JSON Format Full Guide: beautification, validation and common errors

1. JSON Format vs Minify vs Validate

In daily development, many people call "sort out JSON" in general terms, but at least three different things are actually happening: Format（Beautify）、Compression (minimize)andValidation (grammatical examination)。 The three are often done in the same tool, but with different objectives. The difference between them is less deviant and less "reforming" on the wrong data.

From an engineering perspective: the formatting service is "persons" - so that embedded, arrayed boundaries and empty fields are visible. The compression service is a "pipeline" — reducing the volume and noise caused by the gap. The verification service is "boundary" -- to confirm that this text is not allowed to be used. JSON.parse A sort of solver ate it. The most common consequence of mixing three things together is that the business fields are repeatedly adjusted in illegal texts, while always failing to solve the problem.

Yeah.Legal JSON, SETITTING AND COMDUCTION USE ONLY CHANGES BLOCK AND INDUSTRIES. Do not change the decomposition structure and value of the data。 If the tool is sorted, type converted or "smartly repaired" extra, semantics may be affected - these capabilities are identified separately, and not by default "aesthetic is no damage".

One minute to understand the difference.

The compressed interface returns often like this, and it's hard to clean up the structure in one line:

{"user":{"id":1001,"name":"Ada","roles":["admin","editor"]},"ok":true}

Once formatted, the hierarchy, array boundaries and field names are immediately clear:

{
  "user": {
    "id": 1001,
    "name": "Ada",
    "roles": ["admin", "editor"]
  },
  "ok": true
}

If the text itself is illegal, formatting will not "mix" the correct data, but will only expose the problem as soon as possible. This should be done by changing the syntax by reporting errors, not by changing the business field by feeling. The split between "can we" and "can we" and "do we not?" would increase the speed of the error.

When formatting / compression / verification is required

Not every time I see JSON, it's beautiful. Selecting actions by scene is more efficient and makes it less easy to submit debugging texts by error to a warehouse or interface. The following criteria are given as a priority to facilitate quick decision-making when you are connected, document writing and automating.

Pre-formatted scene

• The interface returns to a line, and you need to confirm embedded objects, arrays and empty fields.
• Profile or mock data are poorly readable and field names are frequently used for interlinking.
• The error message only says "Unexpected token" and requires a split and a comparison of the structure.
• Puts a backend sample in a document, Issue or evaluate material, hoping that someone else will read it.
• Checking the "fields are there, but the front end reads undefined" first check the real level path.

Pre-compression scene

• Network requestrs or local caches want to reduce the volume of blanks.
• Some systems require a single-line string or a written text for environment variables, key management systems.
• After batch generation of test data, you need to get a tight output before you can deliver it to the downstream script.
• Log collections are limited in length and the text needs to be reduced to preserve semantics.

The scenes that have to be verified first.

• Text copied from chat records, documents, mails, which may be mixed with Chinese quotation marks, notes or tail comma.
• Submit the "JavaScript Object that looks like JSON" as JSON.
• Automatic flow line luminaries, Webbook loads, third-party fixes need to be identified for resolution.
• Multi-person collaborativeally pasted configuration clips, with unknown origin, validated and merged.

3. Basic rules of lawful JSON (differentiation from JS objects)

Many of the verification failures are not miswritten, but rather miswritten. JavaScript Object LiteraryMistaken as strict JSon. The object that can run in the browser console is not equal to JSON.parse You can eat text. Understanding this border explains the majority of the confusion that I can do locally.

Invalid JSON example

{
  "name": "Example",
  "age": 30,
  "active": true,
  "tags": ["dev", "tools"],
  "meta": null
}

Common illegal writing

• Keynames are single or no quotes
• String with single quote
• One comma at the end of object/array
• Residues // Or block comment
• Undefined, NAN, function
• Brackets, brackets are not correctly closed

The constraints must be remembered.

• Object keynames and strings must be usedDouble Quote。
• Values can only be: objects, arrays, strings, numbers, booleans,null。
• (b) Do not support tail commas; The last member can't go back to comma.
• Standard JSON does not allow comments (part of the "JSONC" dialect says otherwise that interfaces and most of the solvers remain strictly JSON.
• Numbers should not be added to the lead zero; Quotes, back slashes in a string need to be correctly transposed.
• Don't put it on me. undefined Write it in JSON; Missing fields should normally be omitted or visiblely used null(Semanic terms to be agreed to with interfaces).

If your data is really an YAML, XML or a commentable configuration, you can change or wash it and then enter the JSON tool chain. KiloCell of cases JSON ↔ YAML Wait for the conversion of the portal to avoid repeating the "Formatization" point on the wrong format. Getting the format is faster than dying on a wrong grammar.

The pits associated with the loose JSON.

Some editors, configuration loaders or Node eco-tools support more liberal syntax (e.g. tail comma, notes). This doesn't mean online interfaces, browsers. JSON.parse Or a back-end framework of a strict model is acceptable. When exchanging data across the system, please be based on the strictest party: the external contract gives priority to the standard JSON, and for internal JSONC, remove the comment and then release it at the construction or distribution stage.

4. 1,000 cells online: step-by-step

Here. JSON Formattools Example. Processing is done locally in browsers and generally no extension is required; Suits ad hoc check-ups, document-processing and inter-sampling. The whole path can be completed in a few minutes, and the key is not to reverse the sequence.

1. Opens the toolbar. Enter /tools/dev/json-formatter , confirm that the input area is visible.
2. Dissembly before pasting. The site is also used to replace real token, mobile phone numbers, ID cards, internal domain names, etc. The public computer also avoids the long stay of production keys on the clipboard.
3. Paste text to the input area. This may be an interface response, a configuration clip or a JSON string that is intercepted in a log. Be careful not to copy only half of the paragraph.
4. Click "Formatization". (a) A clear structure is indented when successful; Focus on error tips and approximate positions when failure, rather than read the whole of the code.
5. The government is not going to be able to reduce the volume of the project by "compression". Pre-compression suggests ensuring that it is legal, JSON, otherwise compression will also fail or output the result.
6. Take a look before copying the results. Confirms that there are no mistempo fields, comment residues or dissensitisations, and then pastes back to the editor, document or request tool.

How does the tools fit in?

• Two JSON fields are not match: format them and then use them JSON Diff Compare.
• Only compressed demand: direct use JSON Minify。
• Source: First Convert to JSON- Supple or validate.
• When you need to see the path or tree structure, you can then do a point query with the JSON tree, JSONPath type tool in the station.

It is suggested that the Formatting Tool be used as the default entry for the associated desktop: first, to make the text valid and readable, then to decide whether the next step is Diff, conversion or writing back. The tool switching costs very little, but the wrong sequence would waste the afternoon.

5. Common errors and treatments

When the check fails, you will first believe in the location information given by the solver. Here's a set of "generic causes of the phenomenon" and a list of the most high frequency problems in the day-to-day world. You can use it as a wrong tabulation, without having to go from zero to syntax details at a time.

Spacing Proposal

1. First look at the wrong line in the vicinity, one to three, not the hard-cleaning from the file head.
2. The question of the four types of syntax that are to be given priority is that of quotes, commas, brackets, notes.
3. After the grammar is passed, the fields are missing, not the same type, and the business validation (that is Schema/business level, not the JSON syntax itself).
4. If only one interface is cut off, return to the web panel to replicate Response and avoid scrambling on the missing text.
5. Once completed, the correction was formatted again to confirm that the error had disappeared and entered the Diff or business assertions.

// Illegal：End comma + Single quote + Comment
{
  'name': 'Ada',  // Username
  'age': 30,
}

// Legal
{
  "name": "Ada",
  "age": 30
}

Also, some misreported lines are "backsided" and the real problem is probably in the earlier unclosed string. If the line number is not changed properly, the location is faster if you try to look back at the last complete object boundary or to separate large JSON into smaller pieces.

6. How does the real scene work?

The concept is remembered and has to be translated into specific streams of work. The following five scenarios cover the interface, configuration, comparison, document and cross-format collaboration, essentially corresponding to the most high frequency JPON usage at the center backstage and front end.

Scenario A: Return a large amount of interfaces to connect

The front end saw a compressed response in the Network panel, which was painful to read directly. Copy Response to Formatting Tool, confirm first data、list、error Wait for the node level to decide whether to change the requested parameters or to re-simplify the logic. Many of the "undefined" fields are actually wrong-looking levels, not backends that don't return. Formatting and then comparing Type Type Type or Interface document to a much less controversial document.

Scenario B: Profile suddenly unable to start

When the service fails to resolve the configuration, you will first post the configuration of the JSON clip to the verification tool. If failure, click the quote and tail comma; If successful, there is a question as to whether the environmental variable replacement, file encoding or outer-level template engine has damaged the structure. Do not come up and restart the machine or roll back unconnected — the grammar problem usually can be perjured in minutes.

C: Two responses that look "similar" are not right.

Format separately, indent before you use it. JSON Diff 。 People's eyes are easily missed by one more empty string, numbers and strings " 1", array sequence changes, and one more nuld field. Diff is more stable than rolling back and forth and better suited to add Code Review to "where the difference is."

scene D: Document and Mock need a readable sample

(a) In external documents, README, interface instructions, giving priority to formatting examples; If you have a volume-sensitive fixture in the warehouse, you can keep a compressed version, but in an explanatory note or document, specify that "compression is only for volume, and debug it first". Readable examples reduce the cost of new hands and reduce the embarrassment of "JSON Fundamental parse in the document"

scene E: Generate JSON from YAML/Script

The side of the movement is commonly used in Yaml, the side of the application is simply JSON. Convert, verify, and then compress. Do not change indentation to brackets by hand by "feeling" unless you are sure you're maintaining strict JSON. Generates an automatic verification of the chain in the Riga that will block a large number of tail commas and type problems.

"Look at this for me."

When colleagues drop a dusty text, they are allergic to it, then format/validate it and then respond to the conclusions. The response suggested three sentences: whether it was legal, what the main structure was, and where the suspect field was. It is more professional than being character-to-characterized directly in a group, and it is less easy to retransmit the key.

8. How to select the tools

Press "Where are you now stuck" to select a tool that is more effective than a collection of portals:

Selection tips:It's not a formality, it's a condensed volume, it's not a valid pre-check, it's a match, Diff, it's not a JSON, it's a conversion. The same data can then go through "validation → Diff → compression" without forcing the "everybody button".

9. Small habits of teamwork

(a) Misplaced personal means; The team is long-term in time, depending on the agreement. The following are low-cost and high-yielding items that are suitable for inclusion in the README or the Réaration Code. They will not replace Schema with contract tests, but will significantly reduce the amount of time that is being misconstrued by lower grammatical errors.

• There are two types of examples:Human reading formatted; Machine consumption, volume sensitivity, compressed versions, and indicated uses.
• When changing the Review interface:Requesting to attach a minimal legal JSON sample instead of half a chart.
• Logs and worksheets:(b) Pre-adhesive dissemination; Do not put the whole production section into the group chat.
• Auto-generated JSON:Run a check after generation to avoid a template tail comma entering the environment.
• Big document strategy:Browser suitable for small and medium text; Super-sized JSON gives priority to local editor, jq or a special viewer to intercept suspicious footage online.
• Error layer:Syntax Errors are resolved by formatting tool; Fields missing and type errors are given to Schema/single test; Business rules wrongly recheck code logic.

When you strip the word "legal" from "business is correct or not," communication is more efficient: front, back, test can be aligned "can this parse" and "should not exist". A lot of cross-breeding, actually, is stuck on the first floor.

FAQ

Continue reading

Open the tool and try first, and then return to the page's control error sheet, which is usually more effective than a collection of articles. You can also return AllGuides or Directory of Tools Keep browsing. When the "validation poignant formatted / Diff" is turned into muscle memory, the lower-level barriers associated with JSON are much less.