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Visualizers

Mermaid Live Editor

Turn plain text into diagrams with Mermaid, with a live preview, examples and export.

  • Runs in your browser
  • Instant results
  • Free, no sign-up
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How to use the Mermaid Live Editor

  1. Write Mermaid code or start from an example.
  2. Watch the diagram update as you type; errors show the problem line.
  3. Download SVG or PNG, or copy a share link that contains the diagram.

Frequently asked questions

What is Mermaid?

A text syntax for diagrams. GitHub, GitLab, Notion and many docs tools render it, so diagrams live next to your code.

Which diagram types are supported?

Flowcharts, sequence, class, state, ER, Gantt, pie, mind maps, git graphs and user journeys.

Is my diagram stored on a server?

No. It renders in your browser. Share links carry the diagram inside the URL itself.

Markdown PreviewWrite Markdown with a live side-by-side preview. GitHub Flavored Markdown, tables and code blocks. Your draft is saved in this browser. JSON VisualizerSee JSON as a graph of connected cards. Pan, zoom, search and click to copy paths. Export the diagram as SVG. Runs in your browser. Regex VisualizerVisualize regular expressions as railroad diagrams. See groups, alternatives, repeats and lookarounds, and test a sample string. Export SVG.

Practice Python with coding challenges

Solve hands-on problems right in this editor: run the sample tests, submit, and get an AI code review.

All Python challenges
Easy

Average of Three

Average three whole numbers.

You'll learn ArithmeticDivision
BeginnerLearning-pathVariables
Python C++ C#
1 solved
View solutions (1)
Easy

Rectangle Perimeter

Compute the perimeter of a rectangle from its sides.

You'll learn ArithmeticReturn values
BeginnerLearning-pathVariables
Python C++ C#
1 solved
View solutions (1)
Medium

One Generation of a Genetic Algorithm

Breed the next generation of bit strings with tournament selection, single-point crossover and mutation.

You'll learn Genetic algorithmsEvolutionary search
OptimizationSimulationai
Python C++ C#
0 solved
No solutions yet
Easy

Epsilon-Greedy Multi-Armed Bandit

Balance exploration and exploitation on a multi-armed bandit with epsilon-greedy action selection.

You'll learn Explore vs exploitBandits
Reinforcement learningaimachine learning
Python C++ C#
0 solved
No solutions yet
Easy

Markov Chain State Distribution

Propagate a probability distribution through a Markov chain's transition matrix for a number of steps.

You'll learn Markov chainsProbability
Simulationaimath
Python C++ C#
0 solved
No solutions yet
Medium

Value Iteration

Compute how valuable each state of a Markov decision process is by repeatedly applying the Bellman optimality update.

You'll learn Bellman equationMDPs
Reinforcement learningaimachine learning
Python C++ C#
0 solved
No solutions yet
Medium

Q-Learning Updates

Apply the Q-learning update to a stream of experiences and watch rewards flow back to earlier states.

You'll learn Q-learningDiscounted rewards
Reinforcement learningaimachine learning
Python C++ C#
0 solved
No solutions yet
Medium

Alpha-Beta Pruning

Evaluate a game tree with minimax and alpha-beta pruning, and count how many leaves the search really looks at.

You'll learn Alpha-beta pruningGame search
RecursionTreesai
Python C++ C#
0 solved
No solutions yet
Medium

Minimax Tic-Tac-Toe

Pick the perfect tic-tac-toe move by searching the whole game tree with minimax.

You'll learn MinimaxGame trees
Recursionai
Python C++ C#
0 solved
No solutions yet
Medium

A* Search on a Weighted Grid

Find the cheapest path across a grid of terrain costs with A*, the search algorithm behind game and robot pathfinding.

You'll learn A* searchHeuristics
GraphsGridsShortest-pathai
Python C++ C#
0 solved
No solutions yet
Medium

Temperature and Top-K Sampling

Choose the next token like a language model does: keep the top k logits, apply temperature, and sample.

You'll learn Text generationSampling
aimachine learning
Python C++ C#
0 solved
No solutions yet
Hard

Multi-Head Self-Attention

Project the input into queries, keys and values, run attention in several heads in parallel, and combine them.

You'll learn Multi-head attentionMatrix projections
aimachine learning
Python C++ C#
0 solved
No solutions yet