PyLD
ultrajson
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| PyLD | ultrajson | |
|---|---|---|
| 28 | 3 | |
| 577 | 4,244 | |
| 1.2% | 0.7% | |
| 5.2 | 7.0 | |
| about 2 months ago | 19 days ago | |
| Python | C | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
PyLD
- I Wrote an Activitypub Server in OCaml: Lessons Learnt, Weekends Lost
- JSON for Linking Data
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I'm currently in the interview process for a Jr. Full Stack Developer position, and I was given this take-home test that has me on the verge of pulling my hair out.
3) Things I would need to refresh: JSON-LD (This is actually really useful): https://json-ld.org/
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The need for a more semantic web
Some documentation for you OP: - RDFa. - JSON-LD doesn't have to be in HTML. It's just a specification built on JSON to represent RDF data. Also, from experience, Turtle) is more popular - If you want to dig into what defining semantic vocabularies (ontologies) entails, read on RDF, RDFS, and OWL2.
- Making SEO better for blog posts with Structured Data
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Beginners Guide to Yoast SEO 2023
Schema markup can be added to a web page using the JSON-LD format, which is a structured data format that is supported by Yoast SEO.
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Getting Started with ActivityPub
It's a big long, so the response is at the bottom in Appendix A. The format is JSON for Linking Data, or JSON-LD.
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schema-org-java: Java library for working with Schema.org data in JSON-LD format
So it can be tedious to create all the entities needed for your project and then serialize / deserialize the data in JSON-LD format.
ultrajson
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Processing JSON 2.5x faster than simdjson with msgspec
ujson
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Benchmarking Python JSON serializers - json vs ujson vs orjson
For most cases, you would want to go with python’s standard json library which removes dependencies on other libraries. On other hand you could try out ujsonwhich is simple replacement for python’s json library. If you want more speed and also want dataclass, datetime, numpy, and UUID instances and you are ready to deal with more complex code, then you can try your hands on orjson
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The fastest tool for querying large JSON files is written in Python (benchmark)
I asked about this on the Github issue regarding these benchmarks as well.
I'm curious as to why libraries like ultrajson[0] and orjson[1] weren't explored. They aren't command line tools, but neither is pandas right? Is it perhaps because the code required to implement the challenges is large enough that they are considered too inconvenient to use through the same way pandas was used (ie, `python -c "..."`)?
What are some alternatives?
RDFLib plugin providing JSON-LD parsing and serialization - JSON-LD parser and serializer plugins for RDFLib
marshmallow - A lightweight library for converting complex objects to and from simple Python datatypes.
greenpass-covid19-qrcode-decoder - An easy tool for decoding Green Pass Covid-19 QrCode
rdflib - RDFLib is a Python library for working with RDF, a simple yet powerful language for representing information.
Fast JSON schema for Python - Fast JSON schema validator for Python.
serpy - ridiculously fast object serialization
python-rapidjson - Python wrapper around rapidjson
jsons - 🐍 A Python lib for (de)serializing Python objects to/from JSON
pysimdjson - Python bindings for the simdjson project.
lupin is a Python JSON object mapper - Python document object mapper (load python object from JSON and vice-versa)