torequests 4.8.15

Async wrapper for requests / aiohttp, and some python crawler toolkits. Let synchronization code enjoy the performance of asynchronous programming. Read more: https://github.com/ClericPy/torequests.

torequests v4.8.15

Briefly speaking, requests / aiohttp wrapper for asynchronous programming rookie, to shorten the code quantity.

To install:

pip install torequests -U

requirements:

| requests
| futures # python2
| aiohttp >= 3.0.5 # python3
| uvloop  # python3
| jsonpath_rw_ext
| lxml
| cssselect
| objectpath

optional:

| psutil
| fuzzywuzzy
| python-Levenshtein
| pyperclip

Features

Inspired by tomorrow, to make async-coding brief & smooth, compatible for win32 / python 2&3.

• convert any funtions into async-mode with concurrent.futures
• wrap requests module in future...
• simplify aiohttp, make it requests-like.
• some crawler toolkits.

Getting started

1. Async, threads - make functions asynchronous

from torequests import threads, Async
import time


@threads(5)
def test1(n):
    time.sleep(n)
    return 'test1 ok'


def test2(n):
    time.sleep(n)
    return 'test1 ok'


start = int(time.time())
# here async_test2 is same as test1
async_test2 = Async(test2)
future = test1(1)
# future run in non blocking thread pool
print(future, ', %s s passed' % (int(time.time() - start)))
# call future.x will block main thread and get the future.result()
print(future.x, ', %s s passed' % (int(time.time() - start)))
# output:
# <NewFuture at 0x34b1d30 state=running> , 0 s passed
# test1 ok , 1 s passed

2. tPool - thread pool for async-requests

from torequests.main import tPool
from torequests.logs import print_info

req = tPool()
test_url = 'http://p.3.cn'
ss = [
    req.get(
        test_url,
        retry=2,
        callback=lambda x: (len(x.content), print_info(len(x.content))))
    for i in range(3)
]
# or [i.x for i in ss]
req.x
ss = [i.cx for i in ss]
print_info(ss)

# [2019-04-01 00:19:07] temp_code.py(10): 612
# [2019-04-01 00:19:07] temp_code.py(10): 612
# [2019-04-01 00:19:07] temp_code.py(10): 612
# [2019-04-01 00:19:07] temp_code.py(16): [(612, None), (612, None), (612, None)]

2.1 Test the performance (win32+python3.7).

from torequests import tPool
import time

start_time = time.time()
trequests = tPool()
list1 = [
    trequests.get('http://127.0.0.1:5000/test/%s' % num) for num in range(5000)
]
# If failed, i.x may return False by default,
# or you can reset the fail_return arg.
list2 = [i.x.text if i.x else 'fail' for i in list1]
end_time = time.time()
print(list2[:5], '\n5000 requests time cost: %s s' % (end_time - start_time))
# output:
# ['test ok 0', 'test ok 1', 'test ok 2', 'test ok 3', 'test ok 4'] 
# 5000 requests time cost: 5.906721591949463 s

3. Requests - aiohttp-wrapper

from torequests.dummy import Requests
from torequests.logs import print_info
trequests = Requests(frequencies={'p.3.cn': (2, 2)})
ss = [
    trequests.get(
        'http://p.3.cn', retry=1, timeout=5,
        callback=lambda x: (len(x.content), print_info(trequests.frequencies)))
    for i in range(4)
]
trequests.x
ss = [i.cx for i in ss]
print_info(ss)

# [2019-04-01 00:16:35] temp_code.py(7): {'p.3.cn': Frequency(sem=<1/2>, interval=2)}
# [2019-04-01 00:16:35] temp_code.py(7): {'p.3.cn': Frequency(sem=<0/2>, interval=2)}
# [2019-04-01 00:16:37] temp_code.py(7): {'p.3.cn': Frequency(sem=<2/2>, interval=2)}
# [2019-04-01 00:16:37] temp_code.py(7): {'p.3.cn': Frequency(sem=<2/2>, interval=2)}
# [2019-04-01 00:16:37] temp_code.py(12): [<NewResponse [200]>, <NewResponse [200]>, <NewResponse [200]>, <NewResponse [200]>]

3.1 win32+python3.7 cost 3.9s per 5000 requests, which may be much faster with uvloop.

from torequests.dummy import Requests
import time

start_time = time.time()
trequests = Requests()
list1 = [
    trequests.get('http://127.0.0.1:5000/test/%s' % num) for num in range(5000)
]
# If failed, i.x may return False by default,
# or you can reset the fail_return arg.
list2 = [i.x.text if i.x else 'fail' for i in list1]
end_time = time.time()
print(list2[:5], '\n5000 requests time cost:%s s' % (end_time - start_time))
# output:
# win32, without uvloop;
# ['test ok 0', 'test ok 1', 'test ok 2', 'test ok 3', 'test ok 4'] 
# 5000 requests time cost:3.909820079803467 s

3.2 using torequests.dummy.Requests in async environment.

import asyncio

from responder import API
from torequests.dummy import Requests

loop = asyncio.get_event_loop()
api = API()


@api.route('/')
async def index(req, resp):
    # await for request or FailureException
    r = await api.req.get('http://p.3.cn', timeout=(1, 1))
    print(r)
    if r:
        # including good request with status_code between 200 and 299
        resp.text = 'ok' if 'Welcome to nginx!' in r.text else 'bad'
    else:
        resp.text = 'fail'


if __name__ == "__main__":
    api.req = Requests(loop=loop)
    api.run(port=5000, loop=loop)

3.3 mock server source code

from gevent.monkey import patch_all
patch_all()
import bottle
app = bottle.Bottle()
@app.get('/test/<num>')
def test(num):
    return 'ok %s' % num
app.run(server='gevent', port=5000)

4. utils: some useful crawler toolkits

ClipboardWatcher: watch your clipboard changing.
Counts: counter while every time being called.
Null: will return self when be called, and alway be False.
Regex: Regex Mapper for string -> regex -> object.
Saver: simple object persistent toolkit with pickle/json.
Timer: timing tool.
UA: some common User-Agents for crawler.
curlparse: translate curl-string into dict of request.
md5: str(obj) -> md5_string.
print_mem: show the proc-mem-cost with psutil, use this only for lazinesssss.
ptime: %Y-%m-%d %H:%M:%S -> timestamp.
ttime: timestamp -> %Y-%m-%d %H:%M:%S
slice_by_size: slice a sequence into chunks, return as a generation of chunks with size.
slice_into_pieces: slice a sequence into n pieces, return a generation of n pieces.
timeago: show the seconds as human-readable.
unique: unique one sequence.
find_one: use regex like Javascript to find one string with index(like [0], [1]).
...

Documentation

Document & Usage

License

MIT license

Benchmarks

to be continued......