ant-nest 0.38.0

A simple and clear Web Crawler framework build on python3.6+ with async

Overview

AntNest is a simple, clear and fast Web Crawler framework build on python3.6+, powered by asyncio. It has only 600+ lines core code now(thanks powerful lib like aiohttp, lxml and other else).

Features

• Useful http client out of box

• Things(request, response and item) can though pipelines(in async or not)

• Item extractor, it`s easy to define and extract(by xpath, jpath or regex) one item we want from html, json or strings.

• Custom “ensure_future” and “as_completed” api provide a easy work flow

Install

pip install ant_nest

Usage

Create one demo project by cli:

>>> ant_nest -c examples

Then we have a project:

drwxr-xr-x   5 bruce  staff  160 Jun 30 18:24 ants
-rw-r--r--   1 bruce  staff  208 Jun 26 22:59 settings.py

Presume we want to get hot repos from github, let`s create “examples/ants/example2.py”:

from yarl import URL
from ant_nest.ant import Ant
from ant_nest.pipelines import ItemFieldReplacePipeline
from ant_nest.things import ItemExtractor


class GithubAnt(Ant):
    """Crawl trending repositories from github"""

    item_pipelines = [
        ItemFieldReplacePipeline(
            ("meta_content", "star", "fork"), excess_chars=("\r", "\n", "\t", "  ")
        )
    ]
    concurrent_limit = 1  # save the website`s and your bandwidth!

    def __init__(self):
        super().__init__()
        self.item_extractor = ItemExtractor(dict)
        self.item_extractor.add_extractor(
            "title", lambda x: x.html_element.xpath("//h1/strong/a/text()")[0]
        )
        self.item_extractor.add_extractor(
            "author", lambda x: x.html_element.xpath("//h1/span/a/text()")[0]
        )
        self.item_extractor.add_extractor(
            "meta_content",
            lambda x: "".join(
                x.html_element.xpath(
                    '//div[@class="repository-content "]/div[2]//text()'
                )
            ),
        )
        self.item_extractor.add_extractor(
            "star",
            lambda x: x.html_element.xpath(
                '//a[@class="social-count js-social-count"]/text()'
            )[0],
        )
        self.item_extractor.add_extractor(
            "fork",
            lambda x: x.html_element.xpath('//a[@class="social-count"]/text()')[0],
        )
        self.item_extractor.add_extractor("origin_url", lambda x: str(x.url))

    async def crawl_repo(self, url):
        """Crawl information from one repo"""
        response = await self.request(url)
        # extract item from response
        item = self.item_extractor.extract(response)
        item["origin_url"] = response.url

        await self.collect(item)  # let item go through pipelines(be cleaned)
        self.logger.info("*" * 70 + "I got one hot repo!\n" + str(item))

    async def run(self):
        """App entrance, our play ground"""
        response = await self.request("https://github.com/explore")
        for url in response.html_element.xpath(
            "/html/body/div[4]/main/div[2]/div/div[2]/div[1]/article/div/div[1]/h1/a[2]/"
            "@href"
        ):
            # crawl many repos with our coroutines pool
            self.schedule_task(self.crawl_repo(response.url.join(URL(url))))
        self.logger.info("Waiting...")

Then we can list all ants we defined (in “examples”)

>>> $ant_nest -l
ants.example2.GithubAnt

Run it! (without debug log):

>>> ant_nest -a ants.example2.GithubAnt
INFO:GithubAnt:Opening
INFO:GithubAnt:Waiting...
INFO:GithubAnt:**********************************************************************I got one hot repo!
{'title': 'NLP-progress', 'author': 'sebastianruder', 'meta_content': 'Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.', 'star': '3,743', 'fork': '327', 'origin_url': URL('https://github.com/sebastianruder/NLP-progress')}
INFO:GithubAnt:**********************************************************************I got one hot repo!
{'title': 'material-dashboard', 'author': 'creativetimofficial', 'meta_content': 'Material Dashboard - Open Source Bootstrap 4 Material Design Adminhttps://demos.creative-tim.com/materi…', 'star': '6,032', 'fork': '187', 'origin_url': URL('https://github.com/creativetimofficial/material-dashboard')}
INFO:GithubAnt:**********************************************************************I got one hot repo!
{'title': 'mkcert', 'author': 'FiloSottile', 'meta_content': "A simple zero-config tool to make locally-trusted development certificates with any names you'd like.", 'star': '2,311', 'fork': '60', 'origin_url': URL('https://github.com/FiloSottile/mkcert')}
INFO:GithubAnt:**********************************************************************I got one hot repo!
{'title': 'pure-bash-bible', 'author': 'dylanaraps', 'meta_content': '📖 A collection of pure bash alternatives to external processes.', 'star': '6,385', 'fork': '210', 'origin_url': URL('https://github.com/dylanaraps/pure-bash-bible')}
INFO:GithubAnt:**********************************************************************I got one hot repo!
{'title': 'flutter', 'author': 'flutter', 'meta_content': 'Flutter makes it easy and fast to build beautiful mobile apps.https://flutter.io', 'star': '30,579', 'fork': '1,337', 'origin_url': URL('https://github.com/flutter/flutter')}
INFO:GithubAnt:**********************************************************************I got one hot repo!
{'title': 'Java-Interview', 'author': 'crossoverJie', 'meta_content': '👨\u200d🎓 Java related : basic, concurrent, algorithm https://crossoverjie.top/categories/J…', 'star': '4,687', 'fork': '409', 'origin_url': URL('https://github.com/crossoverJie/Java-Interview')}
INFO:GithubAnt:Closed
INFO:GithubAnt:Get 7 Request in total
INFO:GithubAnt:Get 7 Response in total
INFO:GithubAnt:Get 6 dict in total
INFO:GithubAnt:Run GithubAnt in 18.157656 seconds

So, it`s easy to config ant by class attribute

class Ant(abc.ABC):
    response_pipelines: typing.List[Pipeline] = []
    request_pipelines: typing.List[Pipeline] = []
    item_pipelines: typing.List[Pipeline] = []
    request_cls = Request
    response_cls = Response
    request_timeout = 60
    request_retries = 3
    request_retry_delay = 5
    request_proxies: typing.List[typing.Union[str, URL]] = []
    request_max_redirects = 10
    request_allow_redirects = True
    response_in_stream = False
    connection_limit = 10  # see "TCPConnector" in "aiohttp"
    connection_limit_per_host = 0
    concurrent_limit = 100

And you can rewrite some config for one request

async def request(
    self,
    url: typing.Union[str, URL],
    method: str = aiohttp.hdrs.METH_GET,
    params: typing.Optional[dict] = None,
    headers: typing.Optional[dict] = None,
    cookies: typing.Optional[dict] = None,
    data: typing.Optional[
        typing.Union[typing.AnyStr, typing.Dict, typing.IO]
    ] = None,
    proxy: typing.Optional[typing.Union[str, URL]] = None,
    timeout: typing.Optional[float] = None,
    retries: typing.Optional[int] = None,
    response_in_stream: typing.Optional[bool] = None,
) -> Response:

About Item

We use dict to store one item in examples, actually it support many way to define our item: dict, normal class, atrrs`s class, data class and ORM class, it depend on your need and choice.

Examples

You can get some example in “./examples”

Defect

• Complex exception handle

one coroutine`s exception will break await chain especially in a loop, unless we handle it by hand. eg:

for cor in self.as_completed((self.crawl(url) for url in self.urls)):
    try:
        await cor
    except Exception:  # may raise many exception in a await chain
        pass

but we can use “self.as_completed_with_async” now, eg:

async fo result in self.as_completed_with_async(
self.crawl(url) for url in self.urls, raise_exception=False):
    # exception in "self.crawl(url)" will be passed and logged automatic
    self.handle(result)

• High memory usage

It`s a “feature” that asyncio eat large memory especially with high concurrent IO, we can set a concurrent limit(“connection_limit” or “concurrent_limit”) simply, but it`s complex to get the balance between performance and limit.

Coding style

Follow “Flake8”, Format by “Black”, typing check by “MyPy”, sea Makefile for more detail.

Todo

[*] Log system [*] Nest item extractor [ ] Docs