OpenRouter
liteLLM
APIPark
Eden AI
Portkey
fal
ChatGPT
OpenAI
Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
OpenRouter
MatplotlibNo features have been listed yet.
Based on our record, Matplotlib should be more popular than OpenRouter. It has been mentiond 114 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.
It's very easy to use other providers. See https://openrouter.ai/ which also let's you filter by where the provider is hosted and their data retention policy. - Source: Hacker News / 10 days ago
If you want to try it yourself: grab OpenCode, point it at OpenRouter, select GLM 5.2, and give it a real task instead of a benchmark. The z.ai docs have the rest of the details. - Source: dev.to / 14 days ago
Hosted, minimal ops. You want to be calling models in five minutes and you are fine paying a small fee for it. OpenRouter is the marketplace default โ 400+ models, ~5.5% on credits. Vercel AI Gateway and Cloudflare AI Gateway go further and charge 0% markup, billing you at provider list price while adding routing and caching on top. - Source: dev.to / 20 days ago
I use OpenRouter as the single door to a pile of models. Its BYOK (bring-your-own-key) feature has a trap. You add your own OpenAI key for a model, flip on "Always use for this provider," and read that as never spend OpenRouter credits. It doesn't mean that. - Source: dev.to / 22 days ago
Developer gateways - MegaLLM, Portkey, LiteLLM, OpenRouter. The pitch is reliability, failover, cost, analytics. They are headless: you get an API, you bring your own interface. Great for shipping code, nothing to actually use without building a client first. - Source: dev.to / 24 days ago
In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 4 months ago
Numbers are useful, but sometimes itโs easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 7 months ago
We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 7 months ago
NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 8 months ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 10 months ago
liteLLM - One library to standardize all LLM APIs
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
APIPark - โจ#1 Open Source AI Gateway & API Developer Portal
NumPy - NumPy is the fundamental package for scientific computing with Python
Eden AI - Regrouping the best AI APIs for 10mn integration in your code
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.