git jupyter notebook matrix multiplication tensorflow machine learning example
install programs
git clone activate virtual environments
python -m venv venv
venv/Scripts/activate
install requirements using pip
try environments
1
2
1+2
1 + 2
None
print(None)
print(1)
print(1+2)
print(1, 2)
print
import sys
print(sys)
print(sys.version)
def mean(a, b)
mean
mean(3, 4)
2 + mean(3, 4) + 5
1 + 2 * 3 + 5
(1 + 2) * (3 + 5)
# this is a comment
mean(3, 4) # will be evaluated as the average of 3 and 4
topics covered
topics exposed
types
type(1)
type(2)
type(2.0)
type(3/2)
type(3.0/2)
type(0.2)
type(.2)
type("3")
type('3')
type("hello")
type([3, 4])
sum([3,4])
type(sum)
sum(sum[3,4])
type(None)
type("None")
type(print)
def mean(a, b):
return (a + b) / 2
type(mean)
type(mean(1, 2))
class dummy:
pass
import sys
type(sys)
type(sys.version)
type(dummy)
type(True)
type(False)
type(print("hi"))
type(int("3"))
type(float("3"))
type(str(3))
3 + 2
"3" + 2
float("3") + 2
int("3") + 2
"3" + str(2)
topics covered
topics exposed
arithmetic operators
2**3
10%2
10/3
10//3
"hi"*3
"hi" + "hi"
comparison operators
(3 == 4) == False
3 == False
3 + 4 > 2
2 + 1 <= 2
3 != 4
assignment operators
a = 7
c = b = a + 1
d, e = a, b
c += 1 # c = c + 1
d *= 2
a //= 3
logical operators
False and False
False or True
False and 3
False or 3
None and 3
None or 3
print("Hello") and print("Hi")
print("Hello") or print("Hi")
identity operators
3 == 3.0
3 is 3.0
not 3.0
not False
membership operators
5 in [2, 5, 6]
3 in [2, 5, 6]
3 not in [2, 5, 6]
bitwise operators
a = 60 # 0000 0011 1100
b = 13 # 0000 0000 1101
a&b # 0000 0000 1100 - binary and
a|b # 0000 0011 1101 - binary or
a^b # 0000 0011 0001 - binary xor
~a # 1111 1100 0011 - binary 2's complement
a >> 4 # 0000 0000 0011 - binary left shift
b << 4 # 0000 1101 0000 - binary right shift
ternery operator
a = "same" if 3==4 else "different"
examples
(lambda x: x + 1)(4)
dir()
__iter__()__next__()yieldnext()print('r:')
r = range(4)
for i in r:
print(i)
def gen():
yield 1
yield 2
yield 3
yield 7
print('\ng1:')
g1 = gen()
for i in g1:
print(i)
print('\ng2:')
g2 = gen()
print(next(g2))
print(next(g2))
print(next(g2))
print(next(g2))
print(next(g2))
def fibo(n):
if n == 1:
return 1
if n == 2:
return 1
return fibo(n - 2) + fibo(n - 1)
for i in range(10):
print(fibo(i+1))
mydict = {'a': 3, 'b': 4, 'c': 5}
mydict['a']
keyset = set(mydict)
myset = {}
for k in mydict:
myset.add(mydict[k])
mylist = []
for k in mydict:
mylist.append(k * mydict[k])
mylist[0]
mytuple = tuple(mylist)
new_list = [expression(i) for i in old_list if filter(i)]x1 = [i for i in range(10)]
# [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
x2 = [i for i in range(10) if i % 2 == 0]
# [0, 2, 4, 6, 8]
x3 = [x**2 for x in range(10)]
# [0, 1, 4, 9, 16, 25, 36, 49, 64, 81]
list1 = [3,4,5]
x4 = [item*3 for item in list1]
# [9,12,15]
listOfWords = ["this","is","a","list","of","words"]
x5 = [ word[0] for word in listOfWords ]
# ['t', 'i', 'a', 'l', 'o', 'w']
string = "Hello 12345 World"
x6 = [x for x in string if x.isdigit()]
# ['1', '2', '3', '4', '5']
x7 = [x*2 for x in range(10) if x%2==0]
# [0, 4, 8, 12, 16]
__init____add____call__examples
class dummy():
def __call__(self):
print("Hello")
d = dummy()
d()
examples
with clause and file IOexamples
examples