python

Use these frameworks to empower your machine-learning work Link

common packages used in python while working as Data Engineers Link

There are many well-known libraries and platforms for data analysis such as Pandas and Tableau, in addition to analytical databases like ClickHouse, MariaDB, Apache Druid, Apache Pinot, Google BigQuery, Amazon RedShift, etc. Link

There is a proverb “You don’t have to reinvent the wheel”. Libraries are the best example of that. It helps you to write complex and time-consuming functionality in an easy way. According to me, a good project uses some of the best libraries available. Link

Power up your Python development Link

Blockchain Dune Analytics with Uniswap Link

Each chart shown below is a QuickChart image built with a Chart.js config. These images can be sent in emails or embedded in any platform. Link

Daft is currently in its Alpha release phase - please expect bugs and rapid improvements to the project. We welcome user feedback/feature requests in our Discussions forums. Link

It’s a general purpose micro-framework for creating dataflows from python functions! Link

Easily build and manage feature, training and inference pipelines. Support for Python, PySpark, Spark, Flink, and SQL Link

Hypothesis is a Python library for creating unit tests which are simpler to write and more powerful when run, finding edge cases in your code you wouldn’t have thought to look for. It is stable, powerful and easy to add to any existing test suite. Link

Modin is a drop-in replacement for pandas. While pandas is single-threaded, Modin lets you instantly speed up your workflows by scaling pandas so it uses all of your cores. Modin works especially well on larger datasets, where pandas becomes painfully slow or runs out of memory. Link

Decorators provide a new and convenient way for everything from caching to sending notifications Link

Build software collaboratively with the power of AI, on any device, without spending a second on setup Link

TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale. Link