【光る君へ】藤原道長の家系図を Owlready2 で書く - Qiita
おはこんばんちわ。今日も引き続きChatGPT先生をお迎えして、「ChatGPTとPythonで学ぶ owlready2」というテーマで雑談したいと思います。それではChatGPT先生、よろしくお願いします。 assistant: おはようございます、そしてこんばんは。今日もよろしくお願いします。オウルReady2、面白いテーマになりそうですね。 Owlready2はPythonでOntology、特にOWL（Web Ontology Language）を操作するためのライブラリです。最初に言っときますが、このライブラリは深い専門知識を必要とする部分もあるので、ここで全てをカバーするのは難しいかもしれませんが、一緒に学んでいきましょう。 user: それでは早速。Owlready2 を使って、次の家系図をOWL形式に変換する Python コードを書いてください。得られた OWL 形式ファ
GitHub - logan-markewich/llama_index_starter_pack: This repository provides very basic flask, streamlit, and docker examples for the llama_index (fka gpt_index) package
There are two main example folders flask_react (runs three services on localhost:5601/5602/3000) sh launch_app.sh creates a simple api that loads the text from the documents folder (if any), also launches the react frontend the "/query" endpoint accepts requests that contain a "text" parameter, which is used to query the index the "/upload" endpoint is a POST endpoint that inserts an attached text
今時のPythonはこう書く2020 - Qiita
はじめに システム作ってるとかライブラリ作ってるみたいなある程度Pythonを綺麗に1書くことが求められる方々に向けた記事です。 (機械学習系のライブラリを使うためにPython書いてる方とか、初学者の方にはちょっとあわないかも知れません) 綺麗に書くための作法の難しさって共有が面倒なところだと思うんですよね。その書き方は間違いじゃない、間違いじゃないけどもっといい書き方があるぞみたいなやつってなかなか指摘し辛いですし、じゃあ1人に対してレビューしたら他のメンバーにはどう伝える？そもそも伝える必要？俺の工数は？みたいになりがちです。 一番いいのはこういう時はこう書く！みたいなドキュメントを作って「ドキュメント違反です」ってレビューをしてあげることなんですが、まーそれもそれで超面倒じゃないですか。なのでこの記事がそのドキュメントの代わり、とまではいかなくとも礎くらいになればいいなと思って書き
PEP 8: The Style Guide for Python Code
This stylized presentation of the well-established PEP 8 was created by Kenneth Reitz (for humans). Introduction This document gives coding conventions for the Python code comprising the standard library in the main Python distribution. Please see the companion informational PEP describing style guidelines for the C code in the C implementation of Python 1. This document and PEP 257 (Docstring Con
How Docker Can Help You Become A More Effective Data Scientist
By Hamel Husain For the past 5 years, I have heard lots of buzz about docker containers. It seemed like all my software engineering friends are using them for developing applications. I wanted to figure out how this technology could make me more effective but I found tutorials online either too detailed: elucidating features I would never use as a data scientist, or too shallow: not giving me enou
Python Numpy Tutorial (with Jupyter and Colab)
This tutorial was originally contributed by Justin Johnson. We will use the Python programming language for all assignments in this course. Python is a great general-purpose programming language on its own, but with the help of a few popular libraries (numpy, scipy, matplotlib) it becomes a powerful environment for scientific computing. We expect that many of you will have some experience with Pyt
A Practical Introduction to Deep Learning with Caffe and Python // Adil Moujahid // Bridging Tech and Art
A Practical Introduction to Deep Learning with Caffe and Python // tags deep learning machine learning python caffe Deep learning is the new big trend in machine learning. It had many recent successes in computer vision, automatic speech recognition and natural language processing. The goal of this blog post is to give you a hands-on introduction to deep learning. To do this, we will build a Cat/D
Pythonライブラリを作成してPyPIに登録する - shoya.io
Confusion Matrix(混同行列)を視覚的に描画するdalmatianというライブラリを作成してPyPIに登録しました(ソースコードはGitHubで公開)。パッケージの作成とPyPIへの登録、情報が少なくて苦労したので、必要なファイルと公開手順のメモを残しておきます。 ファイル構成 dalmatian ├── README.md ├── dalmatian │ ├── __init__.py │ ├── matrix.py │ └── test.py ├── register.py └── setup.py dalmatian/dalmatian/matrix.pyがモジュールの実体でtest.pyがテストファイルです。必要なファイルはsetup.pyと__init__.py。register.pyやREADME.mdは任意。 setup.py # coding: u
Dive Into Python 3
Dive Into Python 3 covers Python 3 and its differences from Python 2. Compared to Dive Into Python, it’s about 20% revised and 80% new material. The book is now complete, but feedback is always welcome. Table of Contents (expand) Also available on dead trees! What’s New in “Dive Into Python 3” Installing Python Your First Python Program Native Datatypes Comprehensions Strings Regular Expressions C
GitHub - datasciencemasters/go: The Open Source Data Science Masters
Note from the Editor: Take Two In the old days of 2013, the OSDSM was born. Then, there were "little to no Data Scientists with 5 years experience, because the job simply did not exist." (David Hardtke, Nov 2012) Since then, history has witnessed many things, including: • Data Scientists working across industries and the world • social media manipulation disrupts many elections • BLM and #metoo an
The Python Tutorial
The Python Tutorial¶ Python is an easy to learn, powerful programming language. It has efficient high-level data structures and a simple but effective approach to object-oriented programming. Python’s elegant syntax and dynamic typing, together with its interpreted nature, make it an ideal language for scripting and rapid application development in many areas on most platforms. The Python interpre
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GitHub - The-Japan-DataScientist-Society/100knocks-preprocess: データサイエンス100本ノック（構造化データ加工編）
GitHub - cosmicpython/book: A Book about Pythonic Application Architecture Patterns for Managing Complexity. Cosmos is the Opposite of Chaos you see. O'R. wouldn't actually let us call it "Cosmic Python" tho.
GitHub - faif/python-patterns: A collection of design patterns/idioms in Python
Python's pathlib Module: Taming the File System – Real Python
Scipy Lecture Notes — Scipy lecture notes