ChainGPT Reviews

Python Reviews

ChainGPT mentions (3)

• ChainGPT Automates Blockchain News.

  ChainGPT is designed to provide users with up-to-date and accurate information about the latest trends and developments in the sector. The service uses advanced algorithms and machine learning techniques to analyze vast amounts of data from various sources, including social media, news sites, and other online platforms. It then generates high-quality news articles that are tailored to the user's specific interests... Source: about 3 years ago

• Why is it worth it to get involved on ChainGPT

  Visit https://chaingpt.org for more info. Source: about 3 years ago

• ChainGPT project explained

  ChainGPT makes on-chain data analysis simpler than ever. Their advanced AI model can help with risk management, data analysis, ID verification, avoiding bad actors, and analyzing users' on-chain history. To learn more about ChainGPT and its groundbreaking AI technology, visit their website at https://chaingpt.org/ and check out their Twitter page at https://twitter.com/Chain_GPT. Source: about 3 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