10 JSON Mistakes Developers Make (And How to Fix Them)

JSON looks simple. It is just curly braces, square brackets, and key-value pairs. Yet JSON-related bugs consume a disproportionate amount of debugging time across teams of every size. The format's strict specification leaves no room for the shortcuts that JavaScript, Python, and other languages allow in their native object literals. Here are the ten mistakes that show up most often in real codebases, along with concrete fixes for each one.

1. Using Single Quotes Instead of Double Quotes

JavaScript happily accepts single-quoted strings, so developers copy object literals into JSON files without switching to double quotes. The JSON specification requires double quotes for both keys and string values. A file containing {'name': 'Alice'} will fail every JSON parser. The fix is straightforward: replace all single quotes with double quotes, or paste your data into a JSON Formatter that will flag the problem instantly.

2. Trailing Commas

Modern JavaScript engines ignore trailing commas in arrays and objects. JSON does not. This is probably the single most frequent JSON error in configuration files. The array ["red", "green", "blue",] is invalid JSON. Remove the final comma. If you are generating JSON programmatically, make sure your serialization logic does not append a comma after the last element.

3. Including Comments

Developers who work with YAML, TOML, or JSONC often add comments to plain JSON files out of habit. Standard JSON has no comment syntax. Neither // line comments nor /* */ block comments are allowed. If your configuration format needs annotations, consider switching to YAML. You can validate YAML files with a YAML Validator to ensure they are well-formed after conversion.

4. Unquoted Keys

In JavaScript, you can write {name: "Alice"} because the engine treats name as a string automatically. In JSON, every key must be a double-quoted string: {"name": "Alice"}. This mistake often appears when developers hand-write JSON or copy object literals from a browser console.

5. Wrong Data Types for Numbers

JSON numbers must not have leading zeros (except for 0 itself and decimal numbers like 0.5). The value 007 is invalid. Additionally, special values like NaN, Infinity, and -Infinity are not valid JSON numbers. If your application produces these values, you need to serialize them as strings or replace them with null before converting to JSON.

6. Forgetting to Escape Special Characters

String values in JSON must escape certain characters: backslashes, double quotes, and control characters like newlines and tabs. A raw newline character inside a JSON string breaks the parser. Use \n for newlines, \t for tabs, and \\ for literal backslashes. When dealing with file paths on Windows, this is a constant source of errors.

7. Confusing null, "null", and Missing Fields

There is a meaningful difference between a key set to null, a key set to the string "null", and a key that is absent entirely. Many APIs treat these three cases differently. Sending {"middle_name": "null"} tells the server the person's middle name is literally the four-letter word "null." Sending {"middle_name": null} means the field exists but has no value. Omitting the key means it was not provided. Be deliberate about which you intend.

8. Encoding Issues with Unicode

JSON must be encoded in UTF-8 (or UTF-16 or UTF-32, though UTF-8 dominates). Problems arise when files are saved with other encodings like Latin-1 or Windows-1252. Characters with accents, CJK characters, or emoji can appear as garbled text or cause parse failures. Always save your JSON files as UTF-8 without a byte-order mark (BOM). Most modern editors default to this, but legacy systems may not.

9. Deeply Nested Structures Without Schema Validation

As APIs evolve, JSON payloads tend to grow deeper and more complex. Without schema validation, consumers have no way to know whether a nested field changed type or moved to a different location. JSON Schema lets you define the expected shape of your data, including required fields, allowed types, and nesting depth. Catching structural changes early prevents cascading failures downstream.

10. Mixing JSON with CSV When Tabular Data Is Needed

Developers sometimes force tabular data into JSON arrays of objects when a simple CSV would be more appropriate. If your data is a flat table with consistent columns, CSV is smaller, faster to parse, and easier to open in a spreadsheet. The CSV to JSON converter makes it easy to switch between the two formats depending on your use case, so you do not have to commit to one format permanently.

How to Catch These Mistakes Early

The fastest way to prevent JSON errors from reaching production is to validate early and often. Paste suspicious payloads into a JSON Formatter to check for syntax errors and see the structure clearly. When converting between formats, use dedicated tools rather than manual find-and-replace. And when your team's JSON structures become complex, invest the time to write JSON Schema definitions that document the expected shape of every payload.

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