Libraries

Libraries allow us to apply Python to real tasks. These are a few popular ones, but there are many.

Utilities

• collections

  Specialized containers: counting items, grouping with defaults, named tuples, fast queues.

  Counter counts[item] most_common() total() elements() update() subtract() + - & |

  defaultdict default_factory .get()

  namedtuple defaults= _make() _asdict() _replace() _fields _field_defaults

  deque append() appendleft() extend() extendleft() insert() pop() popleft() remove() clear() count() index() copy() rotate() reverse() maxlen=

  OrderedDict move_to_end() popitem() ==

  ChainMap new_child() .maps .parents

  User* wrapper UserDict UserList UserString

• datetime

  Calculating and formatting dates and times.

  date strftime() creating a specific date

  timedelta strptime() difference between two dates

• random

  Random numbers, random picks, shuffled order.

  randint()

  choice() shuffle() sample()

Data analysis

• csv

  Reading and writing spreadsheets.

  csv.writer

  csv.reader DictReader

• matplotlib

  Charts and plots: line, bar, and scatter, built directly from plain Python data.

  line plots labels and title multiple lines and a legend

  bar charts

  scatter plots

  subplots

  saving a figure

• NumPy

  Fast numeric arrays, with math applied to a whole array at once instead of item by item.

  array operations mean() boolean mask

  ndarray arange()

• pandas

  Tabular data: rows and columns, like a spreadsheet, built on top of NumPy.

  DataFrame

  working with a DataFrame sort_values() mean()

APIs

• json

  Reading and writing JSON data: nested dicts and lists, saved to a file or a string.

  json.dump()

  json.load() nested data

  json.loads()

• requests

  Fetching data over the internet, like asking a website or API for information.

  get() status_code json() params

  error handling

Image editing

• Pillow

  Opening, editing, and saving images, built around one Image object.

  why Pillow?

  Image opening and saving images basic operations image modes resize crop rotate and flip

  ImageOps common ImageOps functions

  ImageDraw shapes and lines

  ImageFont loading a font

  ImageColor converting color names

  ImageFilter applying a filter

  ImageEnhance enhancing an image

  ImageChops comparing and combining images

  convert() converting between formats

  ImageSequence looping over GIF frames

  putting it together an interactive filter tool

Computer vision

• OpenCV

  Real-time image and video analysis, built directly on NumPy arrays: color spaces, edge detection, face detection.

  reading, displaying, saving images imread() displaying a window saving a file

  drawing shapes and lines text

  color spaces cvtColor()

  CascadeClassifier detecting and labeling faces

  VideoCapture() reading frames

  basic operations resize() cropping rotating

  thresholding, edge detection Canny() threshold

  blurring gaussian blur

  contours finding and drawing contours

Desktop UIs

• Tkinter

  Creating desktop applications: text, buttons, dropdowns, forms, output, etc.

  Tk()

  Button Label Button Entry

  pack() pack grid

  configure() reading and changing options

  command command callbacks binding events

  ttk.Style customizing a style

  messagebox message boxes file dialogs

  winfo_width() winfo methods

  putting it together a simple form