Guides
Practical writing about the formats this tool reads — what the syntax actually requires, where conversions lose data, and which errors account for most of the time people lose to them.
Articles
- JSON, explained properly
- JSON is a text format for structured data with exactly six types — object, array, string, number, boolean and null — and a deliberately small grammar: no comments, no trailing commas, no dates, and no way to write Infinity or NaN. Read it
- JSON vs YAML
- Use JSON when machines are exchanging data and YAML when humans are editing configuration. JSON is unambiguous and tedious to write; YAML is comfortable to write and has enough ambiguity to cause genuine outages. Read it
- YAML, from the syntax up
- YAML is an indentation-based format for data that humans write by hand. Every JSON document is already valid YAML; what YAML adds is comments, multi-line strings, references between values, and a type system that guesses — which is where almost every YAML bug comes from. Read it
- Writing a JSON Schema
- A JSON Schema is itself a JSON document that describes the shape another document must have. You build one by declaring a type, listing the properties, marking which are required, and then tightening each property until invalid data cannot pass. Read it
- JSONPath, with worked examples
- JSONPath is a query language for JSON, in the way XPath is one for XML. An expression starts at the root, walks down through keys and array indices, and returns every value that matches — which may be none, one, or many. Read it
- How to view a JSON file
- To read a JSON file, open it in a browser (drag it into a tab), a code editor like VS Code, an online viewer, or the command line with jq — the right choice depends on the file’s size, how confidential it is, and whether you need to search it or just look at it. Read it
- How to validate JSON
- There are three separate questions behind "is my JSON valid": does it parse, does it mean what you intended, and does it match the shape a consumer expects — and only the first is answered by a syntax check. Read it
- Converting CSV to JSON without corrupting your data
- CSV to JSON is a simple conversion with five predictable failure modes: leading zeros stripped from identifiers, commas inside quoted fields splitting rows, large numbers losing precision, encodings misread, and empty cells becoming the wrong empty value. Read it
- Alternatives to the popular online JSON editors
- The right alternative depends on what is wrong with the tool you have: for privacy, pick something that parses in your browser; for large files, pick jq; for a cleaner interface, several options remove the advertising; and for features a tree cannot give you, pick a tool with table, graph and diff views. Read it