On Lisp Reviews

Python Reviews

On Lisp mentions (4)

• Prolog-rs: Minimal Prolog implemented in Rust

  See also https://github.com/RussAbbott/pylog which has a toy Prolog implementation and was wondering if it could be done in Python. - Source: Hacker News / almost 2 years ago

• Quote-Unquote "Macros"

  Paul Graham's https://paulgraham.com/onlisp.html is a whole book about it that really helped it click for me. The challenge with the syntax is that there is no syntax. Work that we're used to offloading to syntax is instead carried by your brain. - Source: Hacker News / almost 2 years ago

• Defense of Lisp Macros

  BTW, if you're interested in learning more about Lisp macros, Paul Graham's book about advanced Lisp programming, On Lisp, covers the topic pretty extensively and it's freely downloadable from his website: Book description: https://paulgraham.com/onlisp.html Download page: https://paulgraham.com/onlisptext.html. - Source: Hacker News / almost 2 years ago

• [Getting (re)started] Where can I learn about setf?

  Some info can be found here: http://paulgraham.com/onlisp.html. Source: over 4 years ago

Python mentions (299)

• How to Build a Dependency Map of a Legacy Codebase Using AI Tools

  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 / 2 months ago

• How to Prepare a Legacy Codebase for AI-Assisted Refactoring

  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 / 2 months ago

• Async Web Scraping in Python: asyncio + aiohttp + httpx (Complete 2026 Guide)

  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 — no issue soup = BeautifulSoup(html, "html.parser") return { "url": url, "title": soup.title.string if soup.title... - Source: dev.to / 3 months ago

• Don't Be Afraid of Git: A Beginner's Guide to Saving and Sharing

  **_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: - “Save this data” - “Get this data” - 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

• Asyncio: Interview Questions and Practice Problems

  Import time Import requests Import asyncio Import aiohttp Urls = [ 'https://example.com', 'https://httpbin.org/get', 'https://python.org' ] # Synchronous version Def sync_fetch(): for url in urls: response = requests.get(url) print(f"{url} fetched with {len(response.text)} characters") # Async version Async def async_fetch(): async with aiohttp.ClientSession() as session: ... - Source: dev.to / 9 months ago