WinPython
PyCharm
Colaboratory
Portable Python
Thonny
PythonAnywhere
Spyder
Anaconda
Apache Storm
Apache Spark
Apache Flink
Qubole
Hadoop
Google BigQuery
Apache Kafka
Amazon Kinesis
Based on our record, WinPython should be more popular than Apache Storm. It has been mentiond 19 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.
STEP 1: Python on Windows What to install Download and install WinPython from https://winpython.github.io. I researched Python on Windows and in very short order understood that WinPython is the way to go. While it’s stated audience is scientists, data scientists and education, it fully serves the needs of personal projects. Also, it is available as a portable distribution with no requirement to register with... - Source: dev.to / over 2 years ago
How can I use the portable version of winpython from https://winpython.github.io to configure into qbittorrent to detect the runtime pre-requisites so that my portable qbittorent search can work? Thx in advanced. #portablepython. Source: over 3 years ago
You equally are barred from e.g., WinPython which can work without an installation into the OS, too? Then - mechanically speaking - it wouldn't matter that the USB ports are permanently plastered with some polymer. Source: over 3 years ago
Thank for answering. I understand that the interpreter situation can be annoying. There is WinPython [0] to circumvent that to some degree. I feel like if I don’t do it the „VSCode and py-file“ way, it’ll be more and more difficult to keep everything together when teaching about modularity and putting functions in helper scripts, putting tests in other directories and such. I think it’s just because I got used to... - Source: Hacker News / over 3 years ago
One option would be to use a portable Python runtime. Like this one: https://winpython.github.io/. Source: over 3 years ago
There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 3 years ago
Although this article lists a lot of targets for technical selection, there are definitely others that I haven't listed, which may be either outdated, less-used options such as Apache Storm or out of my radar from the beginning, like JAVA ecosystem. - Source: dev.to / over 3 years ago
Storm, a system for real-time and stream processing. - Source: dev.to / almost 4 years ago
Google has scaled well and has helped others scale, Twitter has always been behind by years. I think the only thing they did well was Twitter Storm, now taken up by Apache Foundation. Source: almost 4 years ago
Streaming: Sparks Streamings's latency is at least 500ms, since it operates on micro-batches of records, instead of processing one record at a time. Native streaming tools like Storm, Apex or Flink might be better for low-latency applications. - Source: dev.to / over 4 years ago
PyCharm - Python & Django IDE with intelligent code completion, on-the-fly error checking, quick-fixes, and much more...
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Colaboratory - Free Jupyter notebook environment in the cloud.
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
Portable Python - Minimum bare bones portable python distribution with PyScripter as development environment.
Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.