Python Field Guide

Get started

• Workspace Setup

  What you need to write and run Python on your own computer.

  installing Python

  writing and running a .py file

  code editor comparison

  using the terminal

• Foundations

  The basic building blocks every Python program starts with: storing, displaying, and reading in values.

  variables naming printing reassigning types

  print()

  input()

  comments # """ FIXME TODO

  tips for getting started

Data types

• Basics

  Kinds of values, and what you can do with them.

  isinstance() type()

  integers + - * / ** //, %, divmod() += -= *= /= //= %= **= abs() int() boolean expressions

  floats + - * / ** //, %, divmod() += -= *= /= //= %= **= abs() float() round() boolean expressions

  strings + * += *= .capitalize() combine .count() .endswith() f-string .find() .format() in index[] .isalpha() .isdigit() .join() len() .lower() .replace() slice[:] .split() .startswith() step[::] str() .strip() .title() .upper() boolean expressions

  booleans == != > < >= <= and in is not or

  None is not boolean expressions

• Collections

  Multiple related values grouped into one container, so you can work with them together.

  isinstance() type()

  lists + .append() .clear() comprehension copy() count() create del .extend() in index index() .insert() item len() list operations list() loop max() min() .pop() remove() reverse() slice .sort() sorted() step sum() boolean expressions

  dictionaries access a value clear() copy() del() dict() .get() .items() key len() loop pop() popitem() update() value .values() boolean expressions

  tuples access items count() immmutable index index() len() loop max() min() packing sum() tuple operations tuple() unpacking boolean expressions

  sets | & - ^ add() clear() copy() discard() isdisjoint() issubset() issuperset() len() loop max() min() pop() remove() set() sum() update boolean expressions

Control flow

• Conditionals

  Lets a program make decisions, running different code depending on whether something is true.

  if, elif, else boolean expressions and, or, not

  match, case unpacking _ (wildcard) match with | case + if

  break, continue break continue

• Loops

  Repeats a block of code multiple times.

  for loop through a collection loop a set number of times range() enumerate() reversed() zip()

  while flag sentinel boolean expressions and, or, not counter and flag names

  break, continue break continue else

  common patterns accumulator counter nested loops

Code organization

• Functions

  Packages a block of code under a name, so it can be run again with different inputs.

  def return default parameter values keyword arguments docstrings

  *args, **kwargs *args **kwargs

  scope local vs global

  recursion

• Classes

  Bundles related data and functions into a reusable blueprint, so a program can create many similar objects without duplicating code.

  class __init__() self object methods

  inheritance super() overriding __init__() adding attributes and methods overriding methods

  polymorphism same method name, unrelated classes polymorphism via inheritance

External files and resources

• Modules & Imports

  Splitting code across files, and using someone else's code.

  import import from as import order packages nested paths

  your own module main guard

  module, package, library

• Reading & Writing Files

  Reads and writes text files to save data outside the program itself.

  open()

  read()

  write()

  append

Robust programming practices

• Style

  Conventions for writing standardized and readable Python code.

  PEP 8 naming docstrings order constants quote style indentation blank lines whitespace comments

  Pythonic patterns common patterns

  best practices type hints catch exceptions keep functions focused readable print output

  linter

  checklist

• Errors

  How to read error messages, handle them, and track down what went wrong.

  try, except exception types

  tracebacks how to read a traceback

  debugger set breakpoints run in debug mode what you can do at a breakpoint

  debugging strategies rubber duck debugging print debugging isolate the problem TODO, FIXME

Add-On Libraries

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

FAQ

Why learn to code yourself, if AI can do it for you?

	Learn to do it yourself	Have AI do it for you
Writing & struggling with code	Productive struggle is what builds understanding You can solve the problem again on your own Adapt the answer, and catch when it's wrong	Being handed the answer skips the friction that builds understanding If you skip that struggle, you won't develop the knowledge to solve the problem again, adapt the answer, or recognize when it's wrong.
Reading & verifying code	Understanding programming fundamentals makes AI more useful — you can read code you didn't write, and check it before you trust it Spot mistakes Understand why a solution works Communicate your problem to AI more effectively	Inefficient communciation with AI if you don't fully understand what's going on, and AI code can look correct while being wrong and insecure You can't tell why a solution works Researchers are already documenting this skill gap in students who rely on AI code generation before they've built their own foundation One Stanford study found developers using AI wrote less secure code — but were more confident it was secure
On the job	Employers are still hiring for understanding, not prompting Code review, debugging, and interviews all test whether you can reason about code And judge whether it's correct Learning to program on your own turns AI into a tool you can direct and verify, instead of one you're assuming got it right	AI will likely be available at work too — but it isn't what's being tested

References

• The friction that builds understanding — E. Bjork & R. Bjork, on desirable difficulties in learning
• Students who rely on AI code generation before building their own foundation — the documented skill gap
• Stanford study — developers using AI wrote less secure code, but were more confident it was secure

How to use AI to support your learning

swimlane-beta TB
    accTitle: Using AI to learn
    accDescr: AI walks you through setup before you start. You attempt each problem yourself with autocomplete off, then check whether you can explain why it works and whether it actually holds up — if either check fails, you describe what you tried rather than handing over your code, so AI explains the concept instead of fixing it, and you try again. Passing both checks means you understand it well enough for a practice problem, or for the code review, debugging, and interviews that are what your job actually tests.

    subgraph You
        you_help_setup(Need help setting up your computer to start programming?)
        you_have_project(Do you have a project to work on?)
        you_attempt(Attempt it yourself, autocomplete off so you understand everything that's there, utilize debug strategies)
        you_writeup(Stuck? Write out your problem: what you expect to happen, what you're observing, what you've tried already, see if this helps you process or rethink your strategy)
        you_finish("Learning to program means making mistakes, getting stuck, and eventually figuring things out and forming a mental model. That's the process that builds skills you can rely on to continue solving problems and detecting issues — ready for code review, debugging, and interviews, where AI won't be tested, your reasoning will. ")
    end

    subgraph AI
        ai_help_setup(AI can help guide you through setup on your exact device — which could make getting started more accessible for beginners)
        ai_suggest_problem(Suggests a problem based on your skill level, interests, and what you're trying to improve)
        explain(With that context AI can provide more targeted, efficient help. Don't just paste the code/error, ask AI to explain what a line does, or what an error means — an explanation to help you understand concepts, be clear you do NOT want it to write code, just explain)
    end


    ai_help_setup ~~~ you_help_setup
    ai_suggest_problem ~~~ you_have_project
    you_help_setup -->|Yes| ai_help_setup
    you_help_setup -->|No| you_have_project
    ai_help_setup --> you_have_project

    you_have_project -->|No| ai_suggest_problem

    you_have_project -->|Yes| you_attempt

    ai_suggest_problem --> you_attempt
    you_attempt <--> you_writeup
    you_attempt -->|Done!| you_finish
    you_writeup --> |still stuck?| explain
    explain --> you_attempt
    explain ~~~ you_finish

    %% Edge label text colored red if it leads into the AI lane, green
    %% if it leads into the You lane, matching the lane colors. This is
    %% linkStyle's "color" property (not background) — the one styling
    %% mechanism mermaid applies from inside its own closed shadow
    %% root, so it's the only thing that actually reaches the label.
    linkStyle 0 color:#a33f3f
    linkStyle 1 color:#3f6b52
    linkStyle 3 color:#3f6b52
    linkStyle 4 color:#a33f3f
    linkStyle 7 color:#3f6b52
    linkStyle 8 color:#a33f3f

    classDef you fill:#3f6b521f,stroke:#3f6b52,stroke-width:2px,color:#3f6b52
    classDef ai fill:#a33f3f1a,stroke:#a33f3f,stroke-width:2px,color:#a33f3f
    class you_writeup,you_help_setup,you_have_project,you_attempt,you_finish you
    class explain,ai_help_setup,ai_suggest_problem ai
    style You fill:#3f6b521f,stroke:#3f6b52,color:#3f6b52
    style AI fill:#a33f3f1a,stroke:#a33f3f,color:#a33f3f

Fig. 1a — when to use AI while learning to program

What is Python, and what is this guide?

Readable, and quick to write. Python is a general-purpose language built for code that's easy to read back later — even by someone who didn't write it. No compiling: write a .py file, run it directly.

• Shows up everywhere — web backends, data analysis and machine learning, automating repetitive tasks, scientific computing, quick glue scripts. Several of these are covered on this site's Libraries pages.
• The skills transfer. Variables, conditionals, loops, functions, classes — the fundamentals every language shares — read closer to plain English here, so you spend your effort learning to think like a programmer instead of fighting a stricter syntax. Once solid, those fundamentals carry over to whatever language you pick up next.
• Often the fastest language to write correct code in — even though it's not the fastest to run — which is why it's such a common first choice for a new project.

This guide. Python Field Guide is a free, in-browser reference — most code blocks are editable and runnable directly on the page.

• For learners — self-taught, students in an intro course, or anyone who wants one combined reference to work through start to finish, instead of a scattered pile of search results.