Messagepack
Protobuf
TOML
YAML
Avro
Apache Thrift
JSON
gRPC
Dask
Pandas
Apache Airflow
NumPy
Apache Spark
Burla
Celery
SciPy
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Dask might be a bit more popular than Messagepack. We know about 16 links to it since March 2021 and only 13 links to Messagepack. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I also read that Salt was using MessagePack to format their messages. MessagePack is a format like JSON, but more compact. - Source: dev.to / 7 months ago
So appreciate such a detailed reply, thanks. btw, why did you choose tinylib/msgp from 4 available go-impls? Source: about 1 year ago
If you find you're running the serial connection at maximum speed and it's still not fast enough, try switching to a more compact binary encoding that has both Serde and Arduino implementations, like MsgPack... Though I don't remember enough about its format off the top of my head to tell you the easiest way to put an unambiguous header on each packet/message to make the protocol self-synchronizing. Source: over 1 year ago
The information can be stored in a database or as files, serialized in a standard format and with a schema agreed with your Data Engineering team. Depending on your information and requirements, it can be as simple as CSV, XML or JSON, or Big Data formats such as Parquet, Avro, ORC, Arrow, or message serialization formats like Protocol Buffers, FlatBuffers, MessagePack, Thrift, or Cap'n Proto. - Source: dev.to / over 1 year ago
MessagePack Similar to JSONs, just more compact, although not as much as the ones above. Still, it's usefull to retain some readability in your messages. Source: over 1 year ago
We're using a lot of Python. In addition to these, gridMET, Dask, HoloViz, and kerchunk. Source: about 2 years ago
I wrote this for speeding up the RPC messaging in dask, but figured it might be useful for others as well. The source is available on github here: https://github.com/jcrist/msgspec. Source: about 2 years ago
Dask: Distributed data frames, machine learning and more. - Source: dev.to / over 2 years ago
To do that, we are efficiently using Dask, simply creating on-demand local (or remote) clusters on task run() method:. - Source: dev.to / over 2 years ago
I’m quite sure dask helps and has a pandas like api though will use disk and not just RAM. Source: over 2 years ago
Protobuf - Protocol buffers are a language-neutral, platform-neutral extensible mechanism for serializing structured data.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
TOML - TOML - Tom's Obvious, Minimal Language
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
YAML - YAML 1.2 --- YAML: YAML Ain't Markup Language
NumPy - NumPy is the fundamental package for scientific computing with Python
