everyday.app
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Based on our record, Python should be more popular than everyday.app. It has been mentiond 299 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.
The app looks good so far! As the indie developer behind https://everyday.app I'm happy to see more indies joining the market :) You have a lot of work to do ahead!! Heheh Cheers and happy to help! - Source: Hacker News / over 2 years ago
Https://everyday.app supports android and ios too. - Source: Hacker News / over 2 years ago
I have a list of 5 things that I do every day without fail and I check them off the app I have. (https://everyday.app). Source: about 3 years ago
I think Op might try to set two goals and use an app like https://everyday.app to track them. Source: about 3 years ago
I use https://everyday.app as a habit tracker :P It is actually my business. It started as a side-project but I kept working on it and now I make a decent living from it. So I like I can keep tweaking it to adapt to my personal system and feedback I get :p. - Source: Hacker News / about 3 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 / 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 / 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
Habitify - The easiest way to keep track of your habits
JavaScript - Lightweight, interpreted, object-oriented language with first-class functions
Polar Habits - Guilt-free habit tracking ๐ปโโ๏ธ
Java - A concurrent, class-based, object-oriented, language specifically designed to have as few implementation dependencies as possible
HabitKit - Habit Tracker - Track your consistency with cool grids
C++ - Has imperative, object-oriented and generic programming features, while also providing the facilities for low level memory manipulation
