Working with the Python REPL and IPython
Interactive exploration, tab completion, ?, %timeit, and shell commands in IPython.
Working with the Python REPL and IPython is a free Learn AI with Python lesson on CoddyKit — lesson 4 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Learn AI with Python learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
The Interactive Workflow
The REPL (Read-Eval-Print Loop) lets you experiment line by line. IPython is a supercharged REPL with introspection, magics, and history, and it powers Jupyter kernels.
pip install ipython
ipythonDocstrings with a Single ?
Append ? to any object to see its docstring and signature, no need to open documentation in a browser.
import numpy as np
np.arange?
# shows signature and docstring for arangeSource with Double ??
Use ?? to view the actual source code of a function (when written in Python). Great for understanding library internals.
def scale(x, factor=2):
return x * factor
scale??
# prints the function sourceTiming with %timeit
The same %timeit magic from notebooks works in IPython. It auto-tunes the number of loops for a stable measurement.
%timeit [i**2 for i in range(1000)]Running Scripts with %run
%run script.py executes a file inside the current session, leaving its variables available afterward for inspection.
%run analysis.py
print(results) # variable defined inside analysis.pyThe Last Result: _
A single underscore _ holds the most recent output. Handy to reuse a result you forgot to assign.
In [1]: 10 * 5
Out[1]: 50
In [2]: _ + 1
Out[2]: 51Older Results: __ and ___
Two underscores __ give the second-to-last result, three ___ the third-to-last. You can recover the last three outputs.
In [1]: 1
In [2]: 2
In [3]: 3
In [4]: ___, __, _
Out[4]: (1, 2, 3)Output by Number
Every numbered output is stored. Out[3] (or _3) retrieves the result of cell 3 specifically.
In [3]: 7 * 6
Out[3]: 42
In [4]: Out[3] + 8
Out[4]: 50Tab Completion
Press Tab after a dot to list an object's attributes and methods. This makes APIs discoverable without memorizing them.
import pandas as pd
pd.read_<TAB>
# read_csv read_excel read_json read_parquet ...Listing Variables with %who
%who lists names defined in the session; %whos adds type and value details for a richer overview.
x = 5
name = "ada"
%who
# name x
%whos
# Variable Type Data/InfoShell and History
IPython also runs shell commands with ! and recalls input history with %history, so you can copy earlier experiments.
!ls *.csv
%history -n 1-5 # show first five inputs with numbersQuick Check
Test your IPython introspection skills.
Recap
IPython power tools:
obj?docstring,obj??source%timeitbenchmarking,%runexecute a file_,__,___recall last three results;Out[n]any resultTabcompletion for discovery%who/%whoslist variables
Frequently asked questions
Is the “Working with the Python REPL and IPython” lesson free?
Yes — the full text of “Working with the Python REPL and IPython” is free to read here on the web, and the Learn AI with Python course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Learn AI with Python course, upgrade to CoddyKit PRO.
What will I learn in “Working with the Python REPL and IPython”?
Interactive exploration, tab completion, ?, %timeit, and shell commands in IPython. You practise Learn AI with Python with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start Learn AI with Python?
No prior experience is required. Learn AI with Python on CoddyKit is structured for beginners through advanced learners; this is — lesson 4 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Working with the Python REPL and IPython” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this Learn AI with Python lesson?
Yes. Every Learn AI with Python lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Virtual Environments and pip
- Jupyter Notebooks for Data Science
- Python Data Types for Data Science
- Working with the Python REPL and IPython