Python
Floor Division¶
5 // 2 will divide 5 by 2 and round the result down to the nearest integer.
Lists¶
Lists are implemented as an array of pointers.
typedef struct {
PyObject_HEAD
Py_ssize_t ob_size;
/* Vector of pointers to list elements. list[0] is ob_item[0], etc. */
PyObject **ob_item;
/* ob_item contains space for 'allocated' elements. The number
* currently in use is ob_size.
* Invariants:
* 0 <= ob_size <= allocated
* len(list) == ob_size
* ob_item == NULL implies ob_size == allocated == 0
*/
Py_ssize_t allocated;
} PyListObject;
A list is grown not by doubling, but by a pattern that looks like 0, 4, 8, 16, 25, 35, 46, 58, 72, 88, ...:
/* Ensure ob_item has room for at least newsize elements, and set
* ob_size to newsize. If newsize > ob_size on entry, the content
* of the new slots at exit is undefined heap trash; it's the caller's
* responsibility to overwrite them with sane values.
* The number of allocated elements may grow, shrink, or stay the same.
* Failure is impossible if newsize <= self.allocated on entry, although
* that partly relies on an assumption that the system realloc() never
* fails when passed a number of bytes <= the number of bytes last
* allocated (the C standard doesn't guarantee this, but it's hard to
* imagine a realloc implementation where it wouldn't be true).
* Note that self->ob_item may change, and even if newsize is less
* than ob_size on entry.
*/
static int
list_resize(PyListObject *self, Py_ssize_t newsize)
{
PyObject **items;
size_t new_allocated, num_allocated_bytes;
Py_ssize_t allocated = self->allocated;
/* Bypass realloc() when a previous overallocation is large enough
to accommodate the newsize. If the newsize falls lower than half
the allocated size, then proceed with the realloc() to shrink the list.
*/
if (allocated >= newsize && newsize >= (allocated >> 1)) {
assert(self->ob_item != NULL || newsize == 0);
Py_SIZE(self) = newsize;
return 0;
}
/* This over-allocates proportional to the list size, making room
* for additional growth. The over-allocation is mild, but is
* enough to give linear-time amortized behavior over a long
* sequence of appends() in the presence of a poorly-performing
* system realloc().
* The growth pattern is: 0, 4, 8, 16, 25, 35, 46, 58, 72, 88, ...
* Note: new_allocated won't overflow because the largest possible value
* is PY_SSIZE_T_MAX * (9 / 8) + 6 which always fits in a size_t.
*/
new_allocated = (size_t)newsize + (newsize >> 3) + (newsize < 9 ? 3 : 6);
if (new_allocated > (size_t)PY_SSIZE_T_MAX / sizeof(PyObject *)) {
PyErr_NoMemory();
return -1;
}
if (newsize == 0)
new_allocated = 0;
num_allocated_bytes = new_allocated * sizeof(PyObject *);
items = (PyObject **)PyMem_Realloc(self->ob_item, num_allocated_bytes);
if (items == NULL) {
PyErr_NoMemory();
return -1;
}
self->ob_item = items;
Py_SIZE(self) = newsize;
self->allocated = new_allocated;
return 0;
}
Decorators¶
Decorators are a special syntax in python that allow you to wrap a function with another function. For example, consider if we have the function:
We can wrap this function in another function that extends the behavior.
from typing import Callable
def addBarDecorator(func: Callable[[str], str]) -> Callable[[str], str]:
def wrapper(string: str) -> str:
string += "bar"
return func(string)
return wrapper
addFoo = addBarDecorator(addFoo)
print(addFoo("hello"))
You can see that our decorator returns a function wrapper, which contains the same signature of the wrapped function. wrapper performs some operation on the input before passing it along to the wrapped function, which is why the result becomes hellobarfoo: bar is added to the string first (in wrapper), then foo is added in addFoo.
There is syntatic sugar you can use to avoid having to specify addFoo = addBarDecorator(addFoo):
from typing import Callable
def addBarDecorator(func: Callable[[str], str]) -> Callable[[str], str]:
def wrapper(string: str) -> str:
string += "bar"
return func(string)
return wrapper
@addBarDecorator
def addFoo(string: str) -> str:
return string + "foo"
print(addFoo("hello"))
Context Manager (with statement)¶
A context manager is a magic method you can add to a class that allows you to perform setup/teardown logic that is scoped within a particular lexical block. For example:
from pathlib import Path
path = Path("/Users/landonclipp/test.txt")
with path.open("w") as f:
f.write("foobar\n")
The with operator first calls the magic method __enter__ on the object returned by path.open, which is a TextIOWrapper. When the enclosing block exits, the context manager calls __exit__, which in this case will flush any remaining bytes to the file and close it.
We can implement our own context manager. Take this example:
class Foo:
def __init__(self): pass
def __enter__(self):
print("enter")
def __exit__(self, exc_type, exc_val, exc_tb):
print("exit")
with Foo() as foo:
print("enclosing block")
The __exit__ function takes some additional parameters, as you've noticed. These are explained here:
exc_type: The type of exception raisedexc_value: The value of the exception.exc_tb: The traceback of the exception.
Let's see what happens when we raise an exception in our with block:
class Foo:
def __init__(self): pass
def __enter__(self):
print("enter")
def __exit__(self, exc_type, exc_val, exc_tb):
print(f"{exc_type = }")
print(f"{type(exc_type) = }")
print(f"{exc_val = }")
print(f"{type(exc_val) = }")
print(f"{exc_tb = }")
print(f"{type(exc_tb) = }")
print("exit")
with Foo() as foo:
raise ValueError("uh-oh")
enter
exc_type = <class 'ValueError'>
type(exc_type) = <class 'type'>
exc_val = ValueError('uh-oh')
type(exc_val) = <class 'ValueError'>
exc_tb = <traceback object at 0x7f363b472f40>
type(exc_tb) = <class 'traceback'>
exit
Traceback (most recent call last):
File "main.py", line 18, in <module>
raise ValueError("uh-oh")
ValueError: uh-oh
** Process exited - Return Code: 1 **
Press Enter to exit terminal
You can see that the value is simply a type object (or just a class). The value of the exception in this case is an instance of the ValueError class, and the traceback is something we can use to determine specifically where the exception happened.
dictionary¶
Literal declaration¶
Function declaration¶
dict merging¶
Dict unpacking¶
(this is my preferred way of doing it, for no good reason in particular):
Using .update()¶
Using union¶
This requires Python >= 3.9
async¶
async functions¶
Defined as
async with¶
This context manager calls the __aenter__ and __aexit__ magic methods instead of the regular __enter__ and __exit__. This is useful when your enter/exit methods rely on potentially expensive external calls.