dsap-cli 1.1.4

CLI tool for practicing data structures and algorithms using spaced repetition.

Data Structures and Algorithms Practice (DSAP)

DSAP is a terminal-first CLI that schedules coding interview problems using the SM-2 spaced repetition algorithm,
helping you retain patterns long-term instead of forgetting them after solving once.

Why DSAP?

Most developers preparing for technical interviews solve algorithm problems once and never revisit them.

As a result, they forget patterns they previously learned.

DSAP solves this by scheduling problems using spaced repetition, a learning technique proven to improve
long-term memory.

Benefits:

• Retain algorithm patterns long-term
• Structured daily practice
• Automatic scheduling of reviews
• Focus on problems you’re about to forget

Instead of guessing what to practice next, DSAP tells you exactly what to review.

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Installation

# Recommended
uv tool install dsap-cli

# Alternatives
pipx install dsap-cli
pip install dsap-cli

Verify installation:

dsap --version

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Quick Start

# Load problems and set focus
dsap load blind75
dsap config preferred_set blind75

# Start practicing
dsap next

For the full workflow see:

USER_GUIDE.md

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Example Session

$ dsap next

Next Problem
Two Sum (Easy)

Category: Arrays
Set: Blind 75

Open problem in browser? [y/N]

After solving, rate your recall:

5 - Perfect
4 - Good
3 - Hard
2 - Incorrect but remembered idea
1 - Incorrect
0 - Complete blackout

DSAP then schedules the next review automatically.

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Commands

Command	Description
dsap next	Get next recommended problem
dsap review	Review due problems in a session
dsap list	List problems with filters
dsap stats	View progress and statistics
dsap load	Load curated problem sets
dsap config	Manage configuration
dsap reset	Reset problems and/or progress
dsap add	Add a custom problem

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Examples

# Filter by problem set
dsap next --set blind75
dsap review --set neetcode150

# Filter by difficulty
dsap next --difficulty Easy
dsap list --difficulty Hard

# Filter by category
dsap list --category "Dynamic Programming"

# Other options
dsap review --limit 5
dsap next --new-only
dsap list --due

# Reset progress
dsap reset --progress

# Reset a specific set
dsap reset --set blind75 --all

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Problem Sets

Set	Problems	Description
blind75	75	Core interview essentials
neetcode150	150	Comprehensive curriculum
grind75	75	Flexible study roadmap

dsap load --list
dsap load blind75
dsap load ./custom.yaml

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Configuration

dsap config --list
dsap config preferred_set blind75
dsap config daily_goal 5
dsap config preferred_difficulty Medium
dsap config auto_open_browser false
dsap config --reset

Setting	Default	Description
preferred_set	None	Default problem set
daily_goal	5	Target problems per day
preferred_difficulty	None	Filter by difficulty
show_hints	true	Show problem hints
auto_open_browser	true	Open problems in browser

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How It Works

DSAP implements the SM-2 (SuperMemo 2) spaced repetition algorithm.

After solving each problem, rate your recall from 0–5.

Rating	Meaning	Effect
5	Perfect	Interval grows
4	Good	Interval grows
3	Hard	Interval grows slowly
0-2	Forgot	Interval resets

Typical interval progression:

1 day → 6 days → 15 days → 38 days → 95 days

After several successful reviews, problems reappear only every few months.

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Data Storage

DSAP stores all data locally:

~/.dsap/
├── dsap.db
└── config.json

To completely uninstall:

uv tool uninstall dsap-cli
rm -rf ~/.dsap

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Development

git clone https://github.com/juma-paul/dsap-cli.git
cd dsap-cli

uv sync --all-extras
uv run pytest

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Changelog

See the full release history in:

CHANGELOG.md

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License

This project is open source and available under the MIT License.

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Built with Python, Click, Rich, Pydantic, and SQLite.

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