Apache Thrift
Docker Hub
Apache ZooKeeper
Eureka
Avro
SkyDNS
gRPC
runc
Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
Apache Thrift MatplotlibBased on our record, Matplotlib should be more popular than Apache Thrift. It has been mentiond 114 times since March 2021. 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 once read a paper about Apache/Meta Thrift [1,2]. It allows you to define data types/interfaces in a definition file and generate code for many programming languages. It was specifically designed for RPCs and microservices. [1]: https://thrift.apache.org/. - Source: Hacker News / almost 2 years ago
While gRPC and Apache Thrift have served the microservice architecture well, CloudWeGo's advanced features and performance metrics set it apart as a promising open source solution for the future. - Source: dev.to / over 2 years ago
Services in general communicate via Thrift (and in some cases HTTP). Source: over 3 years ago
Protocol Buffers is the most popular one, but there are many others such as Apache Thrift and my own Typical. Source: over 3 years ago
RPC is not strictly OO, but you can think of RPC calls like method calls. In general it will reflect your interface design and doesn't have to be top-down, although a good project usually will look that way. A good contrast to REST where you use POST/PUT/GET/DELETE pattern on resources where as a procedure call could be a lot more flexible and potentially lighter weight. Think of it like defining methods in code... Source: over 3 years ago
In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 5 months ago
Numbers are useful, but sometimes itโs easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 8 months ago
We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 9 months ago
NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 10 months ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 11 months ago
Docker Hub - Docker Hub is a cloud-based registry service
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Apache ZooKeeper - Apache ZooKeeper is an effort to develop and maintain an open-source server which enables highly reliable distributed coordination.
NumPy - NumPy is the fundamental package for scientific computing with Python
Eureka - Eureka is a contact center and enterprise performance through speech analytics that immediately reveals insights from automated analysis of communications including calls, chat, email, texts, social media, surveys and more.
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.
