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在使用 selenium 的時(shí)候記得在最后加上:

driver.quit()

現(xiàn)在你這個(gè)情況可以嘗試用kill命令把在后臺運(yùn)行的 chrome 強(qiáng)制結(jié)束看能不能降低內(nèi)存.

$ kill 6364

def 兩個(gè)變量就可以了

settings.py里的STATICFILES_DIR不應(yīng)該是STATICFILES_DIRS嗎?

C1是shape=(1, )的一維constant
C2是shape=(1, 1)的二維constant

個(gè)人覺得virtuanenv是一個(gè)不錯(cuò)的方式，在需要python3的時(shí)候，使用需要的virtualenv，pip也是當(dāng)前virtualenv的pip，只需要一句source <current_env>/bin/active 就可以切換環(huán)境。

簡單來說是有特別的標(biāo)志位。Wiki上是這么說的：

In IEEE 754 standard-conforming floating-point storage formats, NaNs are identified by specific, pre-defined bit patterns unique to NaNs. The sign bit does not matter. Binary format NaNs are represented with the exponential field filled with ones (like infinity values), and some non-zero number in the significand field (to make them distinct from infinity values). The original IEEE 754 standard from 1985 (IEEE 754-1985) only described binary floating-point formats, and did not specify how the signaling/quiet state was to be tagged. In practice, the most significant bit of the significand field determined whether a NaN is signaling or quiet. Two different implementations, with reversed meanings, resulted:
most processors (including those of the Intel and AMD's x86 family, the Motorola 68000 family, the AIM PowerPC family, the ARM family, the Sun SPARC family, and optionally new MIPS processors) set the signaling/quiet bit to non-zero if the NaN is quiet, and to zero if the NaN is signaling. Thus, on these processors, the bit represents an 'is_quiet' flag;
in NaNs generated by the PA-RISC and old MIPS processors, the signaling/quiet bit is zero if the NaN is quiet, and non-zero if the NaN is signaling. Thus, on these processors, the bit represents an 'is_signaling' flag.
The former choice has been preferred as it allows the implementation to quiet a signaling NaN by just setting the signaling/quiet bit to 1. The reverse is not possible with the latter choice because setting the signaling/quiet bit to 0 could yield an infinity.
The 2008 revision of the IEEE 754 standard (IEEE 754-2008) makes formal recommendations for the encoding of the signaling/quiet state.
For binary formats, the most significant bit of the significand field should be an 'is_quiet' flag. I.e. this bit is non-zero if the NaN is quiet, and zero if the NaN is signaling.
For decimal formats, whether binary or decimal encoded, a NaN is identified by having the top five bits of the combination field after the sign bit set to ones. The sixth bit of the field is the 'is_quiet' flag. The standard follows the interpretation as an 'is_signaling' flag. I.e. the signaling/quiet bit is zero if the NaN is quiet, and non-zero if the NaN is signaling. A signaling NaN is quieted by clearing this sixth bit.
For IEEE 754-2008 conformance, the meaning of the signaling/quiet bit in recent MIPS processors is now configurable via the NAN2008 field of the FCSR register. This support is optional in MIPS Release 3 and required in Release 5.[10]
The state/value of the remaining bits of the significand field are not defined by the standard. This value is called the 'payload' of the NaN. If an operation has a single NaN input and propagates it to the output, the result NaN's payload should be that of the input NaN (this is not always possible for binary formats when the signaling/quiet state is encoded by an 'is_signaling' flag, as explained above). If there are multiple NaN inputs, the result NaN's payload should be from one of the input NaNs; the standard does not specify which.

ipython啊
pycharm啊
ipython的help命令， python自帶的dir等等

python的對象根本隱藏不了任何東西。

'input[type="file"]'， 這種用selenium直接sendKeys文件路徑 直接上傳 應(yīng)該可以吧，不用操作Windows控件了。

另外系統(tǒng)彈出框 selenium是無法操作的，可以用autoit試試 。沒接觸過protractor

理論上可以試一試，但是這樣又讓用戶多了一步長按識別小程序二維碼的動(dòng)作

a = aritprog_gen(1, 2, 4)
>>> next(a)
1
>>> next(a)
3
>>> next(a)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration
>>> a
<itertools.takewhile object at 0x0000022195ADB9C8>

https://docs.python.org/3/lib...
官網(wǎng)解釋takewhile 就是返回一個(gè)迭代器，所以跟普通迭代器一樣沒值就拋StopIteration異常啦，下面是普通迭代器

>>> a = iter(range(1,4,2))
>>> next(a)
1
>>> next(a)
3
>>> next(a)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration
>>> next(a, False)
False
>>> a
<range_iterator object at 0x000001D22C9B4F90>

不是一直個(gè)ap_gen賦值，把函數(shù)aritprog_gen改了，a還是itertools.takewhile的對象

>>> import itertools
>>> def aritprog_gen(begin, step, end=None):
...     first = type(begin + step)(begin)
...     ap_gen = itertools.count(first, step)
...     if end is not None:
...         ap_gen = itertools.takewhile(lambda n: n < end, ap_gen)
...     return ap_gen
...
>>> a = aritprog_gen(1, 2, 4)
>>> def aritprog_gen(begin, step, end=None):
...  return None
...
>>> next(a)
1
>>> a.__next__()
3
>>> a.__next__()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration
>>> next(a)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration
>>>

.NET目前的現(xiàn)狀很尷尬，跟微軟的定位有關(guān)。
微軟的"移動(dòng)優(yōu)先，云優(yōu)先"戰(zhàn)略，現(xiàn)在看起來前半句是蒙人的，后半句卻實(shí)實(shí)在在的落地了。微軟已經(jīng)從原來的Windows生態(tài)跳出來，進(jìn)入云計(jì)算特別是企業(yè)云計(jì)算第一梯隊(duì)了，.NET在微軟的生態(tài)里重要性沒有以前那么大了。
而Python可是當(dāng)前最火的所謂人工智能的第一語言。

不過語言排名只能代表目前的趨勢，畢竟有大批的企業(yè)、政務(wù)、工控行業(yè)還是基于WinForm的，他們不可能改變，或者短期內(nèi)做出改變。所以與其在這里探討排名，不如好好把一門語言學(xué)精，VB大神也能輕松實(shí)現(xiàn)財(cái)務(wù)自由，Win7和XP目前還是市場占有率最高的操作系統(tǒng)。

另外：葡萄城也同時(shí)具有.NET開發(fā)控件集ComponentOne和前端開發(fā)工具WijmoJS和純前端表格控件SpreadJS。這些工具并沒有受語言排名產(chǎn)生波動(dòng)，同樣在華為、招商、富士通、微軟等企業(yè)得到廣泛使用。

把<p>里面的內(nèi)容整個(gè)提取出string來后用re提取。

r'\<br\>([\w\/]+)$'

注意，這是Python3.x，默認(rèn)使用Unicode：

看完需求我的理解其實(shí)就是如何在主進(jìn)程里面kill掉子進(jìn)程（不知道理解的對不對），試試下面的方法：

child = subprocess.Popen("b.exe %s -d %s -t %s "%(value,key1,key2))
child.kill() #或者child.terminate()

配置HTTPS - 阿里云

運(yùn)行正常，沒有問題，看看是不是你的 tab 和 4 個(gè)空格是不是混用了。

首先要明確一點(diǎn)：ArrayList用for循環(huán)遍歷比iterator迭代器遍歷快，LinkedList用iterator迭代器遍歷比for循環(huán)遍歷快。
至于Iterator為什么比順序遍歷鏈表要節(jié)省時(shí)間，我的理解是，由于arrayList基于數(shù)組，下標(biāo)明確，使用for循環(huán)的時(shí)候，get(i)效率很高；
而linkedList基于鏈表，get(i)復(fù)雜度是O(n)，加上循環(huán)的次數(shù)就是O(n^2)，但是用iterator.next()則不需要下標(biāo)，只需要算上循環(huán)的復(fù)雜度就可以了

python 里面雙下劃線的方法被叫做“魔法方法”，可以自己查一些相關(guān)介紹，這是別人總結(jié)的一些常用的https://www.jianshu.com/p/3f4...

brew install python3
或者使用虛擬環(huán)境搭建 比如 virtualenv

是不是我只有一臺服務(wù)器就沒有必要用rpc?

不是的， 你裝的操作系統(tǒng)進(jìn)程間通信大量的大用rpc技術(shù)，因?yàn)楫?dāng)軟件復(fù)雜到一定程度時(shí)需要通過模塊化解耦，便于分別升級維護(hù)，便于團(tuán)隊(duì)開發(fā)。

rpc是不是要可以用于遠(yuǎn)程的客戶端服務(wù)器通信？

可以的，http-rpc了解下。處理好現(xiàn)在的微服務(wù)也是類似的概念，需要做的是處理好安全，和流量管理的問題，這些都有現(xiàn)成的方案。問題是哪種技術(shù)更適合。

rpc是否可以跨語言？

當(dāng)然沒問題，跨平臺跨語言的早就發(fā)明出來了。但如果用同一種語言的序列化方式，顯然會(huì)更方便也效率更高，成本更低，前提是你沒有跨語言的要求。