Python 3

uninstall Python 3 from Mac

Make sure we know the version of Python 3: python3 --version
Delete the frameworks: sudo rm -rf /Library/Frameworks/Python.framework/Versions/3.7, here we need to change the 3.7 into the version we want to uninstall
Delete the applications: sudo rm -rf /Applications/Python\ 3.7/, here be careful with the space between Python and 3.7, and change the 3.7 into the version we want to uninstall
Remove the system links in /usr/local/bin/ that point to the version that we want to remove
Check the shell configuration files to make sure no python3.7 path is still in use, e.g., ~/.bash_profile, or ~/.zshrc

interesting built-in functions and topics

five kinds of parameter

positional-or-keyword: this is the default type of parameter, e.g., all the parameters in

def function(arg1, arg2='test')

positional-only: argument supplied only by position, e.g., po_only1 and po_only2 in

def function(po_only1, po_only2, /, arg1, arg2='test')

keyword-only: argument supplied only by keywork, e.g., kw_only1 and kw_only2 in

def function(arg1, arg2, *, kw_only1, kw_only2)

var-position: arbitrary sequence of positional parameters, e.g., *arg in

def function(arg1, arg2, *args)

var_keyword: arbitrarily many keyword arguments, e.g., **kwargs in

def function(arg1, arg2, **kwards)

built-in data types

list

sort

Definition:

sort(*, key=None, reverse=False)

Example:

a = [(1, 2, 4), (3, 2, 5), (2, 4, 2)]
a.sort(key=lambda x:x[0], reverse=True)
# a will be [(3, 2, 5), (2, 4, 2), (1, 2, 4)]

This method sorts the list in place, using only < comparisons between items.

dict

get

Definition:

get(key[, default])

Return the value for key if key is in the dictionary, else default. If default is not given, it defaults to None, so that this method never raises a KeyError.

setdefault

Definition:

setdefault(key[, default])

If key is in the dictionary, return its value. If not, insert key with a value of default, and return default. default defaults to None.

itertools

collections

collections.namedtuple

Create tuple subclass with named fields, which is indexable and iterable.

Definition:

collections.namedtuple(typename, field_names, *, rename=False, defaults=None, module=None)

Examples:

from collections import namedtuple
Person = namedtuple('person', ['name', 'age', 'gender'])
person_a = Person('david', 18, 'male')
person_b = Person._make(['john', 20, 'male'])
person_b_dict = person_b._asdict()
person_a_replaced = person_a._replace(name='steven')
fields = person_a._fields
fields = Person._fields # can be class method or instance method
field_defaults = Person._field_defaults # dictionary
person_a_name = getattr(person, 'name')
# person_a[0] is 'david'
# person_a.age is 18
# name, age, gender = person_b
# person_b_dict is {'name':'john', 'age': 20, 'gender': 'male'}
# fields is ('name', 'age', 'gender')

Notes:

field_names can also be 'name age gender' or 'name, age, gender'.
defaults are applied to the rightmost parameters.
No per-instance dictionaries are needed, so it requires no more memory than tuple, i.e. __slots__ = ().

heapq

bisect

functools

functools.lru_cache()

Decorator to wrap a function with a memoizing callable that saves up to the maxsize most recent calls. It can save time if the function is called multiple times.

Definition:

@lru_cache(user_function)
@lru_cache(maxsize=128, typed=False)

Examples:

@lru_cache
def count(input_string):
    return input_string.count('1')
# this will leaves maxsize at its default
count.cache_parameters()
>>> {"maxsize": 128, "typed": False}
count.cache_info()
>>> CacheInfo(hits=3, misses=8, maxsize=32, currsize=8)
count.cache_clear()
# clear the cache

Notes:

LRU: Least Recent Used.
A dictionary is used to cache the results, so the positional and keyword arguments must be hashable.
If maxsize is None, lru function is disabled.
If typed is True, f(3) and f(3.0) will be cached as distinct results.

glob

Unix style pathname pattern expansion.

glob.glob

Returns a possibly empty list containing file names matching pathname.

Definition:

glob.glob(pathname, *, recursive=False)

Example:

result = glob.glob("/usr/david/home/test/*.py")

Notes:

If recursive is True, pattern ** will match any files, zero or more directories, symbolic links, and subdirectories, recursively.

os.path

os.path.exists

Return True if path is an exsiting path or an open file descriptor, False if a broken symbolic link.

Definition:

os.path.exists(path)

Example:

result = os.path.exists('./abc/test.py')

Notes:

path can be an integer (open file descriptor), a path-like object, or a string.

os.path.isfile

Return True if path is an existing regular file. It follows symbolic links, so both isfile and islink can be true for the same path.

Definition:

os.path.isfile(path)

Example:

result = os.path.isfile('./abc/test.py')

Notes:

path can be a path-like object or a string.

os.path.isdir

Return True if path is an existing directory. It follows symbolic links, so both isdir and islink can be true for the same path.

Definition:

os.path.isdir(path)

Example:

result = os.path.isdir('./abc/testdir')

Notes:

path can be a path-like object or a string.

os.path.islink

Return True if path refers to an existing directory entry that is a symbolic link. Always False if symbolic links are not supported by the Python runtime.

Definition:

os.path.islink(path)

Example:

result = os.path.islink('./abc/test')

Notes:

path can be a path-like object or a string.

os.path.join

Join one or more path components intelligently.

Definition:

os.path.join(path, *paths)

Example:

os.path.join('./abc', 'project2', 'abc')
>>> './abc/project2/abc'

Notes:

path and paths can be a path-like object or a string.

os.path.split

Split the pathname path into a pair, (head, tail) where tail is the last pathname component and head is everything leading up to that.

Definition:

os.path.split(path)

Example:

os.path.split('./abc/project2/abc.py')
>>> ['./abc/project2', 'abc.py']

Notes:

path can be a path-like object or a string.

csv

csv.reader

Return a reader object which will iterate over lines in the given csvfile.

Definition:

csv.reader(csvfile, dialect='excel', **fmtparams)

Example:

with open('test.csv', 'r', newline='') as f:
    reader = csv.reader(f)
    for row in reader:
        print(row)
        print(row[0], row[1]) # each row is a list of strings

Notes:

csvfile can be any object that supports iterable protocol and returns a string when its __next__ method is called.

csv.writer

Return a writer object responsible for converting the user’s data into delimited strings on the given file-like object.

Definition:

csv.writer(csvfile, dialect='excel', **fmtparams)

Example:

with open('writer.csv', 'w', newline='') as f:
    writer = csv.writer(f, delimiter=' ', quotechar='|', quoting=csv.QUOTE_MINIMAL)
    writer.writerow([1, 2, 3, 'abc', 'abass'])

Notes:

csvfile can be any object with a write() method.

argparse

Parser for command-line options, arguments and sub-commands.

ArgumentParser

Create a new ArgumentParser object.

Definition:

class argparse.ArgumentParser(prog=None, usage=None, description=None, epilog=None, parents=[], formatter_class=argparse.HelpFormatter, prefix_chars='-', fromfile_prefix_chars=None, argument_default=None, conflict_handler='error', add_help=True, allow_abbrev=True, exit_on_error=True)

Example:

parser = argparse.ArgumentParser(description="text to display before the argument help", epilog="text to display after the argument help", parents=[parser1, parser2])

add_argument

Define how a single command-line argument should be parsed.

Definition:

ArgumentParser.add_argument(name or flags...[, action][, nargs][, const][, default][, type][, choices][, required][, help][, metavar][, dest])

Example:

parser.add_argument('-f', '--foo')
parser.add_argument('bar')
parser.add_argument('--setnumber', action='store_const', const=42)
parser.add_argument('--trainmode', action="store_true")
parser.add_argument('--addnumber', action="append")
parser.add_argument('--int', dest="types", action="append_const", const=int)
parser.add_argument('--str', dest="types", action="append_const", const=str)
parser.add_argument('--verbose', '-v', action="count", default=0)
parser.add_argument('--version', action="version", version="%(prog)s 2.0")
parser.add_argument('--plot', action="extend", nargs="+", type=str)

Notes:

name or flags: optional argument: '-f', '--foo', positional argument: bar.
action defaults to store, other options are: store_const, store_true, store_false, append, append_const, count, help (automatically added to the parser), version, extend, and any Action subclass.
default defaults to None.
nargs have options: N (an integer, e.g., 1-item, 2-item list), '?' (zero or single item), '*' (zero or more items), '+' (1 or more items).
metavar can set the name to refer to for the optional arguments.
type can facilitate type conversion.

parse_args

Convert argument strings to objects and assign them as attributes of the namespace, then return the namespace.

Definition:

ArgumentParser.parse_args(args=None, namespace=None)

Example:

parser.parse_args(['testtext', '--foo', '1'])
>>> Namespace(bar='testtext', foo='1')
parser.parse_args("--addnumber 1 --addnumber 2".split())
>>> Namespace(addnumber=["1", "2"])
parser.parse_args("--int --str".split())
>>> Namespace(types=[<class 'int'>, <class 'str'>])
parser.parse_args("-vvv --trainmode".split())
>>> Namespace(verbose=3, trainmode=True)
parser.parse_args(["--version"])
>>> PROG 2.0
parser.parse_args("--plot train_acc --plot train_loss val_acc val_loss".split())
>>> Namespace(plot=["train_acc", "train_loss", "val_acc", "val_loss"])
parser.parse_args("--case=test")
>>> Namespace(case="test")
parser.parse_args("-n1")
>>> Namespace(n="1")
parser.parse_args("-sabcC")
>>> Namespace(s=True, a=True, b=True, c="C")
result.s
>>> True

Notes:

For long options (longer than a single character), '=' can be used to parse the argument string.
For short options, the option and its value can be concatenated.
For short options that don't require a value (or only the last one requires a value), they can be concatenated.

datetime

datetime.timedelta

Definition:

class datetime.timedelta(days=0, seconds=0, microseconds=0, milliseconds=0, minutes=0, hours=0, weeks=0)

Example:

t1 = datetime.timedelta(hours=1, seconds=1)
t1.total_seconds()
>>>  3601.0
t1.days, t1.seconds, t1.microseconds
>>> (0, 3601, 3601000)

datetime.date

Definition:

class datetime.date(year, month, day)

Example:

datetime.date.today() == datetime.date.fromtimestamp(time.time())
>>> True
d1 = datetime.date.today()
d1.year, d1.month, d1.day
>>> (2020, 12, 10)
d2 = d1.replace(day=d1.day+1)
d2 - d1
>>> timedelta(days=1)

datetime.time

Definition:

Example:

datetime.datetime

Definition:

class datetime.datetime(year, month, day, hour=0, minute=0, second=0, microsecond=0, tzinfo=None, *, fold=0)

Example:

Reference

How to Uninstall Python 3.7 Cleanly from Mac
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Python 3

uninstall Python 3 from Mac

interesting built-in functions and topics

five kinds of parameter

built-in data types

list

sort

dict

get

setdefault

itertools

collections

collections.namedtuple

heapq

bisect

functools

functools.lru_cache()

glob

glob.glob

os.path

os.path.exists

os.path.isfile

os.path.isdir

os.path.islink

os.path.join

os.path.split

csv

csv.reader

csv.writer

argparse

ArgumentParser

add_argument

parse_args

datetime

datetime.timedelta

datetime.date

datetime.time

datetime.datetime

Reference