ultrajson
PyLD
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ultrajson | PyLD | |
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3 | 28 | |
4,077 | 532 | |
1.0% | 0.6% | |
8.0 | 0.0 | |
about 1 month ago | 2 months ago | |
C | Python | |
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.
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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.
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 "..."`)?
PyLD
- I Wrote an Activitypub Server in OCaml: Lessons Learnt, Weekends Lost
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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/
Id also take a bit of time polishing your work. If its a front end dev job, it helps if you make things pretty. Make sure you also read and note down what you missed. I havent done a deep dive but I didnt see any JSON-LD for instance (https://json-ld.org/). you could implement this by saving the json contents in a const object and just add the @ tags in the object.
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SEO Benefits of Next.js in 2022
There’s another way you can help Google understand the content of your web page better. You should incorporate a particular JS snippet into your HTML that describes the page content according to a JSON-LD format that gives machine-readable information about the website.
- how do i write metadata, and how can i make it cooler?
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QWER : Simply Awesome Blog Starter built with SvelteKit and Love
SEO friendly through meta, Open Graph, Schema, JSON-LD, microformats2.
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Understanding SEO and Web Vitals for your NextJS site and how to improve them?
We can help google search engine understand the content of our site even more by adding structured data with the help of JSON-LD. Google can use the structured data to enable special search features which in turn boost your page rank. You can read more about this here: https://developers.google.com/search/docs/advanced/structured-data/intro-structured-data
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The Block Protocol
Exactly what I was thinking. The Semantic Web done the heavy lifting of defining general schemas (https://schema.org) and extending JSON (https://json-ld.org) and yet people don't subscribe to it. On the other hand, it has a lot of historical baggage (RDF, old schemas) that maybe a new standard can actually be better
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What is Structured Data?
Web pages are an interesting example of both structured and unstructured data. There are specific elements one could look at for certain information like the element or other semantic elements like
or
. The problem though is that these elements are more like our "address" example earlier - they often contain more than just the strict data we are looking for. A title might have a prefix or suffix of the website's name. An article or section might have many other layers of
,or any other elements to help form the site's structure. To top it off, the HTML structure can vary wildly from site to site. If you were wanting to extract data from multiple websites, it can get very hard very fast.
That said, there are a number of ways to embed structured data into web pages. A web page could use Microdata, RDFa, JSON-LD or Open Graph to express structured data. More than that though, a web page can use multiple of these at the same time. Open Graph is commonly used as a method of defining details for a link preview while the others might express more complex data like product pricing or reviews.
Having standard formats like Microdata or JSON-LD are a good start but only represent the format of the data - we need a common vocabulary so we can understand the data those formats encode. One common vocabulary used is called Schema.org and provides over 700 types including types to describe people, places, products, recipes, reviews, vehicles, movies and medical devices. Using Schema.org for structured data on a website can help search engines provide richer experiences in the search results.
Summary
Structured data, through standardising expected properties and value formats, makes the sharing and processing of data easier. Web pages in particular benefit from encoding structured data in their mark-up where it can be used by search engines and other tools.
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Json-ld spices up the staticness of static site generator
Json-ld is a linked data format based on json. If you have never heard of json-ld, that's ok. The most important thing to know is that it's just plain old json with a few extra special fields. It's also a w3c standard and you can check out the complete spec. We don't really need to understand the whole spec, we're just interested in the way json-ld can reference other data fragments with a url using the keyword "@id "
What are some alternatives?
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 plugin providing JSON-LD parsing and serialization - JSON-LD parser and serializer plugins for RDFLib
python-rapidjson - Python wrapper around rapidjson
Fast JSON schema for Python - Fast JSON schema validator for Python.
pysimdjson - Python bindings for the simdjson project.
hjson-py - Hjson for Python
serpy - ridiculously fast object serialization
rdflib - RDFLib is a Python library for working with RDF, a simple yet powerful language for representing information.