torequests 4.8.19

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

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

Install:

pip install torequests -U

requirements

python2.7 / python3.6+

| requests
| futures # python2
| aiohttp >= 3.0.5 # python3
| uvloop  # python3

optional:

| jsonpath_rw_ext
| lxml
| cssselect
| objectpath
| 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 lib with concurrent.futures.
• simplify aiohttp, make it requests-like.
• add failure request class, add frequency control.
• plenty of crawler utils.

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 Performance.

[3.7.1 (v3.7.1:260ec2c36a, Oct 20 2018, 14:57:15) [MSC v.1915 64 bit (AMD64)]]: 2000 / 2000, 100.0%, cost 4.5911 seconds, 436.0 qps.
[2.7.15 (v2.7.15:ca079a3ea3, Apr 30 2018, 16:30:26) [MSC v.1500 64 bit (AMD64)]]: 2000 / 2000, 100%, cost 9.3587 seconds, 214.0 qps.

import timeit
from torequests import tPool
import sys

req = tPool()
start_time = timeit.default_timer()
oks = 0
total = 2000
# concurrent all the tasks
tasks = [req.get('http://127.0.0.1:9090') for num in range(total)]
for task in tasks:
    r = task.x
    if r.text == 'ok':
        oks += 1
end_time = timeit.default_timer()
succ_rate = oks * 100 / total
cost_time = round(end_time - start_time, 4)
version = sys.version
qps = round(total / cost_time, 0)
print(
    '[{version}]: {oks} / {total}, {succ_rate}%, cost {cost_time} seconds, {qps} qps.'
    .format(**vars()))

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 Performance.

aiohttp is almostly 3 times faster than requests + ThreadPoolExecutor, even without uvloop on windows10.

3.7.1 (v3.7.1:260ec2c36a, Oct 20 2018, 14:57:15) [MSC v.1915 64 bit (AMD64)]
sync_test: 2000 / 2000, 100.0%, cost 1.7625 seconds, 1135.0 qps.
async_test: 2000 / 2000, 100.0%, cost 1.7321 seconds, 1155.0 qps.

import asyncio
import sys
import timeit

from torequests.dummy import Requests


def sync_test():
    req = Requests()
    start_time = timeit.default_timer()
    oks = 0
    total = 2000
    # concurrent all the tasks
    tasks = [req.get('http://127.0.0.1:9090') for num in range(total)]
    for task in tasks:
        r = task.x
        if r.text == 'ok':
            oks += 1
    end_time = timeit.default_timer()
    succ_rate = oks * 100 / total
    cost_time = round(end_time - start_time, 4)
    qps = round(total / cost_time, 0)
    print(
        'sync_test: {oks} / {total}, {succ_rate}%, cost {cost_time} seconds, {qps} qps.'
        .format(**vars()))


async def async_test():
    req = Requests()
    start_time = timeit.default_timer()
    oks = 0
    total = 2000
    # concurrent all the tasks
    tasks = [req.get('http://127.0.0.1:9090') for num in range(total)]
    for task in tasks:
        r = await task
        if r.text == 'ok':
            oks += 1
    end_time = timeit.default_timer()
    succ_rate = oks * 100 / total
    cost_time = round(end_time - start_time, 4)
    qps = round(total / cost_time, 0)
    print(
        'async_test: {oks} / {total}, {succ_rate}%, cost {cost_time} seconds, {qps} qps.'
        .format(**vars()))


if __name__ == "__main__":
    print(sys.version)
    sync_test()
    loop = asyncio.get_event_loop()
    loop.run_until_complete(async_test())

3.2 using torequests.dummy.Requests in async environment.

ensure the loop is unique.

import asyncio

import uvicorn
from starlette.applications import Starlette
from starlette.responses import PlainTextResponse
from torequests.dummy import Requests

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


@api.route('/')
async def index(req):
    if not hasattr(api, 'req'):
        # or use `loop` arg to init Requests in globals
        api.req = Requests()
    # 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
        text = 'ok' if 'Welcome to nginx!' in r.text else 'bad'
    else:
        text = 'fail'
    return PlainTextResponse(text)

if __name__ == "__main__":
    uvicorn.run(api)

3.3 mock server source code

from starlette.applications import Starlette
from starlette.responses import PlainTextResponse

app = Starlette()


@app.route("/")
async def source_redirect(req):
    return PlainTextResponse('ok')


if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, port=9090)

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......