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).
- 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
pip install ant_nest
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:
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.
You can get some example in "./examples"
- 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.
Follow "Flake8", Format by "Black", typing check by "MyPy", sea Makefile for more detail.
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