CodeUtility
Making your developer's life easier!
Inspect and compare

JSON Viewer

Explore JSON as an interactive tree: expand and collapse nodes, search, and copy the path to any value.

  • Runs in your browser
  • Instant results
  • Free, no sign-up
Loading the tool…

How to use the JSON Viewer

  1. Paste JSON or load a file.
  2. Expand or collapse nodes and search for keys or values.
  3. Click a key to copy its path, such as data.items[0].name.

Frequently asked questions

How large a JSON file can I open?

Several megabytes work smoothly. Very large files depend on your device memory, since everything runs in the browser.

Is my JSON uploaded?

No. Parsing and display happen entirely in your browser.

What path format is copied?

JavaScript-style paths, for example data.users[2].email, which also work in most JSONPath tools with a leading $.

JSON ValidatorValidate JSON and see the exact line and column of any error. Format or minify valid JSON and get stats such as depth and key count. JSON DiffCompare two JSON documents by structure, not text. See added, removed and changed values with their paths, ignoring key order and formatting. JSON to CSV ConverterConvert JSON arrays to CSV with nested objects flattened into columns. Choose the delimiter, preview the table and download a CSV that opens in Excel.

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