Python
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Julia
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We recommend LibHunt Julia for discovery and comparisons of trending Julia projects.
Python Julia{"data_science" => "Data scientists who require a fast and flexible language for data manipulation and analysis.", "machine_learning" => "Developers looking to implement machine learning models that benefit from Julia's performance.", "numerical_analysis" => "Engineers and analysts conducting numerical analysis that demands high computational efficiency.", "scientific_computing" => "Researchers and scientists working on mathematical, statistical, and computational problems."}
Based on our record, Python should be more popular than Julia. It has been mentiond 300 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.
> When you download Python from http://python.org (on Linux or macOS), what you're actually downloading is an installer that builds Python from source on your machine. > The net effect is that on Linux and macOS, you can't "download a Python binary" from... anywhere. Other than the python-build-standalone project. Are you sure this is right about macOS? I just had a look inside the macOS installer from python.org... - Source: Hacker News / 4 days ago
137Foundry provides legacy modernization services that include dependency mapping as a foundational assessment phase. Prettier and ESLint are useful companion tools for enforcing code style consistency as the refactoring proceeds. Node.js and Python.org official documentation are authoritative references for understanding the import and module systems of those runtimes. - Source: dev.to / 3 months ago
For Python codebases, tools like Python's built-in ast module and import analysis scripts can generate call graphs. For JavaScript, ESLint and module analysis tools serve a similar purpose. GitHub advanced search can help you find all internal references to a specific function across a large repository. - Source: dev.to / 3 months ago
Import asyncio Import aiohttp From bs4 import BeautifulSoup Async def scrape_and_parse(url: str, session: aiohttp.ClientSession) -> dict: async with session.get(url) as response: html = await response.text() # BeautifulSoup parsing happens after the await โ no issue soup = BeautifulSoup(html, "html.parser") return { "url": url, "title": soup.title.string if soup.title... - Source: dev.to / 4 months ago
**_Beginner mistake to avoid_** - Writing SQL only inside DBeaver - Always save SQL files in VS Code and commit them **Using PostgreSQL with Python** _**What Python does here**_ Python talks to PostgreSQL and says: - โSave this dataโ - โGet this dataโ - PostgreSQL listens. Python works. _**Step 1: Install Python **_ - Download from https://python.org - During install, check Add Python to PATH Screenshot... - Source: dev.to / 6 months ago
If you're looking for a language that aims to solve the "two-language problem" like Mojo, but want something more open, more mature and less influenced by VC funding, check out Julia: https://julialang.org/. - Source: Hacker News / 3 months ago
The problem with MATLAB is that idiomatic MATLAB style (every operation returns a fresh matrix) can easily become very inefficient: it leads to countless heap memory allocations of new matrices, resulting in low data-access locality, i.e. Your data is needlessly copied around in slow DRAM all the time, rather than being kept in the fastest CPU cache. Julia's MATLAB-inspired syntax is at least as nice, but the... - Source: Hacker News / 8 months ago
In this post, We will learn how to simulate MRI physics In the Julia programming language, a free and open source programming language That excels especially in scientific computing. - Source: dev.to / 9 months ago
Mine is Julia, although I don't use diary. Nowadays I like SuperCollider. https://julialang.org. - Source: Hacker News / about 1 year ago
> I was active in the Python community in the 200x timeframe, and I daresay the common consensus is that language didn't matter and a sufficiently smart compiler/JIT/whatever would eventually make dynamic scripting languages as fast as C, so there was no reason to learn static languages rather than just waiting for this to happen. To be very pedantic, the problem is not that these are dynamic languages _per se_,... - Source: Hacker News / about 1 year ago
JavaScript - Lightweight, interpreted, object-oriented language with first-class functions
MATLAB - A high-level language and interactive environment for numerical computation, visualization, and programming
Java - A concurrent, class-based, object-oriented, language specifically designed to have as few implementation dependencies as possible
GNU Octave - GNU Octave is a programming language for scientific computing.
C++ - Has imperative, object-oriented and generic programming features, while also providing the facilities for low level memory manipulation
Rust - A safe, concurrent, practical language
