- Understand lambda functions
- Understand list methods map(), filter(), sort(), reduce()
- Understand ternary statements
- Understand list comprehensions
- Understand Try-Except error handling
- temporary, unnamed ("anonymous") functions
## typical function example
def add_one(x):
return x + 1
print(add_one(7)) # output would be 8
## lambda function example
add_two = lambda x : x + 2
print(add_two(7)) # output would be 9map()
- creates a new list, using a function that returns a new item
my_list = [1,2,3,4,5,6,7,8,9,10]
new_list = map(lambda item : item + 2, my_list)
for x in new_list:
print(x)
## [3,4,5,6,7,8,9,10,11,12]filter()
- creates a new list, using a function that returns a bool (True => include item in new list)
my_list = [1,2,3,4,5,6,7,8,9,10]
new_list = filter(lambda item : item % 3 == 0, my_list)
for x in new_list:
print(x)
## [3,6,9]reduce()
- creates a single value, using a function that aggregates values
import functools
my_list = [1,2,3,4,5,6,7,8,9,10]
sum = functools.reduce(lambda agg, item : agg + item, my_list)
print(sum)- inline if-statements
## if statement
x = None
y = 9
if y > 5:
x = "donuts"
else:
x = "bagels"
print(x)
## ternary statement
x = "donuts" if y > 5 else "bagels"
print(x)full_list = [a for a in range(10)]
print(full_list)
evens_list = [x for x in range(10) if x % 2 == 0]
print(my_list)
some_list = ["donuts" if x % 2 == 0 else "bagels" for x in range(10) if x % 3 == 0]
print(some_list)try:
a = 1
b = 2
c = "donuts"
d = a + b
print(d)
e = a + c # error
print(e)
except:
# handle exception
print("BOO! there was an error")
else:
# handle success
print("YAY! there was no error")
finally:
# always execute regardless of exception or success
print("donuts are yummy!")- Modules, libraries, frameworks, and packages are just code that someone else wrote ahead of time to make your life as a developer easier. There is no magic here - it's just meant to make your life easier and for you to make more robust applications
- There are a number of package managers to manage the different libraries we will use. The most popular package manager for Python is Pip, and the most popular (and default) package manager for Javascript is npm.
- You can find some very useful libraries here. We'll be using Django in the next few weeks. If you go the data science route, there are some data science heavy libraries like NumPy and Pandas
You can also write your own modules, which allows for you as the author to organize your code and group it together for ease of use. To put it very simply, a module is a file of Python code that you bring into other files. Let's take a look at an example:
## file1.py
def say_hello():
print('Hey there')
## file2.py
import file1
import file1 as anything
anything.say_hello()We just created two files: file1.py and file2.py. file1.py has a say_hello function. file2.py has nothing in it, but imports that file in as the name of the file and we can use all the methods in that file. We can also rewrite it as import file1 as anything and call anything.say_hello(). You can import anything into your file by providing the correct relative path to the file. More on that can be found under external resources.