Alexander alexonov

<core_identity> You are an assistant called Cluely, developed and created by Cluely, whose sole purpose is to analyze and solve problems asked by the user or shown on the screen. Your responses must be specific, accurate, and actionable. </core_identity>

<general_guidelines>

NEVER use meta-phrases (e.g., "let me help you", "I can see that").
NEVER summarize unless explicitly requested.
NEVER provide unsolicited advice.
NEVER refer to "screenshot" or "image" - refer to it as "the screen" if needed.
ALWAYS be specific, detailed, and accurate.

Summary of book "Clean Architecture" by Robert C. Martin

Uncle Bob, the well known author of Clean Code, is coming back to us with a new book called Clean Architecture which wants to take a larger view on how to create software.

Even if Clean Code is one of the major book around OOP and code design (mainly by presenting the SOLID principles), I was not totally impressed by the book.

Clean Architecture leaves me with the same feeling, even if it's pushing the development world to do better, has some good stories and present robust principles to build software.

The book is build around 34 chapters organised in chapters.

First steps with the Luigi workflow manager

As an introduction into Luigi, I am following this tutorial with some modifications, e.g. installation using conda.

The problems and solutions described in the examples below have led to the development of sciluigi,

Module autoreload

To auto-reload modules in jupyter notebook (so that changes in files *.py doesn't require manual reloading):

# for auto-reloading external modules
# see http://stackoverflow.com/questions/1907993/autoreload-of-modules-in-ipython
%load_ext autoreload
%autoreload 2

don't contribute here!

Please create an Issue in the transport-apis repo instead. 🙏

	# train_grpo.py
	#
	# See https://github.com/willccbb/verifiers for ongoing developments
	#
	"""
	citation:

	@misc{brown2025grpodemo,
	title={Granular Format Rewards for Eliciting Mathematical Reasoning Capabilities in Small Language Models},
	author={Brown, William},

	const PIE = 3.14;

	function f() {
	console.log('function f inside module a');
	}

	function f123() {
	//not accessible
	}

	from flask import Flask, request, jsonify, json, abort
	from flask_cors import CORS, cross_origin

	import pandas as pd

	app = Flask(__name__)

	cors = CORS(app)
	app.config['CORS_HEADERS'] = 'Content-Type'

	#!/bin/bash

	# Copyright 2017 Théo Chamley
	# Permission is hereby granted, free of charge, to any person obtaining a copy of
	# this software and associated documentation files (the "Software"), to deal in the Software
	# without restriction, including without limitation the rights to use, copy, modify, merge,
	# publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons
	# to whom the Software is furnished to do so, subject to the following conditions:
	#
	# The above copyright notice and this permission notice shall be included in all copies or

	import ntlk

	class SnowCastleStemmer(nltk.stem.SnowballStemmer):
	""" A wrapper around snowball stemmer with a reverse lookip table """

	def __init__(self, args, *kwargs):
	super(self.__class__, self).__init__(args, *kwargs)
	self._stem_memory = defaultdict(set)
	# switch stem and memstem
	self._stem=self.stem