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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

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

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

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!

FME Hub user takashi just uploaded a new template to the FME Hub. 国土地理院「ジオイド2024日本とその周辺」に基づいて、標高 (T.P.) から楕円体高への鉛直方向の座標変換を行う方法を示します。 このテンプレートに同梱されている "jpgeo2024+hrefconv2024.grd" は、国土地理院が次のウェブサイトで公開している「ジオイド2024日本とその周辺」 (isg 形式) を CsmapReprojector で利用可能な形式に変換して作成したものです。（2025年4月15日付け「測量法に基づく国土地理院長承認（使用）R 7JHs 29」）。基準面補正パラメーターは反映済みです。 基盤地図情報ダウンロードサービス > 「ジオイド2024日本とその周辺」と「基準面補正パラメータ」の提供 https://service.gsi.go.jp/kiban/app/geoid/ Would you like to know more? Click here to find out more details!

FME Hub user takashi just uploaded a new template to the FME Hub. 国土地理院「ジオイド2024日本とその周辺」に基づいて、標高 (T.P.) から楕円体高への鉛直方向の座標変換を行う方法を示します。 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: This custom transformer is designed to streamline the process of publishing or overwriting map image layers in Enterprise Portal directly from an ArcGIS Pro Project (APRX). The transformer works by referencing the specified APRX file, generating local service definition drafts (SD drafts) for the layers in the map, and then publishing map image layers in the portal. If publishing all layers in the map to one service, the users should specify a service name. Otherwise, the transformer uses the names of the layers in the contents pane of the map. If overwriting existing map image layers, to ensure a successful update, the layers in your ArcGIS Pro project must be named exactly the same as the hosted layers you intend to update. In summary, this process automates the creation of SD drafts and uses those to publish to your portal, applying schema changes and updating data, making sure your hosted layers sta

FME Hub user wghmapgear just uploaded a new transformer to the FME Hub. GeoApps Dataset Truncate With this transformer, you can easily truncate all features from an existing dataset in GeoApps. This connection is for example useful for automated updating of datasets where you first want to remove the old data. To complete a setup like this, take also a look at our other transformers. 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 GeoApps workspace name, dataset id and the web connection to GeoApps. You can find the dataset Id within your GeoApps workspace. Questions? Do you need any

FME Hub user cyclomedia just uploaded a new transformer to the FME Hub. Custom Azure BlobStorageConnector The standard FME Transformer Called AzureBlobStorageConnector doesn't support authentication via an Azure Application for connecting to your Blob Storage using a predefined web connection or web services. This custom transformer is a special version where your are able to connect to Azure BlobStorage using a web connection / web services. In the background, this transformer is working with the Azure Rest API. The webconnection needs to be referenced to a Azure Application in Azure Active Directory, where your permissions are managed. You can list, download, upload, copy, and remove your blobs, as well as create or remove containers, depending on the permissions granted to the Azure Application. Generating a web service in FME You'll need: - Tenant-ID - Client-ID - Client Secret This transformer is builded in: FME(R) 2024.2.1.0 (20241202 - Build 24801 - WIN64) By: Jan Smitsman Would

FME Hub user cyclomedia just uploaded a new transformer to the FME Hub. Custom Azure BlobStorageConnector The standard FME Transformer Called AzureBlobStorageConnector doesn't support authentication via an Azure Application for connecting to your Blob Storage using a predefined web connection or web services. This custom transformer is a special version where your are able to connect to Azure BlobStorage using a web connection / web services. In the background, this transformer is working with the Azure Rest API. The webconnection needs to be referenced to a Azure Application in Azure Active Directory, where your permissions are managed. You can list, download, upload, copy, and remove your blobs, as well as create or remove containers, depending on the permissions granted to the Azure Application. Generating a web service in FME You'll need: - Tenant-ID - Client-ID - Client Secret This transformer is builded in: FME(R) 2024.2.1.0 (20241202 - Build 24801 - WIN64) By: Jan Smitsman Would

FME Hub user martin_ekstrand just uploaded a new transformer to the FME Hub. Generates a customizable HTML report of failed jobs using the FME Flow REST API. This transformer retrieves all failed jobs from FME Flow and outputs an HTML report that can be emailed or embedded in a dashboard in FME Flow. The report's appearance can be customized by modifying the CSS. You can split the report based on job attributes—for example, generate separate reports for jobs triggered by Automations versus those started via Workspace Apps. Additionally, the raw feature output is available if you prefer to build your own custom reports or workflows. Would you like to know more? Click here to find out more details!

FME Hub user chrisatsafe just uploaded a new transformer to the FME Hub. OpenAIConnector Transformer Documentation The OpenAIConnector is a custom FME transformer that enables integration with OpenAI's /v1/responses endpoint. This transformer allows you to send prompts to OpenAI's large language models and receive responses directly within an FME workspace. This model accepts text, image (Vision), file search, and web search based inputs. Purpose This transformer supports AI-driven tasks such as content generation, classification, summarization, or transformation of structured/unstructured data, by leveraging OpenAI's text generation capabilities in a repeatable, automatable data workflow. The Example Use Case Imagine you have a dataset with a column of customer support inquiries, and you'd like to auto-generate a response or classify the sentiment. You can: Use AttributeCreator to build a dynamic prompt string. Pass that prompt to OpenAIConnector. Capture the model's response as a new

FME Hub user olavny just uploaded a new transformer to the FME Hub. Tests if GUID is valid Would you like to know more? Click here to find out more details!

FME Hub user davekazemi just uploaded a new transformer to the FME Hub. File Custom Metadata Manager Transformer Description This transformer allows you to manage custom metadata for files through three primary operations: Set - Add or update metadata (either all metadata or a specific key-value pair) Get - Retrieve metadata (either all metadata or a specific key) Remove - Delete all custom metadata from a file The transformer leverages Python to manipulate file streams with alternate data streams (ADS) in Windows file systems, storing metadata in a structured JSON format. Use Cases 1. Data Lineage Tracking Track data processing history by attaching metadata about transformations applied, processing dates, or source information to files without modifying their original content. 2. Workflow Configuration Management Store configuration parameters as metadata directly with the data files, allowing workflows to read these settings during execution rather than hard-coding them. 3. Complianc