In [ ]:
def txt_to_ls(filename: str) -> list[str]:
    """
    Split a plain text file given by filename into lines, and return a list of
    those lines. The newline/line break (\n) *is* included in the returned
    strings.
    """
    with open(filename) as fh:
        return list(fh)
    
assert txt_to_ls("a-tale-of-two-cities.txt")[10] == "Title: A Tale of Two Cities\n", "Title line"
assert txt_to_ls("a-tale-of-two-cities.txt")[106] == "It was the best of times, it was the worst of times, it was the age of\n", "Famous first line"
In [ ]:
def ls_to_txt(filename: str, lines: list[str], add_newline=True) -> list[str]:
    """
    Write a list of strings, given by lines, to a text file, given by filename.
    If add_newline is True, the default, then a newline is added after each
    string. Returns the list of strings written, with the newlines if
    applicable.
    """
    def concat_newline(s: str) -> str:
        """
        Return s concatenated to a newline.
        """
        return s + "\n"
    if add_newline:
        lines = list(map(concat_newline, lines))
    with open(filename, "w") as fh:
        fh.writelines(lines)
    return lines

assert ls_to_txt("tmp.txt", ["Hello"])[0] == "Hello\n", "Newline added by default"
assert ls_to_txt("tmp.txt", ["Hello"], add_newline=False)[0] == "Hello", "Newline not added with add_newline=False"
In [ ]:
lines = txt_to_ls("a-tale-of-two-cities.txt")
lines.sort(key=len)
ls_to_txt("out.txt", lines, add_newline=False)
print("Hi")

Hi
In [ ]:
import numpy as np
import math
print(np.sin(1))
print(math.sin(1))
print(np.abs(-42))
print(abs(-42))
print(np.sum([2, 4, 6, 0, 1]))
print(sum([2, 4, 6, 0, 1]))

0.8414709848078965
0.8414709848078965
42
42
13
13
In [ ]:
print([1, 2, "3", 4, (5, 6)])

[1, 2, '3', 4, (5, 6)]
In [ ]:
arr = np.array([2, 4, 6, 0, 1])
print(arr)
arr = np.array([1, 2, 3.14159])
print(arr)
arr = np.array([3.14159, "3.14159"])
print(arr)

[2 4 6 0 1]
[1.      2.      3.14159]
['3.14159' '3.14159']
In [ ]:
arr = np.array([1, 2, 3.14159])
print(arr)
print(arr.dtype)
arr = np.array([1, 2, 3])
print(arr.dtype)

[1.      2.      3.14159]
float64
int64
In [ ]:
arr = np.array(["one", "two", "three"])
arr[0] = "seventy"
print(arr.dtype)
print(arr)

<U5
['seven' 'two' 'three']
In [ ]:
x = np.array([1.1, 2.2, 3.3])
y = np.array([2.0, 4.0, -1.0])
print(x * 2)
print(x - 1)
print(x * y)
print(x < 3)

lst = [1, 2, 3]
print(lst * 2)
print(lst)

[2.2 4.4 6.6]
[0.1 1.2 2.3]
[ 2.2  8.8 -3.3]
[ True  True False]
[1, 2, 3, 1, 2, 3]
[1, 2, 3]
In [ ]:
x = np.array([1.1, 2.2, 3.3])
q = x
x *= 2
print(x)
print(q)
x -= 1
print(x)
x *= y
print(x)

for idx in range(len(x)):
    x[idx] = x[idx]*2
print(x)

a = 42
a *= 3
print(a)

[2.2 4.4 6.6]
[2.2 4.4 6.6]
[1.2 3.4 5.6]
[ 2.4 13.6 -5.6]
[  4.8  27.2 -11.2]
126
In [ ]:
x = np.array([1, 2, 3])
y = x / 2
print(y)
x /= 2
print(x)

[0.5 1.  1.5]

---------------------------------------------------------------------------
UFuncTypeError                            Traceback (most recent call last)
Input In [45], in <cell line: 4>()
      2 y = x / 2
      3 print(y)
----> 4 x /= 2
      5 print(x)

UFuncTypeError: Cannot cast ufunc 'divide' output from dtype('float64') to dtype('int64') with casting rule 'same_kind'
In [ ]:
print(np.array([3.14159], dtype=np.float32))

[3.14159]
In [ ]:
y = np.array([2.0, 4.0, -1.0])
print(np.sin(y))
print(math.sin(y))

[ 0.90929743 -0.7568025  -0.84147098]

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Input In [54], in <cell line: 3>()
      1 y = np.array([2.0, 4.0, -1.0])
      2 print(np.sin(y))
----> 3 print(math.sin(y))

TypeError: only size-1 arrays can be converted to Python scalars
In [ ]: