An open and universal framework for processing spatial omics data. — spatialdata

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Free GIS Datasets - Categorised List
Geoportal
Esri Geoportal Server | Open-Source Metadata Management
Esri Geoportal Server is a free, open-source, stand-alone metadata catalog management app that enables discovery and use of geospatial resources such as datasets, raster data & web services.
Building a Large Geospatial Model to Achieve Spatial Intelligence
At Niantic, we are pioneering the concept of a Large Geospatial Model that will use large-scale machine learning to understand a scene and connect it to millions of other scenes globally.
Klarety
Empower geospatial data, deploy AI, automate satellite analysis - unveil insights, unify action
Julius AI | Your AI Data Analyst
Julius is a powerful AI data analyst that helps you analyze and visualize your data. Chat with your data, create graphs, build forecasting models, and more.
GeoLLM: Extracting Geospatial Knowledge from Large Language Models
Rube
Rube by Composio, somethings connect to something, something happens
Abacus.AI - DeepAgent Apps How-To
Abacus.AI - DeepAgent How-To
Abacus.AI - DeepAgent
A god-tier general agent
Blitzy: AI-Powered Autonomous Software Development Platform
Blitzy: Build enterprise software in days with our autonomous AI platform. Automate up to 80% of development. Infinite code context. Accelerate your roadmap by 5x.
awesome-gee-community-catalog - awesome-gee-community-catalog
Community Datasets in Google Earth Engine
DevSheets - Developer Cheat Sheets
Comprehensive collection of developer cheat sheets and quick reference guides
WebUtils.io - Free Online Web Utilities & Developer Tools
Privacy-first web utilities for developers. JSON formatter, Base64 converter, QR generator, password creator, and more. All processing happens locally in your browser.
API Probe - Simple API Testing Tool
A simple and clean API testing tool built with Next.js
ApiMocker
Free fake REST API service with multiple resources. Perfect for development, testing, and tutorials.
5 Strategies for Smart Land Valuation Analytics in Acquisition
Explore smart land valuation analytics and discover strategies for efficient land acquisition.
Managing Geospatial Data with PostgreSQL and PostGIS: A Developer's Guide
Learn how to effectively manage and analyze geospatial data using PostgreSQL and PostGIS. This comprehensive guide covers spatial queries, performance optimization, advanced features, and integration with GIS tools. Perfect for developers working on location-based applications and GIS projects.
Soil health data cube - AI4SoilHealth
AI4SoilHealth is building a Soil Health Data Cube to aid the sustainable management of Europe’s soils by integrating crucial data on soil, climate, and
Cloud Optimized Geotiffs
UArizona DataLab Workshops
paradoxical-fermi/YTDLP_DanielsAllInOneYouTubeVideoDownloader.ps1 at main · dverbern/paradoxical-fermi
A repository of the scripts I've written to simplify my working life ... or just for my own enjoyment. - dverbern/paradoxical-fermi
POWERSHELL: USE PARAMETERS AND CONFIGURATION FROM INI FILE, USE AS SPLATTING
I was working on one of my friends requirement for automating scripts, He wanted a safe way to use parameters and configuration values from external file instead of modifyi...
How to Generate JSON Schema Effectively and Efficiently
Creating a JSON schema can be a crucial step in ensuring data consistency and quality, especially when dealing with APIs and data exchange. Below is a detailed guide on how to create a JSON schema:
Extending Object Definitions With OpenAPI's allOf
Did you know you can define object inheritance using OpenAPI?
Getting Creative with OpenAPI - by David Biesack
Defining resource creation and update operations with OpenAPI
unevaluatedProperties: false
This article pulls in lots of aggregated knowledge from earlier articles in the Language of API Design series:
Mapping a domain model to OpenAPI
Patterns for clean URLs and URL structure
Defining the request body for a POST operation
Defining API responses with OpenAPI response objects and response body data format with JSON Schema
Composing JSON Schemas to keep the OpenAPI definition DRY
Understanding the subtleties of JSON schema (notably, unevaluatedProperties)
Defining reusable response objects to keep the OpenAPI definition DRY
Defining how the API handles problems with client requests as well as server errors
Validating API Requests - by David Biesack
Techniques for API Request Validation
A promise of REST APIs is good decoupling of clients and services. This is achieved in part by reducing business logic as much as possible in the client application. For example, a client application may use a form for collecting information used in a POST operation to create an API resource, or to edit an existing resource before updating it with a PUT or PATCH operations. The client then maps the form fields to the properties of the operation’s request body. Clients can use front end frameworks and libraries to perform lots of low-level validation in the front end corresponding to JSON schema constraints.
However, this only covers “syntactic” or static field-level validation. Often, an API will also have business rules that the client must follow. Secure API services will enforce those business rules in the API operations
Parse the options and (JSON) request body and return a 400 Bad Request if any of the request data is malformed (i.e. does not satisfy the constraints of the operation (such as required body or required parameters) or all the JSON Schemas associated with the operation’s parameters or request body)
Verify that the caller passes valid Authorization to the API call, and return 401 Unauthorized if not
Verify that the caller is authorized to perform the API operation, and return a 403 Forbidden error if not.
Verify the state of the application and return 409 Conflict if the operation would put the application into an inconsistent state
Verify the semantics of the request body and return a 422 Unprocessable Content error if the request is incomplete, inconsistent, or otherwise invalid
One pattern is to extend the API operations with a dry run feature. A dry run is a variant of the API operation which performs all (and only) the validation performed by the full operation, but does not execute the associated behavior. As such, it will return the same 400/401/403/409/422 that the full operation would return, allowing the client to highlight invalid form data or otherwise correct the problem. The client can use dry run operation incrementally as the user fills out a form, and disable the “Save” or “Submit” or similar UI controls if there are validation errors.
One way to implement a dry run is to create a separate "validation” operation for each API operation. This has the significant disadvantage of greatly increasing the footprint (size) of the API and adding a lot of duplication.
Rather than duplicate operations to add sibling validation operations, another approach is to add a ?dryRun=true query parameter to the operations. When used, the operation can return 204 No Content if the request contains no problems. The dryRun parameter acts as a “short circuit” in the API operation. The implementation performs the full validation it would normally do before executing the desired behavior, but then stops before actually executing anything other than the validation.
This pattern has a small impact on the API footprint compared to making sibling validation operations. A smaller footprint makes the API easier to read and understand. It is also a good use of the DRY principal, since you do not have to duplicate the definition of all the operation request parameters and request bodies, which opens up the chance for them to become out of sync.
Leave a calling card - by David Biesack
Make API responses more self-descriptive with reference objects
In OAS, a reference object contains a $ref value and may contain summary or description values. However, there is a kernel of usefulness here that can be used outside of defining an API with OpenAPI — we can use a construct inspired by OAS reference objects instead of terse and cryptic Restful JSON URLs or naked resource ID properties.
Such reference objects in API responses (or requests) can include other key identifying data about the referenced resource; these are optional and informative. The id or url of the resource are required to actually identify the referenced resource. This makes the overall JSON payload more self-descriptive and does not send the developer down ratholes trying to understand data they see when exploring and learning the API.
To make these reference objects even more useful, the API service can build them for you instead of making the client construct them. For example, the response from the getUniverse operation can contain a reference or ref property which is the reference object that the client can embed in other requests when citing a universe. The *Item schema in the API’s list responses (see “What am I getting out of this?”) can also include the reference object.
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