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GIS (StackExchange) user Ms05 just made a new post with the tags: python, fme-form. Would you like to know more? Click here to find out more details! StackExchange content licensed as: CC BY-SA 4.0

FME Hub user wghmapgear just uploaded a new transformer to the FME Hub. GeoApps Version Validator With this transformer, you can easily validate if your GeoApps environment matches the minimum required version to use with FME. It also verifies if the required license is available on your GeoApps environment to use of this integration. At last, you can use this transformer to validate your setup: it is a simple request that verifies if you are able to connect to your GeoApps environment. Prerequisites To use this transformer, you need to have an active GeoApps subscription and a user account with enough permissions to run the jobs. In addition, you need to first set up a web connection to GeoApps from FME. You can find the web connection in the FME Hub at https://hub.safe.com/publishers/mapgear/web-connections/geoapps. How to use? Add the transformer in your workspace, and configure the parameters. You need to set up two parameters: the tenant name, and the web connection to GeoApps. Af

FME Hub user wghmapgear just uploaded a new transformer to the FME Hub. GeoApps Attribute Name Verifier Eliminate data compatibility issues before they happen! With this transformer, you can easily verify that your feature attributes in FME are fully compatible with GeoApps, saving you time, preventing errors, and ensuring smooth data workflows. Perfect for data professionals who demand reliability and efficiency in their geospatial data preparation workflows. Whether you're working with complex enterprise datasets or simple feature collections, this transformer helps you in every way when transferring data to GeoApps. ⚡ Key Features & Benefits SImplify your data preparation workflow with these capabilities: 🔍 Automated Compatibility Validation: Instantly verify that attribute names meet GeoApps standards - no more guesswork or trial-and-error uploads 💡 Intelligent Error Diagnostics: Get clear, actionable error messages that tell you exactly what's wrong and why, eliminating confusio

FME Hub user pierrekoelich just uploaded a new transformer to the FME Hub. DGN Linear Dimension Drawer This custom transformer contains the framework to draw linear DGN dimensions when fed linear features(lines, polygons). This transformer will break the features into its constituent lines, and draw dimensions for each line. It has user parameters with presets to help make drawing the dimensions more visually appealing, these include: text alignment, text justification, arrow style, and offsetting the witness lines. Limitations: A major limitation of this custom transformer is that the user does not have control over where the dimension line gets drawn. It will be along the line that its measuring but which side the dimension line itself will be drawn on seems to be random. As the name suggests, this transformer cannot handle arc dimensions at all, a workflow to draw arc dimensions would be too different to incorporate into this one. Only 3 fonts are available, I recommend using the tr

FME Hub user cratcliff just uploaded a new transformer to the FME Hub. 🔄 Update or Publish Hosted Feature Layers from an APRX This script automates the process of updating or publishing web feature layers to ArcGIS Online (AGOL) or Enterprise Portal directly from an ArcGIS Pro project (.aprx). It supports flexible publishing options while preserving key metadata and ensuring that published content stays consistent with the source APRX. 🔧 Key Capabilities Connects to AGOL or Portal and loads a specific APRX and map by name. Supports two publishing modes: Single Service: Publishes all non-basemap layers as a combined web feature layer. Individual Layers: PublishGroupLayer: Publishes each top-level group layer as a unit. PublishSubLayers: Publishes each sublayer independently. Reuses metadata from existing hosted feature layers, including: Title, description, tags, thumbnail, credits, license info, and sharing settings. Retains feature service properties like editor tracking and capabil

FME Hub user dmitribagh just uploaded a new transformer to the FME Hub. The GOQRCodeReader transformer reads and decodes QR codes from various sources including local files, raster geometry, and URLs. It uses the https://goQR.me API to process the image and extract encoded text. Parameters Read QR Code from Specifies the source of the QR code image. File – Reads from a local image file (e.g., PNG, JPG, GIF). Raster Geometry – Uses the raster geometry on the incoming feature. URL – Downloads the image from a provided web address. File Displayed only if File is selected. Opens a file browser to choose the image file containing the QR code. URL Displayed only if URL is selected. Enter the direct URL to a QR code image. 📎 The URL must point directly to an image file (not a webpage). For example: https://example.com/qr-code.png The decoded result is returned as an attribute _qr_code_text on the output feature. Would you like to know more? Click here to find out more details!

FME Hub user cratcliff just uploaded a new transformer to the FME Hub. Description Get a URL to a formated docx or pdf report file of your Survey123 record. - Modified version for Portal Details This transformer uses HTTPCallers to submit a report job to Survey123 and returns the report's URL after the job has completed. At the moment, only detail reports for a single Survey123 record are supported. You must create and upload a report template in Survey123 first. See ESRI's documentation for more information: https://doc.arcgis.com/en/survey123/browser/analyze-results/featurereporttemplates.htm This transformer can be used in a workspace within an FME Server automation that is triggered by a Survey123 webhook, allowing you to create a report as soon as a survey has been submitted. Would you like to know more? Click here to find out more details!

FME Hub user andreas_h just uploaded a new transformer to the FME Hub. AttributeTableFlightSimulator Custom Transformer Transform your attribute tables into an interactive HTML-based flight simulator game! This custom transformer takes your FME attribute table and converts it into a dynamic gaming experience where you pilot the table itself. Input: * An attribute table. Tip for Optimal Gameplay: * The flight simulation will run smoother and be easier to win with fewer attribute fields and rows in your input table. Use for example a Sampler and a AttributeKeeper to make your attribute table manageable. Output: * HTML content ready to be written out using an FME HTML writer, creating your playable attribute table flight simulator. Use With: * HTML Writer Gameplay: How to Soar! Objective: Fly your attribute table through a series of glowing hoops to accumulate points. Key Rules: Ranking Up: Gather points by successfully navigating through hoops. Achieving higher scores will allow you to a

FME Hub user andreas_h just uploaded a new transformer to the FME Hub. AttributeTableFlightSimulator Custom Transformer Transform your attribute tables into an interactive HTML-based flight simulator game! This custom transformer takes your FME attribute table and converts it into a dynamic gaming experience where you pilot the table itself. Input: * An attribute table. Tip for Optimal Gameplay: * The flight simulation will run smoother and be easier to win with fewer attribute fields and rows in your input table. Use for example a Sampler and a AttributeKeeper to make your attribute table manageable. Output: * HTML content ready to be written out using an FME HTML writer, creating your playable attribute table flight simulator. Use With: * HTML Writer Gameplay: How to Soar! Objective: Fly your attribute table through a series of glowing hoops to accumulate points. Key Rules: Ranking Up: Gather points by successfully navigating through hoops. Achieving higher scores will allow you to a

GIS (StackExchange) user roundball2 just made a new post with the tags: fme-form. Would you like to know more? Click here to find out more details! StackExchange content licensed as: CC BY-SA 4.0

FME Hub user alexbiz just uploaded a new transformer to the FME Hub. MistralAIConnector The MistralAIConnector transformer allows FME users to interact with Mistral AI's chat completion service directly from within FME Workbench. Mistral AI is an AI research and deployment company focused on delivering cutting-edge open-weight models through simple APIs. This transformer wraps Mistral's API and exposes key parameters to help automate interactions with large language models. 🛠️ An API Key is required You can sign up here and access your API keys here. Parameters User Parameters API Key : The API key for authenticating requests to the Mistral API. Chat Completion System Prompt (optional) : An optional system-level instruction that sets the behavior or role of the assistant. User Prompt (required) : The user query or message to send to the AI model. Model : The Mistral model to use. Default is mistral-large-latest. You may input another supported model name manually. Advanced Settings Th

FME Hub user cratcliff just uploaded a new transformer to the FME Hub. Description Get a URL to a formated docx or pdf report file of your Survey123 record. - Modified version for Portal Details This transformer uses HTTPCallers to submit a report job to Survey123 and returns the report's URL after the job has completed. At the moment, only detail reports for a single Survey123 record are supported. You must create and upload a report template in Survey123 first. See ESRI's documentation for more information: https://doc.arcgis.com/en/survey123/browser/analyze-results/featurereporttemplates.htm This transformer can be used in a workspace within an FME Server automation that is triggered by a Survey123 webhook, allowing you to create a report as soon as a survey has been submitted. Would you like to know more? Click here to find out more details!

FME Hub user mark2atsafe just uploaded a new transformer to the FME Hub. This transformer sanitizes string values intended to be inserted into databases. It is a useful way to clean data and to guard against malicious code attacks such as SQL injection. Parameters String to Sanitize: This parameter defines the string to be sanitized. It can be either entered into the dialog, or derived from an attribute value. Output Attribute: This parameter defines the attribute to hold the output (i.e. the sanitized string). It can be either a new attribute or an existing one, even the same as the incoming attribute. Select Language: This parameter controls the query language to use. It can encode a string in either SQL or Cypher. Example: Data Cleaning Using the SQLExecutor, a workspace author wishes to issue the command: select x from y where z = 'Mark's Data' This will fail because of the apostrophe in the value being queried. The StringSanitizer can be used on Mark's Data in order to produce a S

FME Hub user abizien just uploaded a new fme_project to the FME Hub. Allow for PostreSQL table monitoring and automation around that Would you like to know more? Click here to find out more details!

FME Hub user abizien just uploaded a new transformer to the FME Hub. The DataVirtualizationJSONPaginate custom transformer helps create JSON-formatted responses suitable for use with FME’s Data Virtualization functionality. It allows users to paginate FME features and generate HTTP-like responses containing metadata and content suitable for integration with FME Flow’s virtual API endpoints. The transformer supports two pagination strategies: Page-based Pagination and Offset-based Pagination. Input Ports Input: Accepts a stream of features to be paginated and converted into a JSON response. Output Ports Output: Returns a single feature with HTTP response-like attributes and JSON content formatted for Data Virtualization. Parameters Attributes to Write A list of attribute names to include in the data array of the JSON response. Pagination Type Specifies the pagination strategy: - Page-based Pagination - Offset-based Pagination If Page-based Pagination is selected: Current Page: The curre

FME Hub user abizien just uploaded a new transformer to the FME Hub. The DataVirtualizationGeoJSON is a custom FME transformer designed to generate valid GeoJSON responses for FME's Data Virtualization feature. It transforms incoming spatial features into a GeoJSON FeatureCollection, embedding geometry and selected attributes as properties, and sets the appropriate HTTP response attributes. Parameters Feature Collection Name Type: Text Description: Sets the value for the name field in the GeoJSON FeatureCollection. Attributes to Include Type: Attribute Selector Description: Selects the attributes from incoming features to include under the properties object of each GeoJSON feature. Output Attributes The transformer sets the following attributes on the output features: response.status_code: Set to 200, indicating a successful HTTP response. response.body.content: Contains the GeoJSON-formatted string representing the feature collection. response.body.content_type: Set to application/geo

FME Hub user abizien just uploaded a new transformer to the FME Hub. The DataVirtualizationJSONList is a custom FME transformer that assists users in constructing HTTP JSON responses tailored for FME's Data Virtualization feature. It transforms incoming FME features into a structured JSON array, embedding selected attributes, and sets the necessary HTTP response attributes. Parameters List Name Type: Text Description: Specifies the key name under which the array of JSON objects will be nested in the response body. Attributes to Write Type: Attribute Selector Description: Selects the attributes from incoming features to include in each JSON object within the array. Output Attributes The transformer sets the following attributes on the output features: response.status_code: Set to 200, indicating a successful HTTP response. response.body.content: Contains the JSON-formatted string representing the array of feature attributes. response.body.content_type: Set to application/json, specifyin

FME Hub user abizien just uploaded a new transformer to the FME Hub. TimeSeriesGenerator The TimeSeriesGenerator is a custom FME transformer designed to generate a sequence of timestamped features between a specified start and end date, at user-defined intervals. It outputs each timestamp in three formats: FME Date Format: Suitable for internal FME date operations. ISO 8601 Format: Human-readable format. Epoch Time: Unix timestamp in seconds, ideal for sorting and time-based calculations. Parameters Start Date Type: Date Description: Defines the beginning of the time series. Accepts direct date input or attribute references. End Date Type: Date Description: Defines the end of the time series. Accepts direct date input or attribute references. Time Lapse (seconds) Type: Numeric Description: Specifies the interval between consecutive timestamps, in seconds. Obvious Cheat Sheet To assist in determining appropriate time lapse values: 1 min = 60 sec 5 min = 300 sec 10 min = 600 sec 30 min =

FME Hub user abizien just uploaded a new transformer to the FME Hub. Overview The DataVirtualizationResponseSetter custom transformer is designed to assist in the configuration of HTTP responses within the context of FME's Data Virtualization functionality. This transformer allows users to construct and populate the required HTTP response attributes by providing a simplified user interface for specifying standard response values. It is particularly useful when simulating or defining API response outputs for virtualized data services. Input Ports Input: Accepts any feature. Only attribute values are used by this transformer; geometry is ignored. Output Ports Output: Passes through the input feature, augmented with the specified http_response attributes. Generated Attributes This transformer adds the following attributes to the feature under the http_response group: http_response.response.status_code: The HTTP response code (e.g., 200, 404). http_response.response.body.content: The body

Blogger Tiana Warner just posted a new article to the FME Blog. Title: 4 methods for tracking data changes in FME Summary: Learn how to track data changes in FME using four powerful methods, including timestamps, database triggers, and change data capture (CDC). Introduction: When managing data, understanding how and why it changes is critical. By detecting changes early and accurately, you can streamline workflows, eliminate tedious manual checks, and focus on the records that matter. Automated change detection allows you to handle large datasets efficiently by processing only updated records, improve real-time responsiveness by reacting immediately to new changes, minimize data movement to reduce API calls and cloud storage costs, and align with enterprise-level data practices by tapping into existing change capture systems. Would you like to know more? Click here to read this new article!

FME Hub user daveatsafe just uploaded a new format to the FME Hub. FME can read data in the FalconView™ vector format. FalconView is a Windows mapping system that displays various types of maps and geographically referenced overlays. Many types of maps are supported, but the primary ones of interest to most users are aeronautical charts, satellite images, and elevation maps. FalconView also supports a large number of overlay types that can be displayed over any map background. The current overlay set is targeted toward military mission planning users and is oriented towards aviators and aviation support personnel. Overview The FalconView reader is a custom reader based on the Microsoft Access JDBC reader, and produces vector data such as lines, points and text, along with other feature types more specific to military data processing. Reader Overview FalconView drawing files contain a single table, Main, with three fields specifying the feature number, type, and data. Drawing files may

GIS (StackExchange) user SAM just made a new post with the tags: fme-form, splitting. Would you like to know more? Click here to find out more details! StackExchange content licensed as: CC BY-SA 4.0

Blogger Tiana Warner just posted a new article to the FME Blog. Title: 4 Methods for Tracking Data Changes in FME Summary: Learn how to track data changes in FME using four powerful methods, including timestamps, database triggers, and change data capture (CDC). Introduction: When managing data, understanding how and why it changes is critical. By detecting changes early and accurately, you can streamline workflows, eliminate tedious manual checks, and focus on the records that matter. Automated change detection allows you to handle large datasets efficiently by processing only updated records, improve real-time responsiveness by reacting immediately to new changes, minimize data movement to reduce API calls and cloud storage costs, and align with enterprise-level data practices by tapping into existing change capture systems. Would you like to know more? Click here to read this new article!

FME Hub user jasonfevang just uploaded a new fme_package to the FME Hub. Write Adobe PDF documents and reports. Would you like to know more? Click here to find out more details!

Blogger Tiana Warner just posted a new article to the FME Blog. Title: Automating Transportation Data: Real-World Solutions Using FME Summary: Discover how real transportation agencies use FME to automate data workflows, improve accuracy, and streamline infrastructure management. Introduction: In the transportation sector, decisions are only as good as the data behind them. Whether you’re managing transit schedules, monitoring infrastructure, or optimizing road safety, having accurate, real-time data is critical. Would you like to know more? Click here to read this new article!