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Causal App PythonNo Causal App 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 Causal App. While we know about 299 links to Python, we've tracked only 20 mentions of Causal App. 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.
Financial planning tools are another major category. Causal, a financial planning platform, integrated with customers' accounting systems to pull financial statement data into an AI-powered modeling tool. Users connect their QuickBooks or Xero account, and the platform auto-generates financial models with metrics like burn rate and runway, updated on a recurring schedule. Cash flow data is especially valuable... - Source: dev.to / 6 days ago
This is exactly what I loved about the Causal app (no affiliation). They started as a general purpose spreadsheet with 'Amb' cells built-in, though later on they seem to have converged on the financial modeling space. [0]: https://causal.app/. - Source: Hacker News / over 1 year ago
It looks like Causal (https://causal.app) has pivoted to focus on businesses. There are a lot use cases for individual users to build models with probabilistic parameters that are no longer possible due to the high cost (example: https://netlify.causal.app/buy). Is there another spreadsheet + probabilistic model parameter tool available for individual users? - Source: Hacker News / almost 2 years ago
IMO the better paradigm is coming from enterprise applications like Anaplan. Cells are not the right abstraction to work with numbers. Most of the time you work with multi-dimensional quantities (eg revenue by product, geography, month). Weโre working on a more approachable implementation of that paradigm at https://causal.app. - Source: Hacker News / about 2 years ago
We're using Hypertune at https://causal.app for a few months now and it's been great! We have a few feature flags in there but also some more complex typed data for our onboarding modals. - 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 / 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
Forecastr - Forecastr is a seed-stage, B2B SaaS startup that has raised over $3M in capital, and has gone through the Techstars accelerator program.
JavaScript - Lightweight, interpreted, object-oriented language with first-class functions
Finmark - Financial planning software for startups
Java - A concurrent, class-based, object-oriented, language specifically designed to have as few implementation dependencies as possible
PrometAI - PrometAI is an AI business plan maker, that can generate a detailed business plan in seconds. Harness the power of AI for strategic insights and future success.
C++ - Has imperative, object-oriented and generic programming features, while also providing the facilities for low level memory manipulation
