**A thread-safe list with efficient appends and pops from either side. Pronounced "deck".**
**List with efficient appends and pops from either side. Pronounced "deck".**
```python
from collections import deque
@ -2101,71 +2101,6 @@ from collections import deque
```
Threading
---------
**CPython interpreter can only run a single thread at a time. Using multiple threads won't result in a faster execution, unless at least one of the threads contains an I/O operation.**
```python
from threading import Thread, Lock, RLock, Semaphore, Event, Barrier
from concurrent.futures import ThreadPoolExecutor, as_completed
```
### Thread
```python
<Thread> = Thread(target=<function>) # Use `args=<collection>` to set the arguments.
<Thread>.start() # Starts the thread. Also <Thread>.is_alive().
<Thread>.join() # Waits for the thread to finish.
```
* **Use `'kwargs=<dict>'` to pass keyword arguments to the function.**
* **Use `'daemon=True'`, or the program will not be able to exit while the thread is alive.**
### Lock
```python
<lock> = Lock/RLock() # RLock can only be released by acquirer.
<lock>.acquire() # Waits for the lock to be available.
<lock>.release() # Makes the lock available again.
```
#### Or:
```python
with <lock>: # Enters the block by calling acquire() and
... # exits it with release(), even on error.
```
### Semaphore, Event, Barrier
```python
<Semaphore> = Semaphore(value=1) # Lock that can be acquired by 'value' threads.
<Event> = Event() # Method wait() blocks until set() is called.
<Barrier> = Barrier(n_times) # Wait() blocks until it's called n_times.
```
### Queue
```python
<Queue> = queue.Queue(maxsize=0) # A thread-safe first-in-first-out queue.
<Queue>.put(<el>) # Blocks until queue stops being full.
<Queue>.put_nowait(<el>) # Raises queue.Full exception if full.
<el> = <Queue>.get() # Blocks until queue stops being empty.
<el> = <Queue>.get_nowait() # Raises queue.Empty exception if empty.
```
### Thread Pool Executor
```python
<Exec> = ThreadPoolExecutor(max_workers=None) # Or: `with ThreadPoolExecutor() as <name>: ...`
<Futr> = <Exec>.submit(<func>, <arg_1>, ...) # Creates a thread and returns its Future obj.
<Exec>.shutdown() # Blocks until all threads finish executing.
```
```python
<bool> = <Future>.done() # Checks if the thread has finished executing.
<obj> = <Future>.result(timeout=None) # Waits for thread to finish and returns result.
<bool> = <Future>.cancel() # Cancels or returns False if running/finished.
<iter> = as_completed(<coll_of_Futures>) # `next(<iter>)` returns next completed Future.
```
* **Map() and as\_completed() also accept 'timeout'. It causes futures.TimeoutError when next() is called/blocking. Map() times from original call and as_completed() from first call to next(). As\_completed() fails if next() is called too late, even if all threads are done.**
* **Exceptions that happen inside threads are raised when map iterator's next() or Future's result() are called. Future's exception() method returns exception object or None.**
* **ProcessPoolExecutor provides true parallelism but: everything sent to/from workers must be [pickable](#pickle), queues must be sent using executor's 'initargs' and 'initializer' parameters, and executor should only be reachable via `'if __name__ == "__main__": ...'`.**
Operator
--------
**Module of functions that provide the functionality of operators. Functions are ordered and grouped by operator precedence from least to most binding. Logical and arithmetic operators in rows 1, 3 and 5 are also ordered by precedence within a group.**
@ -2316,6 +2251,71 @@ delattr(<obj>, '<name>') # Deletes attribute from __dict__. Also `del
```
Threading
---------
**CPython interpreter can only run a single thread at a time. Using multiple threads won't result in a faster execution, unless at least one of the threads contains an I/O operation.**
```python
from threading import Thread, Lock, RLock, Semaphore, Event, Barrier
from concurrent.futures import ThreadPoolExecutor, as_completed
```
### Thread
```python
<Thread> = Thread(target=<function>) # Use `args=<collection>` to set the arguments.
<Thread>.start() # Starts the thread. Also <Thread>.is_alive().
<Thread>.join() # Waits for the thread to finish.
```
* **Use `'kwargs=<dict>'` to pass keyword arguments to the function.**
* **Use `'daemon=True'`, or the program will not be able to exit while the thread is alive.**
### Lock
```python
<lock> = Lock/RLock() # RLock can only be released by acquirer.
<lock>.acquire() # Waits for the lock to be available.
<lock>.release() # Makes the lock available again.
```
#### Or:
```python
with <lock>: # Enters the block by calling acquire() and
... # exits it with release(), even on error.
```
### Semaphore, Event, Barrier
```python
<Semaphore> = Semaphore(value=1) # Lock that can be acquired by 'value' threads.
<Event> = Event() # Method wait() blocks until set() is called.
<Barrier> = Barrier(n_times) # Wait() blocks until it's called n_times.
```
### Queue
```python
<Queue> = queue.Queue(maxsize=0) # A thread-safe first-in-first-out queue.
<Queue>.put(<el>) # Blocks until queue stops being full.
<Queue>.put_nowait(<el>) # Raises queue.Full exception if full.
<el> = <Queue>.get() # Blocks until queue stops being empty.
<el> = <Queue>.get_nowait() # Raises queue.Empty exception if empty.
```
### Thread Pool Executor
```python
<Exec> = ThreadPoolExecutor(max_workers=None) # Or: `with ThreadPoolExecutor() as <name>: ...`
<Futr> = <Exec>.submit(<func>, <arg_1>, ...) # Creates a thread and returns its Future obj.
<Exec>.shutdown() # Blocks until all threads finish executing.
```
```python
<bool> = <Future>.done() # Checks if the thread has finished executing.
<obj> = <Future>.result(timeout=None) # Waits for thread to finish and returns result.
<bool> = <Future>.cancel() # Cancels or returns False if running/finished.
<iter> = as_completed(<coll_of_Futures>) # `next(<iter>)` returns next completed Future.
```
* **Map() and as\_completed() also accept 'timeout'. It causes futures.TimeoutError when next() is called/blocking. Map() times from original call and as_completed() from first call to next(). As\_completed() fails if next() is called too late, even if all threads are done.**
* **Exceptions that happen inside threads are raised when map iterator's next() or Future's result() are called. Future's exception() method returns exception object or None.**
* **ProcessPoolExecutor provides true parallelism but: everything sent to/from workers must be [pickable](#pickle), queues must be sent using executor's 'initargs' and 'initializer' parameters, and executor should only be reachable via `'if __name__ == "__main__": ...'`.**
Coroutines
----------
* **Coroutines have a lot in common with threads, but unlike threads, they only give up control when they call another coroutine and they don’t use as much memory.**
@ -2553,7 +2553,7 @@ import flask as fl
```python
app = fl.Flask(__name__) # Returns the app object. Put at the top.
* **Starts the app at `'http://localhost:5000'`. Use `'host="0.0.0.0"'` to run externally.**
* **Install a WSGI server like [Waitress](https://flask.palletsprojects.com/en/latest/deploying/waitress/) and a HTTP server such as [Nginx](https://flask.palletsprojects.com/en/latest/deploying/nginx/) for better security.**
@ -3146,7 +3146,7 @@ if __name__ == '__main__':
Pandas
------
**Data analysis library. For examples see [Plotly](#displays-a-line-chart-of-total-coronavirus-deaths-per-million-grouped-by-continent).**
**Data analysis library. For examples see [Plotly](#plotly).**
<div><h2id="deque"><ahref="#deque"name="deque">#</a>Deque</h2><p><strong>A thread-safe list with efficient appends and pops from either side. Pronounced "deck".</strong></p><pre><codeclass="python language-python hljs"><spanclass="hljs-keyword">from</span> collections <spanclass="hljs-keyword">import</span> deque
<div><h2id="deque"><ahref="#deque"name="deque">#</a>Deque</h2><p><strong>List with efficient appends and pops from either side. Pronounced "deck".</strong></p><pre><codeclass="python language-python hljs"><spanclass="hljs-keyword">from</span> collections <spanclass="hljs-keyword">import</span> deque
<deque>.rotate(n=<spanclass="hljs-number">1</span>) <spanclass="hljs-comment"># Last element becomes first.</span>
<el> = <deque>.popleft() <spanclass="hljs-comment"># Raises IndexError if deque is empty.</span>
</code></pre>
<div><h2id="threading"><ahref="#threading"name="threading">#</a>Threading</h2><p><strong>CPython interpreter can only run a single thread at a time. Using multiple threads won't result in a faster execution, unless at least one of the threads contains an I/O operation.</strong></p><pre><codeclass="python language-python hljs"><spanclass="hljs-keyword">from</span> threading <spanclass="hljs-keyword">import</span> Thread, Lock, RLock, Semaphore, Event, Barrier
<div><h3id="thread">Thread</h3><pre><codeclass="python language-python hljs"><Thread> = Thread(target=<function>) <spanclass="hljs-comment"># Use `args=<collection>` to set the arguments.</span>
<Thread>.start() <spanclass="hljs-comment"># Starts the thread. Also <Thread>.is_alive().</span>
<Thread>.join() <spanclass="hljs-comment"># Waits for the thread to finish.</span>
</code></pre></div>
<ul>
<li><strong>Use <codeclass="python hljs"><spanclass="hljs-string">'kwargs=<dict>'</span></code> to pass keyword arguments to the function.</strong></li>
<li><strong>Use <codeclass="python hljs"><spanclass="hljs-string">'daemon=True'</span></code>, or the program will not be able to exit while the thread is alive.</strong></li>
</ul>
<div><h3id="lock">Lock</h3><pre><codeclass="python language-python hljs"><lock> = Lock/RLock() <spanclass="hljs-comment"># RLock can only be released by acquirer.</span>
<lock>.acquire() <spanclass="hljs-comment"># Waits for the lock to be available.</span>
<lock>.release() <spanclass="hljs-comment"># Makes the lock available again.</span>
</code></pre></div>
<div><h4id="or-1">Or:</h4><pre><codeclass="python language-python hljs"><spanclass="hljs-keyword">with</span><lock>: <spanclass="hljs-comment"># Enters the block by calling acquire() and</span>
... <spanclass="hljs-comment"># exits it with release(), even on error.</span>
</code></pre></div>
<div><h3id="semaphoreeventbarrier">Semaphore, Event, Barrier</h3><pre><codeclass="python language-python hljs"><Semaphore> = Semaphore(value=<spanclass="hljs-number">1</span>) <spanclass="hljs-comment"># Lock that can be acquired by 'value' threads.</span>
<Event> = Event() <spanclass="hljs-comment"># Method wait() blocks until set() is called.</span>
<Barrier> = Barrier(n_times) <spanclass="hljs-comment"># Wait() blocks until it's called n_times.</span>
</code></pre></div>
<div><h3id="queue">Queue</h3><pre><codeclass="python language-python hljs"><Queue> = queue.Queue(maxsize=<spanclass="hljs-number">0</span>) <spanclass="hljs-comment"># A thread-safe first-in-first-out queue.</span>
<Queue>.put(<el>) <spanclass="hljs-comment"># Blocks until queue stops being full.</span>
<Queue>.put_nowait(<el>) <spanclass="hljs-comment"># Raises queue.Full exception if full.</span>
<el> = <Queue>.get() <spanclass="hljs-comment"># Blocks until queue stops being empty.</span>
<el> = <Queue>.get_nowait() <spanclass="hljs-comment"># Raises queue.Empty exception if empty.</span>
</code></pre></div>
<div><h3id="threadpoolexecutor">Thread Pool Executor</h3><pre><codeclass="python language-python hljs"><Exec> = ThreadPoolExecutor(max_workers=<spanclass="hljs-keyword">None</span>) <spanclass="hljs-comment"># Or: `with ThreadPoolExecutor() as <name>: ...`</span>
<Futr> = <Exec>.submit(<func>, <arg_1>, ...) <spanclass="hljs-comment"># Creates a thread and returns its Future obj.</span>
<Exec>.shutdown() <spanclass="hljs-comment"># Blocks until all threads finish executing.</span>
</code></pre></div>
<pre><codeclass="python language-python hljs"><bool> = <Future>.done() <spanclass="hljs-comment"># Checks if the thread has finished executing.</span>
<obj> = <Future>.result(timeout=<spanclass="hljs-keyword">None</span>) <spanclass="hljs-comment"># Waits for thread to finish and returns result.</span>
<bool> = <Future>.cancel() <spanclass="hljs-comment"># Cancels or returns False if running/finished.</span>
<iter> = as_completed(<coll_of_Futures>) <spanclass="hljs-comment"># `next(<iter>)` returns next completed Future.</span>
</code></pre>
<ul>
<li><strong>Map() and as_completed() also accept 'timeout'. It causes futures.TimeoutError when next() is called/blocking. Map() times from original call and as_completed() from first call to next(). As_completed() fails if next() is called too late, even if all threads are done.</strong></li>
<li><strong>Exceptions that happen inside threads are raised when map iterator's next() or Future's result() are called. Future's exception() method returns exception object or None.</strong></li>
<li><strong>ProcessPoolExecutor provides true parallelism but: everything sent to/from workers must be <ahref="#pickle">pickable</a>, queues must be sent using executor's 'initargs' and 'initializer' parameters, and executor should only be reachable via <codeclass="python hljs"><spanclass="hljs-string">'if __name__ == "__main__": ...'</span></code>.</strong></li>
</ul>
<div><h2id="operator"><ahref="#operator"name="operator">#</a>Operator</h2><p><strong>Module of functions that provide the functionality of operators. Functions are ordered and grouped by operator precedence from least to most binding. Logical and arithmetic operators in rows 1, 3 and 5 are also ordered by precedence within a group.</strong></p><pre><codeclass="python language-python hljs"><spanclass="hljs-keyword">import</span> operator <spanclass="hljs-keyword">as</span> op
<memb> = <Param>.kind <spanclass="hljs-comment"># Returns ParameterKind member (Parameter.KEYWORD_ONLY, …).</span>
<type> = <Param>.annotation <spanclass="hljs-comment"># Returns Parameter.empty if missing. Also <Param>.default.</span>
</code></pre>
<div><h2id="threading"><ahref="#threading"name="threading">#</a>Threading</h2><p><strong>CPython interpreter can only run a single thread at a time. Using multiple threads won't result in a faster execution, unless at least one of the threads contains an I/O operation.</strong></p><pre><codeclass="python language-python hljs"><spanclass="hljs-keyword">from</span> threading <spanclass="hljs-keyword">import</span> Thread, Lock, RLock, Semaphore, Event, Barrier
<div><h3id="thread">Thread</h3><pre><codeclass="python language-python hljs"><Thread> = Thread(target=<function>) <spanclass="hljs-comment"># Use `args=<collection>` to set the arguments.</span>
<Thread>.start() <spanclass="hljs-comment"># Starts the thread. Also <Thread>.is_alive().</span>
<Thread>.join() <spanclass="hljs-comment"># Waits for the thread to finish.</span>
</code></pre></div>
<ul>
<li><strong>Use <codeclass="python hljs"><spanclass="hljs-string">'kwargs=<dict>'</span></code> to pass keyword arguments to the function.</strong></li>
<li><strong>Use <codeclass="python hljs"><spanclass="hljs-string">'daemon=True'</span></code>, or the program will not be able to exit while the thread is alive.</strong></li>
</ul>
<div><h3id="lock">Lock</h3><pre><codeclass="python language-python hljs"><lock> = Lock/RLock() <spanclass="hljs-comment"># RLock can only be released by acquirer.</span>
<lock>.acquire() <spanclass="hljs-comment"># Waits for the lock to be available.</span>
<lock>.release() <spanclass="hljs-comment"># Makes the lock available again.</span>
</code></pre></div>
<div><h4id="or-1">Or:</h4><pre><codeclass="python language-python hljs"><spanclass="hljs-keyword">with</span><lock>: <spanclass="hljs-comment"># Enters the block by calling acquire() and</span>
... <spanclass="hljs-comment"># exits it with release(), even on error.</span>
</code></pre></div>
<div><h3id="semaphoreeventbarrier">Semaphore, Event, Barrier</h3><pre><codeclass="python language-python hljs"><Semaphore> = Semaphore(value=<spanclass="hljs-number">1</span>) <spanclass="hljs-comment"># Lock that can be acquired by 'value' threads.</span>
<Event> = Event() <spanclass="hljs-comment"># Method wait() blocks until set() is called.</span>
<Barrier> = Barrier(n_times) <spanclass="hljs-comment"># Wait() blocks until it's called n_times.</span>
</code></pre></div>
<div><h3id="queue">Queue</h3><pre><codeclass="python language-python hljs"><Queue> = queue.Queue(maxsize=<spanclass="hljs-number">0</span>) <spanclass="hljs-comment"># A thread-safe first-in-first-out queue.</span>
<Queue>.put(<el>) <spanclass="hljs-comment"># Blocks until queue stops being full.</span>
<Queue>.put_nowait(<el>) <spanclass="hljs-comment"># Raises queue.Full exception if full.</span>
<el> = <Queue>.get() <spanclass="hljs-comment"># Blocks until queue stops being empty.</span>
<el> = <Queue>.get_nowait() <spanclass="hljs-comment"># Raises queue.Empty exception if empty.</span>
</code></pre></div>
<div><h3id="threadpoolexecutor">Thread Pool Executor</h3><pre><codeclass="python language-python hljs"><Exec> = ThreadPoolExecutor(max_workers=<spanclass="hljs-keyword">None</span>) <spanclass="hljs-comment"># Or: `with ThreadPoolExecutor() as <name>: ...`</span>
<Futr> = <Exec>.submit(<func>, <arg_1>, ...) <spanclass="hljs-comment"># Creates a thread and returns its Future obj.</span>
<Exec>.shutdown() <spanclass="hljs-comment"># Blocks until all threads finish executing.</span>
</code></pre></div>
<pre><codeclass="python language-python hljs"><bool> = <Future>.done() <spanclass="hljs-comment"># Checks if the thread has finished executing.</span>
<obj> = <Future>.result(timeout=<spanclass="hljs-keyword">None</span>) <spanclass="hljs-comment"># Waits for thread to finish and returns result.</span>
<bool> = <Future>.cancel() <spanclass="hljs-comment"># Cancels or returns False if running/finished.</span>
<iter> = as_completed(<coll_of_Futures>) <spanclass="hljs-comment"># `next(<iter>)` returns next completed Future.</span>
</code></pre>
<ul>
<li><strong>Map() and as_completed() also accept 'timeout'. It causes futures.TimeoutError when next() is called/blocking. Map() times from original call and as_completed() from first call to next(). As_completed() fails if next() is called too late, even if all threads are done.</strong></li>
<li><strong>Exceptions that happen inside threads are raised when map iterator's next() or Future's result() are called. Future's exception() method returns exception object or None.</strong></li>
<li><strong>ProcessPoolExecutor provides true parallelism but: everything sent to/from workers must be <ahref="#pickle">pickable</a>, queues must be sent using executor's 'initargs' and 'initializer' parameters, and executor should only be reachable via <codeclass="python hljs"><spanclass="hljs-string">'if __name__ == "__main__": ...'</span></code>.</strong></li>
<li><strong>Coroutines have a lot in common with threads, but unlike threads, they only give up control when they call another coroutine and they don’t use as much memory.</strong></li>
<li><strong>Coroutine definition starts with <codeclass="python hljs"><spanclass="hljs-string">'async'</span></code> and its call with <codeclass="python hljs"><spanclass="hljs-string">'await'</span></code>.</strong></li>
<li><strong>Starts the app at <codeclass="python hljs"><spanclass="hljs-string">'http://localhost:5000'</span></code>. Use <codeclass="python hljs"><spanclass="hljs-string">'host="0.0.0.0"'</span></code> to run externally.</strong></li>
'<strong>Objects returned by the <a href="#itertools">itertools</a> module, such as count, repeat and cycle.</strong>':'<strong>Objects returned by the itertools module, such as count, repeat and cycle (p. 3).</strong>',
'<strong>Generators returned by the <a href="#generator">generator functions</a> and <a href="#comprehensions">generator expressions</a>.</strong>':'<strong>Generators returned by the generator functions (p. 4) and generator expressions (p. 11).</strong>',
'<strong>File objects returned by the <a href="#open">open()</a> function, etc.</strong>':'<strong>File objects returned by the open() function (p. 22), etc.</strong>',
'<strong>Use <code class="python hljs"><span class="hljs-string">\'logging.exception(<str>)\'</span></code> to log the passed message, followed by the full error message of the caught exception. For details see <a href="#logging">logging</a>.</strong>':'<strong>Use <code class="python hljs"><span class="hljs-string">\'logging.exception(<str>)\'</span></code> to log the passed message, followed by the full error message of the caught exception. For details see logging (p. 32).</strong>',
'<strong>Use <code class="python hljs"><span class="hljs-string">\'logging.exception(<str>)\'</span></code> to log the passed message, followed by the full error message of the caught exception. For details see <a href="#logging">logging</a>.</strong>':'<strong>Use <code class="python hljs"><span class="hljs-string">\'logging.exception(<str>)\'</span></code> to log the passed message, followed by the full error message of the caught exception. For details see logging (p. 31).</strong>',
'<strong>Functions report OS related errors by raising either OSError or one of its <a href="#exceptions-1">subclasses</a>.</strong>':'<strong>Functions report OS related errors by raising OSError or one of its subclasses (p. 23).</strong>',
'<strong>To print the spreadsheet to the console use <a href="#table">Tabulate</a> library.</strong>':'<strong>To print the spreadsheet to the console use Tabulate library (p. 34).</strong>',
'<strong>For XML and binary Excel files (xlsx, xlsm and xlsb) use <a href="#dataframeplotencodedecode">Pandas</a> library.</strong>':'<strong>For XML and binary Excel files (xlsx, xlsm and xlsb) use Pandas library (p. 46).</strong>',
'<strong>Bools will be stored and returned as ints and dates as <a href="#encode">ISO formatted strings</a>.</strong>':'<strong>Bools will be stored and returned as ints and dates as ISO formatted strings (p. 9).</strong>',
'<strong>ProcessPoolExecutor provides true parallelism but: everything sent to/from workers must be <a href="#pickle">pickable</a>, queues must be sent using executor\'s \'initargs\' and \'initializer\' parameters, and executor should only be reachable via <code class="python hljs"><span class="hljs-string">\'if __name__ == "__main__": ...\'</span></code>.</strong>':'<strong>ProcessPoolExecutor provides true parallelism but: everything sent to/from workers must be pickable, queues must be sent using executor\'s \'initargs\' and \'initializer\' parameters, and executor should only be reachable via <code class="python hljs"><span class="hljs-string">\'if __name__ == "__main__": ...\'</span></code>.</strong>',
'<strong>Asyncio module also provides its own <a href="#queue">Queue</a>, <a href="#semaphoreeventbarrier">Event</a>, <a href="#lock">Lock</a> and <a href="#semaphoreeventbarrier">Semaphore</a> classes.</strong>':'<strong>Asyncio module also provides its own Queue, Event, Lock and Semaphore classes (p. 30).</strong>',
'<strong>Install a WSGI server like <a href="https://flask.palletsprojects.com/en/latest/deploying/waitress/">Waitress</a> and a HTTP server such as <a href="https://flask.palletsprojects.com/en/latest/deploying/nginx/">Nginx</a> for better security.</strong>':'<strong>Install a WSGI server like Waitress and a HTTP server such as Nginx for better security.</strong>',
'<strong>Data analysis library. For examples see <a href="#displays-a-line-chart-of-total-coronavirus-deaths-per-million-grouped-by-continent">Plotly</a>.</strong>':'<strong>Data analysis library. For examples see Plotly (p. 47).</strong>',
'<strong>Data analysis library. For examples see <a href="#plotly">Plotly</a>.</strong>':'<strong>Data analysis library. For examples see Plotly (p. 47).</strong>',
Jure Šorn
5 months ago
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