PyCon JP 2022 adoption meeting was held & Bulletin of Talk Adoption

Hi, I'm Peacock, the PyCon JP 2022 Vice Chair.

Thank you for submitting your proposal for PyCon JP 2022.
In Tokyo, we had the PyCon JP 2022 adoption meeting yesterday, Sunday, 2022/07/10.

Overview of the Talk Adoption Status

A total of 120 proposals were submitted this year, from which 45 were selected.
The overall acceptance rate was 37.5%.
The breakdown by language was 40.26% (31/77) for Japanese and 32.56% (14/43) for English.

More English proposals were submitted this year, and the quality was very high compared to previous years.

PyCon JP 2022 Talk Adoption Bulletin Report

Now, here is the news you have all been waiting for. The following titles of talks have been accepted!

The reviews and adoptions were based on the perspectives already shared.
Only one talk per submitter will be adopted. (We do not accept multiple submissions from the same submitter.)

IMPORTANT: The adopters will receive an email from the CfP system (pretalx) later to confirm whether or not they accept the adoption. Please note that the acceptance will not be confirmed until you respond within the deadline.

List of Accepted Talks

The following titles of talks have been accepted. (They are sorted by alphabetically.)
  • AST(Abstract Syntax Tree)に入門する
  • Automate the Boring Stuff with Slackbot(ver.2)
  • Building Pytest Plugins
  • Don’t let your data model `drift` away!
  • Effective data science teams with Jupyter and databooks
  • Fast API と学ぶ WebRTC
  • GeoDjango ORMと地理空間データの世界
  • Introducing new game development stack using XState, PyScript and Atri
  • Jupyter - Under the Hood
  • Modernizing development workflow for a 7-year old 74K LoC Python project using Pantsbuild
  • Network Science with Python
  • NLPを活用したアプリチュートリアルの改善とコールドスタート問題への対策
  • Pandas卒業?大規模データを様々なパッケージで高速処理してみる
  • Playwrightを使って簡単に自動テストしてみる
  • Pybind11を用いたC拡張の開発
  • Python Socal Authで学ぶ、OAuth2.0認可フローにおける異常系への対処
  • Python ライブラリ開発における失敗談 〜開発者に選ばれるライブラリを作るために必要なこと〜
  • Python/PyQtとQGISではじめる公共交通分析
  • Python3.11新機能asyncio.TaskGroup()と2022年asyncioの"Hello-ish world"
  • Pythonではじめる地理空間情報
  • Pythonで公的統計APIのオープンデータ活用
  • Pythonとアスタリスク 🐍🌟💫🐍🌟💫
  • Pythonに上級テクニックは要らない(そして正しい付き合い方)
  • Python使いのためのスポーツデータ解析のきほん - PySparkとメジャーリーグデータを添えて
  • Reinforcement learning for guiding swarm of robots using python
  • Security Best Practices for Django Applications
  • setuptoolsの最近
  • Sphinxを通して考える、「拡張」の仕方
  • Synergize AI and Domain Expertise - "SHAP" Explainability Check with Python
  • Tracking the invisible: Geoinformatics and Human Social Behavior
  • Using Python for Disease Variant Analysis
  • What Starlette really do for FastAPI
  • What's new in Python 3.11 and beyond
  • Working with Rust and Python using PyO3
  • イベント駆動アーキテクチャについて
  • エッジAI開発入門
  • お前はまだ本当のDjango ASGIを知らない。
  • コーディング規約自動化: PyLintのカスタムルールを作ろう
  • データに関する堅牢性と可読性を向上させるpydanticとpanderaの活用方法の提案
  • はじめての量子コンピューター
  • 業務改善の面白さ ~毎日更新されるビジュアルコンテンツの差分をわかりやすくするためのプロトタイプを作るまで~
  • 実践:日本語文章生成 Transformersライブラリで学ぶ実装の守破離
  • 詳解 print("Hello, world")
  • 情報システム部門の業務におけるPythonの活用
  • 続・絵を読む技術 Pythonで読むイラストの心理戦略

Talks on the waiting list

And here are the talks that made the waiting list (also in alphabetically)
Proposals on this list are that may be moved up in the event that confirmation of selection cannot be obtained from the submitter of an accepted proposal.
The reason we have more English talks on the waiting list is that we are assuming that there will be people who will be traveling from overseas.
Those submitting here will also be given priority for the Distant Assistance Program, which will be announced later.

  • aioauth+FastAPIでOAuth2.0を学ぶ
  • Better project maintenance with static analysis
  • Building & testing Cloud applications locally using LocalStack
  • CPythonはどのようにして文のブロック構造をインデントで実現しているか
  • Data driven approach to analyze the efficacy of LEED certified buildings using python.
  • JAXA Earth API for Python : より自由な衛星データ利用へ向けたAPIの開発と公開
  • Python 1994
  • PyTorch Lightning で深層学習する
  • SQL クエリ解析による E2E データリネージの実現
  • Type erasure in Python
  • Visualisation of Experimental Data Obtained at Seven Times the Speed of Sound
  • データの品質向上に Confident Learning で挑む
  • ログって何に使うんですか?


Once again, thank you to the reviewers for the many objective reviews. (We felt we were able to meet a sufficient number of reviews this year.)
We would also appreciate your continued cooperation with staffing on the day of the event, which we will be recruiting later.

Update on 2022/07/15: Added the explanation about the waiting list

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