Dask vs Data Miner: What are the differences?
Dask: A flexible library for parallel computing in Python. It is a versatile tool that supports a variety of workloads. It is composed of two parts: Dynamic task scheduling optimized for computation. This is similar to Airflow, Luigi, Celery, or Make, but optimized for interactive computational workloads Big Data collections like parallel arrays, dataframes, and lists that extend common interfaces like NumPy, Pandas, or Python iterators to larger-than-memory or distributed environments. These parallel collections run on top of dynamic task schedulers. ; Data Miner: Extract Data From any Website in Seconds. It is a Google Chrome extension that helps you scrape data from web pages and into a CSV file or Excel spreadsheet.
Dask and Data Miner can be primarily classified as "Data Science" tools.
Some of the features offered by Dask are:
- Supports a variety of workloads
- Dynamic task scheduling
- Trivial to set up and run on a laptop in a single process
On the other hand, Data Miner provides the following key features:
- Scrape with one click
- No coding
- No bots