Python Recipes vs Vision Detector

An everyday Python reference, from strings and collections to threading and design patterns. Tricky parts of the examples are explained in comments. You know what you need, but the exact syntax escapes you: • How do I sort a dict by value? • How do I serialize an object to JSON and back? • How do I start a thread and wait for it to finish? Each has a working example here, ready to adapt to your code. • 22 sections, including classes, functions and lambdas, files, serialization, exceptions, regular expressions, databases and algorithms. • Language changes by version, Python 3.0 to 3.13: the walrus operator, match statements, dataclasses, free-threading and more, with before-and-after code. • Keyword and function reference: over 200 entries. Browse, search, or tap a word in the code to look it up. • SQL included: JOIN, GROUP BY, subqueries, data types; more than half of the queries run on a real practice database. • No IDE or local Python needed: over 90% of examples run in the app, with the output right below the code. • Search covers the code itself, not just titles: type a fragment you remember and find the example. • Edit examples or add your own; changes are saved in the app. • Everything except running code works offline. No account needed. Examples are curated from professional sources and checked before release: the code works and is easy to follow. FREE VERSION • 12 runs (examples and SQL combined) and 12 edits a day • Keyword and function reference with no limits • Up to 5 examples of your own The full version unlocks every example and query, removes the limits on edits and on your own examples, and raises the daily run limits to 30 for examples and 80 for SQL. One-time purchase, no subscription. Built by a developer for developers. The project behind it has been in active development since 2015.

Vision Detector is an AI image analysis tool that supports CoreML machine learning models, multi-modal Large Language Models, and on-device Apple Intelligence. Choose the mode that best fits your use case. You can choose one of the following image input sources: - Live video by built-in camera - Still image by the built-in camera - Photo Library - Files (iCloud, Google Drive, Dropbox, etc) For live video inputs, continuous inference is performed on the camera feed. However, the frame rate and other parameters depend on the device. # Notification Center Vision Detector can call Notification Center for predefined conditions. Broadcasting notifications send notification to your all Apple devices signed in with the same Apple Account. ## CoreML Mode Vision Detector locally executes CoreML models using Apple’s Vision framework. Before using this mode, prepare a machine learning model in the CoreML format (.mlmodel or .mlpackage) using Create ML. Import ML models via iClpoud or AirDrop. Vision Detector supports the following types of CoreML models: - Image classification - Object detection - Style transfer ## Vision LLM Mode Vision Detector can use multi-modal large language model (LLMs). Define what to do with prompt as following samples: - If the image is screen shot, answer the name software - Call notification when you see a cat - Count number of persons in the image, and notify when it changes ## Apple Intelligence mode Available with iOS 27 on selected devices (iPhone 17 Pro, iPhone Air, etc). The images are completely processed on your device locally with your prompt.