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Based on our record, NumPy seems to be a lot more popular than Singer. While we know about 122 links to NumPy, we've tracked only 7 mentions of Singer. 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.
Coincidently, I saw a presentation today on a nice half-way-house solution: using embeddable Python libraries like Sling and dlt - both open-source. See https://www.youtube.com/watch?v=gAqOLgG2iYY There is also singer.io which is more of a protocol than a library, but can also be installed although it looks like it is a true community effort and not so well maintained. Source: over 2 years ago
Singer is an open-source framework for data ingestion, which provides a standardized way to move data between various data sources and destinations (such as databases, APIs, and data warehouses). Singer offers a modular approach to data extraction and loading by leveraging two main components: Taps (data extractors) and Targets (data loaders). This design makes it an attractive option for data ingestion for... - Source: dev.to / about 3 years ago
Or you could build your own such system and run it on Airflow, Prefect, Dagster, etc. Check out the Singer project for a suite of Python packages designed for such a task. Quality varies greatly, though. Source: almost 4 years ago
This is good advice and I think Airbyte created a great product here. I tried singer.io and pipewise but Airbyte is much better in my opinion and I love the UI. Source: almost 5 years ago
Suspect my question should have been regarding FREE systems, rather than BUYING a system. Sounds like singer.io will do what I need. Source: about 5 years ago
Unmatched integration with ML/AI ecosystems through NumPy, TensorFlow, and PyTorch. - Source: dev.to / 9 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
AI starts with math and coding. You donโt need a PhDโjust high school math like algebra and some geometry. Linear algebra (think matrices) and calculus (like slopes) help understand how AI models work. Python is the main language for AI, thanks to tools like TensorFlow and NumPy. If you know JavaScript from Vue.js, Pythonโs syntax is straightforward. - Source: dev.to / 12 months ago
The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / over 1 year ago
This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / almost 2 years ago
Airbyte - Replicate data in minutes with prebuilt & custom connectors
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Apache Camel - Apache Camel is a versatile open-source integration framework based on known enterprise integration patterns.
OpenCV - OpenCV is the world's biggest computer vision library
