GitHub Metrics
GitWrapped
Contributions for GitHub
GitPrime
Waydev
Code Time
Sixtyfour
GitHub Unwrapped 2022
Python
JavaScript
Java
C++
Rust
Ruby
PHP
Elixir
GitHub Metrics PythonNo GitHub Metrics videos yet. You could help us improve this page by suggesting one.
Based on our record, Python seems to be a lot more popular than GitHub Metrics. While we know about 299 links to Python, we've tracked only 9 mentions of GitHub Metrics. 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.
This tutorial shows you how to create a fully automated GitHub profile README using GitHub Metrics with custom SVGs and GitHub Actions. - Source: dev.to / about 1 year ago
Metrics this will generate a detailed stats infographic based on your GitHub Profile. - Source: dev.to / about 2 years ago
Another GitHub profile using lowlighter/metrics with a slightly different setup. - Source: dev.to / almost 3 years ago
Using projects like this is an easy way to make your Github profile really standout. Source: over 3 years ago
Lowlighter/metrics is a GitHub repo you will fall in love with if you adore easy-to-use upgrading capabilities for your GitHub README.md through GitHub Actions. - Source: dev.to / about 4 years 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 / about 2 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 / about 2 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 / 3 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
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
GitWrapped - View/Share how you contributed to Github over the years
JavaScript - Lightweight, interpreted, object-oriented language with first-class functions
Contributions for GitHub - Show your GitHub contributions graph on your iOS Devices
Java - A concurrent, class-based, object-oriented, language specifically designed to have as few implementation dependencies as possible
GitPrime - GitPrime uses data from any Git based code repository to give management the software engineering metrics needed to move faster and optimize work patterns.
C++ - Has imperative, object-oriented and generic programming features, while also providing the facilities for low level memory manipulation
