Hi everyone,
I’ve been working with JSON files lately and realized they’re not always easy to read or share, especially for non-technical users. I’m looking for simple and effective ways to convert JSON data into more readable formats like PDF, TXT, CSV, or even Excel.
Are there any reliable manual methods, tools, or software you’d recommend for this? I’ve heard about a few converters but not sure which ones are actually efficient and safe to use.
Over the past week I’ve been deep in debugging a pretty gnarly multi-layer integration — the kind where you’re constantly staring at huge JSON payloads, trying to understand what’s actually inside, and then turning that into clear bug reports or questions for other teams.
Pretty quickly I got tired of manually digging through nested structures, broken payloads, and JSON-inside-JSON situations. So I ended up writing a small CLI tool for myself called jray.
The idea is simple: treat JSON like an “X-ray” problem. Instead of pretty-printing it, flatten it into a list of .path=value pairs so you can immediately see what’s there, no matter how deeply nested or messy it is. It is very friendly to grep or similar tools.
A few things that turned out to be especially useful:
If you deal with messy JSON regularly, this might save you some time (and sanity).
Hey everyone,
I recently built a small microservice to solve a frustrating problem I kept running into: parsing line items from unpredictable invoice layouts.
Traditional regex parsing breaks the moment a vendor changes their document formatting. To fix this, I built a FastAPI backend that takes raw text strings (like messy OCR or receipt text) and formats them into a clean JSON schema using generative AI.
The Tech Stack:
I'm currently looking for testers to see how well it handles different invoice types. If you've got a weirdly formatted invoice text string, I’d love for you to test the extraction speed and accuracy.
You can test the endpoint directly on the RapidAPI listing: Invoice and Receipt Extractor
Any feedback on the extraction schema or the response times is highly appreciated!
I have spent some time recently reimplementing Mojang's DataFixerUpper library (which handles serialization and data transformation through the lifetime of a project) in C# with a few of my own takes on it. It uses literally zero reflection and rivals the built-in System.Text.Json library in allocations, sometimes even beating it (although latency is a bit of a problem right now because I'm not batching operations together), as evidenced by the benchmarks:
| Method | Mean | Error | StdDev | Median | Gen0 | Allocated |
|----------------------------|---------:|---------:|----------:|---------:|-------:|----------:|
| STJ_Serialize | 237.9 ns | 24.37 ns | 71.86 ns | 194.4 ns | 0.0343 | 72 B |
| STJ_Serialize_IntArray | 186.2 ns | 20.36 ns | 60.02 ns | 142.0 ns | 0.0191 | 40 B |
| STJ_Deserialize | 321.7 ns | 5.65 ns | 10.19 ns | 318.4 ns | 0.0801 | 168 B |
| STJ_Deserialize_IntArray | 198.2 ns | 2.63 ns | 2.46 ns | 197.5 ns | 0.0534 | 112 B |
| Codec_Serialize | 546.0 ns | 59.11 ns | 174.29 ns | 418.2 ns | 0.0534 | 112 B |
| Codec_Serialize_IntArray | 393.4 ns | 2.92 ns | 2.28 ns | 392.7 ns | 0.0610 | 128 B |
| Codec_Deserialize | 524.7 ns | 5.14 ns | 4.29 ns | 524.2 ns | 0.0305 | 64 B |
| Codec_Deserialize_IntArray | 475.7 ns | 4.07 ns | 3.40 ns | 475.0 ns | 0.0343 | 72 B |
The library is designed in such a way that you can create tiny codecs for structs/classes and compose them together to serialize even complex/nested DTOs seamlessly. You can also define "timelines" for your objects and pass their serialized versions through transformation pipelines to add/remove/rename keys.
The library also happens to be format-agnostic by design, so the exact same APIs would work with a backend for cbor, custom binary, yaml, burping into the mic vocoded into gangsta's paradise or any other format you might think of.
As said in the title, I requested a discord data package to find my ip address of my apartment which i moved out of and I find that I cant open some of the json files cause they're too large
For mac users who are dealing with a lot of GPX files exported from strava, biking routes, etc... I built a small quicklook viewer to allow you to peek into any GPX file to check it plotted on a map without actually opening it, allowing you to use the arrows to explore all files in a directory without firing any software to recognize it, 100% local, using anonymous openstreetmap tiles for viewing, and supports also some other formats: GeoJSON, KML, KMZ, GPKG, and a very limited support for SHP files.
Let me know your thoughts!
I thought nullable DTO fields were enough for PATCH.
My rule was simple: if a field is missing or null, treat both the same. Client sends only what it wants to update.
That worked until it didn’t
We accidentally wiped a production value because the client updated one field and omitted another intentionally. :(
After deserialization, I couldn’t distinguish “not sent” from “explicit null,” so my code cleared a field that should have stayed untouched. So we had to roll back. No problem
I am looking at a few alternatives like nullable fields, explicit field_present flags, JSON Patch, and wrapper types that preserve field presence.
Curious how other people handle “missing vs null” in PATCH without making the client payload ugly?
Hey everyone,
While working with APIs, I kept hitting the same annoying issues:
- Invalid JSON breaking things
- XML responses that are hard to debug
- Comparing API responses manually when something changes
- No easy way to validate if an API response still matches expected structure
So I started building a tool to make this easier.
Right now it supports:
- JSON validation + auto-fix
- XML validation
- JSON diff (compare responses)
- (Working on) API contract monitoring — basically detecting when an API response changes unexpectedly
It’s still early, but I’m trying to make it genuinely useful for developers working with APIs.
Would love honest feedback:
- What’s missing?
- What would make this actually useful for your workflow?
Thanks 🙌
Hey guys, I believe most of you know the pain of dealing with large nested JSON from API responses or production traces. It gets even more painful when this is your daily job and you have no good way to visualize it… except quitting :))
I ended up building one for myself with the features I needed:
- level selection
- visualize JSON as a graph node
- send JSON directly to the API Client tool and test it without leaving the current tab
Check it out if interested:
https://catssaymeow.org/json-formatter/