torequests 4.7.5

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 - v4.7.5](https://github.com/ClericPy/torequests)

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

*warn: v4.1.0 is not backwardly compatible with old version in about some args and function name.*

### To install:

> pip install torequests -U

**requirements:**

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

**optional:**

| jsonpath_rw_ext
| lxml
| objectpath
| psutil
| fuzzywuzzy
| python-Levenshtein
| pyperclip

### Features

Inspired by [tomorrow](https://github.com/madisonmay/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

```python
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

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

trequests = tPool()
test_url = 'http://p.3.cn'
ss = [
trequests.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]
trequests.x
ss = [i.cx for i in ss]
print_info(ss)

# [2018-03-18 21:18:09]: 612
# [2018-03-18 21:18:09]: 612
# [2018-03-18 21:18:09]: 612
# [2018-03-18 21:18:09]: [(612, None), (612, None), (612, None)]
```
> Test the performance, slower than gevent and aiohttp.
```python
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:
# ['ok 0', 'ok 1', 'ok 2', 'ok 3', 'ok 4']
# 5000 requests time cost:10.918817281723022 s
```

#### 3. Requests - aiohttp-wrapper

```python
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)

# [2018-03-19 00:57:36]: {'p.3.cn': Frequency(sem=<1/2>, interval=2)}
# [2018-03-19 00:57:36]: {'p.3.cn': Frequency(sem=<0/2>, interval=2)}
# [2018-03-19 00:57:38]: {'p.3.cn': Frequency(sem=<1/2>, interval=2)}
# [2018-03-19 00:57:38]: {'p.3.cn': Frequency(sem=<2/2>, interval=2)}
# [2018-03-19 00:57:38]: [(612, None), (612, None), (612, None), (612, None)]
```

> uvloop cost about 3.8s per 5000 requests; win32 5.78s per 5000 requests.
```python
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;
# ['ok 0', 'ok 1', 'ok 2', 'ok 3', 'ok 4']
# 5000 requests time cost:5.776089191436768 s
```

> mock server

```python
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.


### Documentation
> [Document & Usage](https://torequests.readthedocs.io/en/latest/)

### License
> [MIT license](LICENSE)

### Benchmarks
> to be continued......