a reusable architecture. Such a framework can provide a common crawler interface, scheduling, configuration, and extension points, although the README does not compare it with any specific framework. A small application-specific HTTP client is another alternative when only one endpoint is needed and the required response is narrow. The right choice depends on whether the goal is learning from concrete examples or operating a dependable multi-site service.

## Maintenance Scope, Licensing, and Adoption Cost

The repository is not archived, and its last push was on 2026-05-12. It has no GitHub releases. The README also displays an unfinished, intermittent-update label. Based on those maintenance facts, the project should not be described as having a regular release process or predictable compatibility track. The absence of releases means there is no documented versioned upgrade path for consumers who need stable interfaces.

The project is licensed under MIT. That license identifies the permission and notice framework for reuse, modification, and distribution, but this review does not provide legal advice. In practical terms, an adopter still needs to review the repository's license text and preserve the required notices when reusing code. The license does not grant permission to bypass site controls, access private accounts, or ignore a target service's terms.

The main trade-off is breadth versus coherence. The collection offers concrete examples for different crawling tasks, but the shared abstraction is weak. Each script may have its own input handling, output format, network behavior, and failure behavior. Compared with a maintained crawler framework, PythonCrawler offers examples rather than a documented scheduling, retry, proxy, storage, and observability layer. Compared with a small custom script, it supplies more ready-made starting points, but also brings unrelated code and site-specific assumptions. The repository's stated learning purpose makes that distinction appropriate, provided the adopter treats each entry point independently.

## Conclusion

Use yhangf/PythonCrawler when you need a small reference example for a specific Python crawling task or want to study how its scripts and API modules are organized. Do not adopt it as a production crawler without first checking the individual script, dependency availability, target-site terms, authentication handling, failure behavior, and whether the relevant site interface still works. Its MIT license permits reuse under the license conditions, while the repository's mixed examples and limited release history leave more upgrade work for the adopter.

## FAQ

### What is yhangf/PythonCrawler used for?

It is a collection of Python 3 crawler examples for tasks such as collecting images, retrieving recruitment information, querying Baike, reading GitHub-related information, processing weather data, and using selected website APIs.

### How do I use the Baidu Maps example in yhangf/PythonCrawler?

Import functions from `spiderAPI.baidumap`, call `citys()` to obtain a city list, then call `search()` with a keyword, city code, and page number. The README does not provide installation steps, dependency versions, or return-value details.

### Does yhangf/PythonCrawler include a requirements file or installation command?

The documented repository entries are `LICENSE`, `README.md`, `spiderAPI/`, and `spiderFile/`. The README does not document a `requirements.txt`, `pyproject.toml`, install command, or supported Python version range.

## Sources

- [Issues](https://github.com/yhangf/PythonCrawler/issues)
- [License: MIT](https://github.com/yhangf/PythonCrawler/blob/master/LICENSE)
- [README](https://github.com/yhangf/PythonCrawler/blob/master/README.md)
- [yhangf/PythonCrawler on GitHub](https://github.com/yhangf/PythonCrawler)

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Hysen Labs editorial analysis, written from the project's own repository and release notes. Cite the canonical page: https://hysenlabs.com/projects/yhangf-pythoncrawler