CPython uses a Global Interpreter Lock. Linux has removed all traces of the Big Kernel Lock. What is the alternative to these locks? How can a system make full use of a truly multi-core or multi-processor system without grinding everything to a halt? A GIL wouldn't be necessary if python used a more advanced Garbage Collector like IBM's Recycler instated of a primitive reference coun
CPython使用全局解释器锁。 Linux已经删除了大内核锁的所有痕迹。 什么是这些锁的替代品？ 一个系统如何充分利用真正的多核或多处理器系统，而不会把所有的事情都停下来？ 如果python使用像IBM的Recycler这样的更高级的垃圾收集器，那么GIL就没有必要了。 这是Unladen Swallow为改善蟒蛇性能而做的事情。 一个更有前途的答案是Stackless Python，它使用自己的微线程实现，而不像传统的CPython那样依赖于操作系统。 GIL
I'm curious in how the Global Interpreter Lock in python actually works. If I have a c++ application launch four separate instances of a python script will they run in parallel on separate cores, or does the GIL go even deeper then just the single process that was launched and control all python process's regardless of the process that spawned it? The GIL only affects threads within a
我很好奇Python中的全局解释器锁实际上是如何工作的。 如果我有一个c ++应用程序启动，python脚本的四个独立实例将在不同核心上并行运行，或者GIL更深入一些，那么启动的单个进程就可以控制所有python进程，而不管产生它的进程？ GIL只影响单个进程中的线程。 multiprocessing模块实际上是threading一种替代方案，它允许Python程序使用多个核心＆c。 您的方案也可以轻松地使用多个内核。 正如Alex Martelli指出的那样，你
When deleting a column in a DataFrame I use: del df['column_name'] And this works great. Why can't I use the following? del df.column_name As you can access the column/Series as df.column_name , I expect this to work. It's difficult to make del df.column_name work simply as the result of syntactic limitations in Python. del df[name] gets translated to df.__delitem__(name) under th
当删除DataFrame中的列时，我使用： del df['column_name'] 这工作很好。 为什么我不能使用以下内容？ del df.column_name 正如你可以访问列/ Series作为df.column_name ，我期望这个工作。 由于Python中的语法限制，很难让del df.column_name正常工作。 del df[name]被Python翻译为df.__delitem__(name) 。 在熊猫做这件事的最好方法是使用drop ： df = df.drop('column_name', 1) 其中1是轴编号（ 0表示行， 1表示
In my app , I need the client to join a room so that it may then receive messages from my server . Server Code @socketio.on('join', namespace='/test') def join(message): join_room(message['room']) room = message['room'] emit('my response', {'data': 'Entered the room ' + message['room']}, room=room) @app.route('/scan/user/<int:user_id>/venue/<int:venue_id>', methods =
在我的app ，我需要client加入一个room以便它可以从我的server receive消息。 服务器代码 @socketio.on('join', namespace='/test') def join(message): join_room(message['room']) room = message['room'] emit('my response', {'data': 'Entered the room ' + message['room']}, room=room) @app.route('/scan/user/<int:user_id>/venue/<int:venue_id>', methods = ['POST']) @auth.login_requ
What are the consequences of not closing a psycopg2 connection at the end of a Python script? For example, consider the following snippet: import psycopg2 psycopg2.connect("dbname=test") The script opens a connection, but does not close it at the end. Is the connection still open at the end of the execution? If so, is there an issue with not closing the connection? Normally when your pytho
在Python脚本的末尾没有关闭psycopg2连接有什么后果？ 例如，请考虑以下代码片段： import psycopg2 psycopg2.connect("dbname=test") 该脚本将打开一个连接，但不会在最后关闭它。 执行结束时连接是否仍然打开？ 如果是这样，是否存在未关闭连接的问题？ 通常，当你的python程序退出时，它拥有的所有套接字将被关闭，并且打开事务中止。 但最终关闭连接是一个很好的做法。 一旦你不再需要它，就立即关闭连接，从而释
Is there a library that could help decode the punched tape from an image? Punched tape is like this: The dots have different color than background. The image is just a white rectangle with black dots. I need to locate the dots and then decode the text. The desired output is for example an array ("00011", "11001", ...) where 1 is the dot, 0 is the missing dot. What appr
有没有一个库可以帮助解码图像中的穿孔磁带？ 穿孔胶带是这样的： 点的颜色与背景不同。 图像只是一个带黑点的白色矩形。 我需要找到点，然后解码文本。 所需的输出例如是一个数组（“00011”，“11001”，...），其中1是点，0是缺失的点。 你会推荐什么方法？ 我宁愿使用像python的PIL或ImageMagick或Ruby中的某些东西。
Look at this Python code: from gc import get_referrers as refs x = 'x' d = {x:x} print(d in refs(x)) It prints False. That's weird by itself, but becomes much weirder when you consider the following: If x is a number (int, float, complex, Fraction, Decimal) instead of a string, it still prints False. For bytes and bytearray, too. But for every other type (hashable if used as key, like
看看这个Python代码： from gc import get_referrers as refs x = 'x' d = {x:x} print(d in refs(x)) 它打印False。 这本身就很奇怪，但在考虑以下情况时会变得更加怪异： 如果x是一个数字（int，float，complex，Fraction，Decimal）而不是字符串，它仍然会打印False。 对于字节和bytearray也是如此。 但是对于其他类型（如果用作键的话可以散列，比如tuple或者frozenset，但是很多其他类型，如果仅用作值），它会打印T
From what I understand, Flask Admin supports AJAX use for foreign key model loading. The Flask Admin - Model Documentation covers the basics under the heading form_ajax_refs . I have managed to use this successfully on many occasions, however I am having issues with the level of customisation that I hope to achieve. Let me elaborate. I have a Product model, an Organisation model and a join t
据我所知，Flask Admin支持AJAX用于外键加载。 Flask Admin - Model Documentation涵盖了标题form_ajax_refs下的基础知识。 我已经成功地在很多场合成功地使用了这个功能，但是我希望能够实现定制化水平方面的问题。 让我详细说明一下。 我有一个Product模型，一个Organisation模型和一个连接表来关联它们，定义如下： class Product(Base): __tablename__ = "products" product_uuid = Column(UUID(as_uuid=Tru
What I need to accomplish: Given a binary file, decode it in a couple different ways providing a TextIOBase API. Ideally these subsequent files can get passed on without my needing to keep track of their lifespan explicitly. Unfortunately, wrapping a BufferedReader will result in that reader being closed when the TextIOWrapper goes out of scope. Here is a simple demo of this: In [1]: impo
我需要实现的是： 给定一个二进制文件，以几种不同的方式对它进行解码，以提供一个TextIOBase API。 理想情况下，这些后续文件可以传递，而不需要明确地追踪它们的寿命。 不幸的是，包装BufferedReader会导致读者在TextIOWrapper超出范围时关闭。 这是一个简单的演示： In [1]: import io In [2]: def mangle(x): ...: io.TextIOWrapper(x) # Will get GCed causing __del__ to call close ...: In [3]:
I am writing a YAML file using https://pypi.python.org/pypi/ruamel.yaml The code is like this: import ruamel.yaml from ruamel.yaml.comments import CommentedSeq d = {} for m in ['B1', 'B2', 'B3']: d2 = {} for f in ['A1', 'A2', 'A3']: d2[f] = CommentedSeq(['test', 'test2']) if f != 'A2': d2[f].fa.set_flow_style() d[m] = d2 with open('test.yml', "w")
我正在使用https://pypi.python.org/pypi/ruamel.yaml编写YAML文件 代码是这样的： import ruamel.yaml from ruamel.yaml.comments import CommentedSeq d = {} for m in ['B1', 'B2', 'B3']: d2 = {} for f in ['A1', 'A2', 'A3']: d2[f] = CommentedSeq(['test', 'test2']) if f != 'A2': d2[f].fa.set_flow_style() d[m] = d2 with open('test.yml', "w") as f: rua