diff --git a/index.html b/index.html index fcad74c..c762fb9 100644 --- a/index.html +++ b/index.html @@ -120,8 +120,8 @@ product_of_elems = functools.reduce(lambda out list_of_chars = list(<str>) 
<list>.insert(<int>, <el>)     # Inserts item at index and moves the rest to the right.
 <el>  = <list>.pop([<int>])    # Removes and returns item at index or from the end.
@@ -386,7 +386,7 @@ Point(x=1, y=2
 
 
 
Strings
{'abcde':10}                             # 'abcde     '
 {'abcde':10.3}                           # 'abc       '
@@ -750,7 +750,7 @@ player = Player(point, direction)                   #
 

 
#Decorator
    
 
  • A decorator takes a function, adds some functionality and returns it.
    • 
-
  • It can be any callable, but is usually implemented as a function that returns a closure.
    • 
+
  • It can be any callable, but is usually implemented as a function that returns a closure.
    • 
 
@decorator_name
 def function_that_gets_passed_to_decorator():
     ...
@@ -894,9 +894,9 @@ Z = dataclasses.make_dataclass('Z', [
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  • Objects can be made sortable with 'order=True' and immutable with 'frozen=True'.
    • 
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  • For object to be hashable, all attributes must be hashable and 'frozen' must be True.
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  • Function field() is needed because '<attr_name>: list = []' would make a list that is shared among all instances. Its 'default_factory' argument can be any callable (p. 17).
    • 
+
  • Objects can be made sortable with 'order=True' and immutable with 'frozen=True'.
    • 
+
  • For object to be hashable, all attributes must be hashable and 'frozen' must be True.
    • 
+
  • Function field() is needed because '<attr_name>: list = []' would make a list that is shared among all instances. Its 'default_factory' argument can be any callable.
    • 
 
  • For attributes of arbitrary type use 'typing.Any'.
    • 
 
 
    Inline:
    from dataclasses import make_dataclass
@@ -998,10 +998,10 @@ Z = dataclasses.make_dataclass('Z', [1, 2, 3)
 
    
 
    Python has many different iterator objects:
      
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    • Sequence iterators returned by the iter() function, such as list_iterator and set_iterator (p. 3).
      • 
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    • Objects returned by the itertools module, such as count, repeat and cycle (p. 3).
      • 
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    • Generators returned by the generator functions (p. 4) and generator expressions (p. 11).
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    • File objects returned by the open() function (p. 22), etc.
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    • Sequence iterators returned by the iter() function, such as list_iterator and set_iterator.
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+
    • Objects returned by the itertools module, such as count, repeat and cycle.
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+
    • Generators returned by the generator functions and generator expressions.
      • 
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    • File objects returned by the open() function, etc.
      • 
 
    Callable
      
 
    • All functions and classes have a call() method, hence are callable.
      • 
 
    • When this cheatsheet uses '<function>' as an argument, it actually means '<callable>'.
      • 
@@ -1452,7 +1452,7 @@ shutil.rmtree(<path>)               # Deletes t
 
    
 
      
 
    • Paths can be either strings, Paths or DirEntry objects.
      • 
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    • Functions report OS related errors by raising OSError or one of its subclasses (p. 23).
      • 
+
    • Functions report OS related errors by raising either OSError or one of its subclasses.
      • 
 
    
 
    Shell Commands
    <pipe> = os.popen('<command>')      # Executes command in sh/cmd. Returns its stdout pipe.
 <str>  = <pipe>.read(size=-1)       # Reads 'size' chars or until EOF. Also readline/s().
@@ -1514,8 +1514,8 @@ CompletedProcess(args=['bc', 'newline=""' argument, or newlines embedded inside quoted fields will not be interpreted correctly!
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  • To print the spreadsheet to the console use Tabulate library (p. 34).
    • 
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  • For XML and binary Excel files (xlsx, xlsm and xlsb) use Pandas library (p. 46).
    • 
+
  • To print the spreadsheet to the console use Tabulate library.
    • 
+
  • For XML and binary Excel files (xlsx, xlsm and xlsb) use Pandas library.
    • 
 
  • Reader accepts any iterator of strings, not just files.
    • 
 
 
    Write
    <writer> = csv.writer(<file>)       # Also: `dialect='excel', delimiter=','`.
@@ -1588,7 +1588,7 @@ CompletedProcess(args=['bc', ISO formatted strings.
 
 
    Example
    Values are not actually saved in this example because 'conn.commit()' is omitted!
    >>> conn = sqlite3.connect('test.db')
 >>> conn.execute('CREATE TABLE person (person_id INTEGER PRIMARY KEY, name, height)')
@@ -1761,7 +1761,7 @@ CompletedProcess(args=['bc', Thread Pool Executor
      
 
    • Object that manages thread execution.
      • 
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    • An object with the same interface called ProcessPoolExecutor provides true parallelism by running a separate interpreter in each process. All arguments must be pickable (p. 25).
      • 
+
    • An object with the same interface called ProcessPoolExecutor provides true parallelism by running a separate interpreter in each process. All arguments must be pickable.
      • 
 
    <Exec> = ThreadPoolExecutor(max_workers=None)  # Or: `with ThreadPoolExecutor() as <name>: …`
 <Exec>.shutdown(wait=True)                     # Blocks until all threads finish executing.
 
    
@@ -1898,7 +1898,7 @@ ValueError: malformed node or string
 
  • Coroutine definition starts with 'async' and its call with 'await'.
    • 
 
  • 'asyncio.run(<coroutine>)' is the main entry point for asynchronous programs.
    • 
 
  • Functions wait(), gather() and as_completed() start multiple coroutines at the same time.
    • 
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  • Asyncio module also provides its own Queue, Event, Lock and Semaphore classes (p. 30).
    • 
+
  • Asyncio module also provides its own Queue, Event, Lock and Semaphore classes.
    • 
 
    Runs a terminal game where you control an asterisk that must avoid numbers:
    import asyncio, collections, curses, curses.textpad, enum, random
 
 P = collections.namedtuple('P', 'x y')         # Position
@@ -2081,7 +2081,7 @@ app.run()
 
    
 
      
 
    • Starts the app on 'http://localhost:5000'.
      • 
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    • A WSGI server like Waitress and a HTTP server such as Nginx are needed to run globally.
      • 
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    • A WSGI server like Waitress and a HTTP server such as Nginx are needed to run globally.
      • 
 
    
 
    Static Request
    @app.route('/img/<path:filename>')
 def serve_file(filename):
@@ -2162,7 +2162,7 @@ drawer = cg.output.GraphvizOutput(output_file=filename)
 
 
 
      
-
    • The "latest and greatest" profiler that can also monitor GPU usage is called Scalene.
      • 
+
    • The "latest and greatest" profiler that can also monitor GPU usage is called Scalene.
      • 
 
    
 
    #NumPy
    Array manipulation mini-language. It can run up to one hundred times faster than the equivalent Python code. An even faster alternative that runs on a GPU is called CuPy.
    # $ pip3 install numpy
 import numpy as np