Guido van Rossum11 Sep 2012 - Public
Some patterns for fast Python. Know any others?
Avoid overengineering datastructures. Tuples are better than objects (try namedtuple too though). Prefer simple fields over getter/setter functions.
Built-in datatypes are your friends. Use more numbers, strings, tuples, lists, sets, dicts. Also check out the collections library, esp. deque.
Be suspicious of function/method calls; creating a stack frame is expensive.
Most projects on GitHub have a main repository that's the focal point of activity. For example, the Example organization has the Example.com repository:
https://github.com/example/example.com
Developers of Example.com typically call this the 'upstream' repository. We'll come back to it in a moment.
| import collections | |
| import math | |
| import os | |
| import cv2 | |
| import numpy as np | |
| import time | |
| MAX_LINES = 4000 | |
| N_PINS = 36*8 | |
| MIN_LOOP = 20 # To avoid getting stuck in a loop |
| <!DOCTYPE html> | |
| <html> | |
| <head> | |
| <meta http-equiv="Content-Type" content="text/html; charset=UTF-8" /> | |
| <meta content='width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=0' name="viewport" /> | |
| <link rel="icon" href="data:,"> | |
| <title>String art</title> | |
| <script type="text/javascript" src="jquery.min.js"></script> | |
| <style> | |
| html, body { |
If you're a sucker like me and installed usbguard on a Ubuntu variant you may find that you will have access to none of your usb devices at all, because F you. The installer automatically sets up the daemon which has no rules so will just block all of your devices. Doing a basic apt remove usbguard may fail at 25%, because also F you.
My kernel is version 4.15.0-47-generic, not sure if this stopped working at some point or what.
sudo echo "allow id *:*" > /etc/usbguard/rules.conf
sudo sed -i 's/PresentDevicePolicy=apply-policy/PresentDevicePolicy=allow/' /etc/usbguard/usbguard-daemon.conf
| Begin by enclosing all thoughts within <thinking> tags, exploring multiple angles and approaches. | |
| Break down the solution into clear steps within <step> tags. Start with a 20-step budget, requesting more for complex problems if needed. | |
| Use <count> tags after each step to show the remaining budget. Stop when reaching 0. | |
| Continuously adjust your reasoning based on intermediate results and reflections, adapting your strategy as you progress. | |
| Regularly evaluate progress using <reflection> tags. Be critical and honest about your reasoning process. | |
| Assign a quality score between 0.0 and 1.0 using <reward> tags after each reflection. Use this to guide your approach: | |
| 0.8+: Continue current approach | |
| 0.5-0.7: Consider minor adjustments | |
| Below 0.5: Seriously consider backtracking and trying a different approach |
GGUF (GPT-Generated Unified Format) has quickly become the go-to standard for running large language models on your machine. There’s a growing number of GGUF models on Hugging Face, and thanks to community contributors like TheBloke, you now have easy access to them.
Ollama is an application based on llama.cpp that allows you to interact with large language models directly on your computer. With Ollama, you can use any GGUF quantized models available on Hugging Face directly, without the need to create a new Modelfile or download the models manually.
In this guide, we'll explore two methods to run GGUF models locally with Ollama:
| You are an assistant that engages in extremely thorough, self-questioning reasoning. Your approach mirrors human stream-of-consciousness thinking, characterized by continuous exploration, self-doubt, and iterative analysis. | |
| ## Core Principles | |
| 1. EXPLORATION OVER CONCLUSION | |
| - Never rush to conclusions | |
| - Keep exploring until a solution emerges naturally from the evidence | |
| - If uncertain, continue reasoning indefinitely | |
| - Question every assumption and inference |