New video with Vladimír Gorej of Jentic, one of the long-time, well-known contributors in the OpenAPI (and AsyncAPI) ecosystem. We talk about a new open-source Python toolkit for working with OpenAPI descriptions programmatically: 🎥 OpenAPI Tools for Python: Parse, Validate, Transform, and Analyze OpenAPI Descriptions - https://lnkd.in/dzJWKKU7 If you care about standards, this is a good example of why they matter: the spec is only part of the story. The ecosystem of tooling that grows around it is what makes it truly useful. If you're working with OpenAPI in Python, check out OpenAPI Tools: 👉 OpenAPI Tools GitHub repo - https://lnkd.in/d6i3vFQP Vladimir built Jentic OpenAPI Tools out of a practical need: a reliable way to parse, validate, transform, and analyze OpenAPI in Python, with a consistent object model you can build on. We've already built on top of it — one example is the Jentic API Scorecard. 👉 API Scorecard for rating APIs - https://lnkd.in/gTBGABpT #api #apimanagement #apidesign #apiplatform OpenAPI Initiative Getting APIs to Work
OpenAPI Tools for Python: Parse, Validate, Transform and Analyze
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One of the benefits of standards is the ecosystem of tools available to use. These can be COTS tools or libraries such as this new Python toolkit for working with OpenAPI descriptions.
New video with Vladimír Gorej of Jentic, one of the long-time, well-known contributors in the OpenAPI (and AsyncAPI) ecosystem. We talk about a new open-source Python toolkit for working with OpenAPI descriptions programmatically: 🎥 OpenAPI Tools for Python: Parse, Validate, Transform, and Analyze OpenAPI Descriptions - https://lnkd.in/dzJWKKU7 If you care about standards, this is a good example of why they matter: the spec is only part of the story. The ecosystem of tooling that grows around it is what makes it truly useful. If you're working with OpenAPI in Python, check out OpenAPI Tools: 👉 OpenAPI Tools GitHub repo - https://lnkd.in/d6i3vFQP Vladimir built Jentic OpenAPI Tools out of a practical need: a reliable way to parse, validate, transform, and analyze OpenAPI in Python, with a consistent object model you can build on. We've already built on top of it — one example is the Jentic API Scorecard. 👉 API Scorecard for rating APIs - https://lnkd.in/gTBGABpT #api #apimanagement #apidesign #apiplatform OpenAPI Initiative Getting APIs to Work
OpenAPI Tools for Python: Parse, Validate, Transform, and Analyze OpenAPI Descriptions
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Great conversation on why 𝐬𝐭𝐚𝐧𝐝𝐚𝐫𝐝𝐬 𝐨𝐧𝐥𝐲 𝐛𝐞𝐜𝐨𝐦𝐞 𝐩𝐨𝐰𝐞𝐫𝐟𝐮𝐥 𝐰𝐡𝐞𝐧 𝐬𝐭𝐫𝐨𝐧𝐠 𝐭𝐨𝐨𝐥𝐢𝐧𝐠 𝐠𝐫𝐨𝐰𝐬 𝐚𝐫𝐨𝐮𝐧𝐝 𝐭𝐡𝐞𝐦. #openapi #python #tools #datamodel One thing I want to emphasize about 𝐉𝐞𝐧𝐭𝐢𝐜 𝐎𝐩𝐞𝐧𝐀𝐏𝐈 𝐓𝐨𝐨𝐥𝐬 that we touched on only briefly in the video: the toolkit is designed not just for parsing OpenAPI, but for deep, reliable document analysis. In practice, that means: ✅ 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧-𝐫𝐞𝐚𝐝𝐲 𝐰𝐢𝐭𝐡 𝐩𝐨𝐩𝐮𝐥𝐚𝐫 𝐉𝐚𝐯𝐚𝐒𝐜𝐫𝐢𝐩𝐭 𝐀𝐏𝐈 𝐠𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 𝐭𝐨𝐨𝐥𝐬 (linting, rulesets, quality checks) 🧠 An 𝐚𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐬𝐞𝐦𝐚𝐧𝐭𝐢𝐜 𝐥𝐨𝐰-𝐥𝐞𝐯𝐞𝐥 𝐝𝐚𝐭𝐚 𝐦𝐨𝐝𝐞𝐥 (not just a schema wrapper) 🧭 𝐂𝐨𝐦𝐩𝐥𝐞𝐭 𝐬𝐨𝐮𝐫𝐜𝐞𝐦𝐚𝐩𝐬, so every finding can be traced back to the exact location in the original OpenAPI document This makes it particularly well-suited for 𝐀𝐏𝐈 𝐠𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞, 𝐬𝐜𝐨𝐫𝐢𝐧𝐠, 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧, 𝐚𝐧𝐝 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐞𝐝 𝐚𝐧𝐚𝐥𝐲𝐬𝐢𝐬 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬, where precision and traceability really matter. If you work with OpenAPI at scale, especially across Python ecosystems, this kind of foundation makes a big difference.
New video with Vladimír Gorej of Jentic, one of the long-time, well-known contributors in the OpenAPI (and AsyncAPI) ecosystem. We talk about a new open-source Python toolkit for working with OpenAPI descriptions programmatically: 🎥 OpenAPI Tools for Python: Parse, Validate, Transform, and Analyze OpenAPI Descriptions - https://lnkd.in/dzJWKKU7 If you care about standards, this is a good example of why they matter: the spec is only part of the story. The ecosystem of tooling that grows around it is what makes it truly useful. If you're working with OpenAPI in Python, check out OpenAPI Tools: 👉 OpenAPI Tools GitHub repo - https://lnkd.in/d6i3vFQP Vladimir built Jentic OpenAPI Tools out of a practical need: a reliable way to parse, validate, transform, and analyze OpenAPI in Python, with a consistent object model you can build on. We've already built on top of it — one example is the Jentic API Scorecard. 👉 API Scorecard for rating APIs - https://lnkd.in/gTBGABpT #api #apimanagement #apidesign #apiplatform OpenAPI Initiative Getting APIs to Work
OpenAPI Tools for Python: Parse, Validate, Transform, and Analyze OpenAPI Descriptions
https://www.youtube.com/
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📺🐍 Create Callable Instances With Python's .__call__() Learn Python callables: what "callable" means, how to use dunder call, and how to build callable objects with step-by-step examples https://lnkd.in/dcPrVFfS
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Python Starters Daily Nugget Exploring Python's Built-in Functions len() sum() max() range() enumerate() These save you some lines of code. So, knowing what is built-in makes your code efficient. Follow the Python 🐍 Starters Hub: WhatsApp: https://lnkd.in/dbjAFv52 LinkedIn: https://lnkd.in/dkJE3tZq
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🚀 Python OOPS – Day 7 🔧 __init__() Method (Constructor in Python) The __init__() method is Python’s constructor, automatically executed when an object of a class is created. Its main purpose is to initialize instance attributes and prepare the object for use. In simple terms: ➡ Class = Blueprint ➡ Object = Actual instance ➡ Constructor = Sets initial values inside the object The method takes self as its first parameter, representing the specific instance being created. 📝 Key Highlights ✔ Called automatically during object creation ✔ Initializes attributes with default or custom values ✔ Makes objects ready for immediate use Example use cases: 🎯 student registration, 🎯 user account creation, 🎯 order processing—all require initialization at the moment of creation.
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🚀 Python OOPS – Day 7 🔧 __init__() Method (Constructor in Python) The __init__() method is Python’s constructor, automatically executed when an object of a class is created. Its main purpose is to initialize instance attributes and prepare the object for use. In simple terms: ➡ Class = Blueprint ➡ Object = Actual instance ➡ Constructor = Sets initial values inside the object The method takes self as its first parameter, representing the specific instance being created. 📝 Key Highlights ✔ Called automatically during object creation ✔ Initializes attributes with default or custom values ✔ Makes objects ready for immediate use Example use cases: 🎯 student registration, 🎯 user account creation, 🎯 order processing—all require initialization at the moment of creation.
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How to Integrate Local LLMs With Ollama and Python From https://lnkd.in/eSQ9f-Pp Learn how to integrate your Python projects with local models (LLMs) using Ollama for enhanced privacy and cost efficiency.
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How to Integrate Local LLMs With Ollama and Python From https://lnkd.in/eSQ9f-Pp Learn how to integrate your Python projects with local models (LLMs) using Ollama for enhanced privacy and cost efficiency.
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BSON to JSON: The Python Way By Mario García Through this blog post, you will learn how to convert a BSON document to JSON using Python. If you’re a Python developer, there are two ways for reading a BSON document and converting it to JSON. Using the bson module from PyMongo from bson import decode_all from bson.json_util import dumps ... https://lnkd.in/ePMux47x
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Create Callable Instances With Python's .__call__() From https://lnkd.in/eyC4kxEy Learn Python callables: what "callable" means, how to use dunder call, and how to build callable objects with step-by-step examples.
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