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NumPy Alternatives
Similar projects and alternatives to NumPy
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Pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
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Mergify
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Pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
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Nim
Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).
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InfluxDB
Collect and Analyze Billions of Data Points in Real Time. Manage all types of time series data in a single, purpose-built database. Run at any scale in any environment in the cloud, on-premises, or at the edge.
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fastapi
FastAPI framework, high performance, easy to learn, fast to code, ready for production
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Sonar
Write Clean Python Code. Always.. Sonar helps you commit clean code every time. With over 225 unique rules to find Python bugs, code smells & vulnerabilities, Sonar finds the issues while you focus on the work.
NumPy reviews and mentions
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Building an efficient sparse keyword index in Python
Large computations in pure Python can also be painfully slow. Luckily, there is a robust landscape of options for numeric processing. The most popular framework is NumPy. There is also PyTorch and other GPU-based tensor processing frameworks.
- How to Create a Pareto Chart 📐
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NumPy VS gmpy - a user suggested alternative
2 projects | 2 Aug 2023
- How to Build and Deploy a Machine Learning model using Docker
- Open source public fund experiment - One and a half years update
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[Python] A Journey to Python Async - 1. Intro
But whereas I took for granted that async syntax in JS, async in Python was quite unfamiliar to me when I saw it for the first time. I had some experiences of using Python for writing really simple scripts, without ever worrying about those async features. That was probably because many big popular libraries such as numpy, pandas, or even selenium didn’t require any async logics to be considered. And those libraries were(and still are) the main reasons for using Python at all.
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Python Algotrading with Machine Learning
A super-fast backtesting engine built in NumPy and accelerated with Numba.
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Why are physics undergrads told to "learn programming" and what does this consist of?
NumPy: allows you to work with matrices and common math functions efficiently. Very useful for analyzing experimental data and running simulations.
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PSA: You don't need fancy stuff to do good work.
Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses without relying on expensive or proprietary software.
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Beating Bisect with Branchless Binary Search
If anyone has the time & energy to put into figuring out a production quality open source version of this, one place that could benefit is numpy's searchsorted function
https://github.com/numpy/numpy/blame/main/numpy/core/src/npy...
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A note from our sponsor - Mergify
blog.mergify.com | 23 Sep 2023
Stats
numpy/numpy is an open source project licensed under BSD 3-clause "New" or "Revised" License which is an OSI approved license.
The primary programming language of NumPy is Python.