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FME Hub user daveatsafe just uploaded a new transformer to the FME Hub.This transformer reads health insurance transaction records stored in EDI 835 documents, using the edi-835-parser Python module. It outputs the following feature types:Interchange - document sender, receiver and dateFinancialInformation - amount, payment methodOrganizations - payer and payee infoClaims - records of each claim, including both patient and insurance subrecordsServices - services provided for each claim, with subrecords for adjustments as a list. The edi835_parent_id attribute contains the value of the parent claim's edi385_id, allowing the user to link the two if desiredThe transformer will also output schema records through the <Schema> port, for use with Dynamic writers.Would you like to know more?

FME Hub user virtualcitymatt just uploaded a new transformer to the FME Hub.Creates a single temp folder using the TempPathnameCreator. Group By has been added so you can create multiple paths per group.That is all. Vote on this idea to have better support for creating temp files in FMEWould you like to know more? Click here to find out more details!

FME Hub user takashi.pss just uploaded a new template to the FME Hub.国土交通省が次のサイトで公開している都市計画決定GISデータ（CityGML形式）を OGC GeoPackage データセット (市町村別ファイル、フィーチャータイプ別テーブル) および GeoParquet データセット (市町村別フォルダー、フィーチャータイプ別ファイル) に変換するワークスペース例です。 都市計画決定GISデータ 全国データダウンロードページhttps://www.mlit.go.jp/toshi/tosiko/toshi_tosiko_tk_000087.html変換結果テーブル名、属性名 (列名) について都市計画決定GISデータ (CityGML形式) に記述されているフィーチャータイプ名や主題属性名はキャメルケース (例: UrbanPlanningArea, validFrom) ですが、変換結果の GeoPackage テーブル名、GeoParquet ファイル名や主題属性名はスネークケース (例: urban_planning_area, valid_from) となります。コードリストの参照についてgml:CodeType 型の主題属性のうち、codeSpace 属性によって参照すべきコードリストの URL が指定されているもの (例: function, city) については、その URL に基づいてウェブ上で公開されているコードリストを自動的に取得・参照し、コードに対応する意味文字列 (description) を取得して元の主題属性の値を置き換えるとともに、元の属性名にサフィクス "_code" をつけた名前 (例: function_code, city_code) の属性を追加して元の値 (コード) を格納します。 注: ウェブ上のコードリストを取得できるよう、

FME Hub user trd2021 just uploaded a new transformer to the FME Hub.Een FME-transformer om te gebruiken i.c.m. KLIC Genius.Voor vragen email ons: info@klicgenius.nlWould you like to know more? Click here to find out more details!

FME Hub user antoine just uploaded a new transformer to the FME Hub.PurposeTakes a pointcloud input, applies a PDAL pipeline and output the modified pointcloud.PDALUsageInput Ports :Input : This transformer accepts pointclouds.Output Ports :Output : Pointcloud transformed.RequirementsFME 2014.0 pdal and python-pdal in a conda envconda env specified in FME parameters.Published Parameterspipeline : PDAL pipeline (read the help to see example)FME_PROCESS_GROUP_BY : group bycomponents : Custom pointcloud dimensions you might have in your inputgenerateMetadata : Allows to print the status of your pointcloud along the the pdal

FME Hub user mark2atsafe just uploaded a new transformer to the FME Hub.DescriptionThis transformer controls the flow of features according to which input ports receive data. Various logic tests (AND, OR, etc.) can be applied to determine which combination of ports is a pass or fail.The main purpose is to direct data according to the output of previous transformers. For example, a workspace should continue processing if - and only if - the previous two transformers both return data. If one of them fails, the workspace should terminate.ParametersPorts to UseWhich input ports should form part of the logic tests. The transformer can use any number of ports, from 1 to 4.Logic to UseWhich logic test to apply to the input ports. There are various tests, such as AND, OR, and XOR.Functionality

FME Hub user haider just uploaded a new transformer to the FME Hub.TransactionHistoryFetcherThis is a transformer which is mostly used on transaction history data to find out what changed over time for each item.Would you like to know more? Click here to find out more details!

FME Hub user vhruska just uploaded a new transformer to the FME Hub.Extracting JSON values from API responses has always been a time-consuming task for me during workspace development. My previous workflow involved receiving an API response from HTTP Caller, pasting it into VS Code, saving it as JSON, opening a new FME Form Window, adding a JSON Reader, and then changing Schema Scan Mode to JSON Query before selecting a query.To streamline this process, I created a transformer specifically for parsing JSON strings. This transformer dynamically sets feature attributes based on JSON paths and their corresponding values from a specified attribute of an incoming feature.The transformer is particularly useful for handling deeply nested JSON structures, making data manipulation within FME workflows more effective and efficient.Would you like to know more?

FME Hub user chrisatsafe just uploaded a new web_connection to the FME Hub.OAuth Web Service for the Docusign REST API (Docusign also produces an OpenAPI Specification that can easily be imported into the HTTPCaller Transformer). Please note: For the developer environment, the URI ishttps://account-d.docusign.com/oauth/tokenFor the production environment, the URI ishttps://account.docusign.com/oauth/tokenFor more details, please refer to step 2. Obtain the access token documentation. Would you like to know more? Click here to find out more details!

FME Hub user gimmy15+ just uploaded a new transformer to the FME Hub.Telegram Message sender:this transformer sends messages (attribute text or images) to chats.Previously you need to create a Telegram Bot and get the Token.Developed by Genegis GI s.r.l.Would you like to know more? Click here to find out more details!

FME Hub user kevs-2021 just uploaded a new transformer to the FME Hub.Colors surface, 3D and faces from a RGB or RGBA value.It is an improved version of the SurfaceColorSetter.Would you like to know more? Click here to find out more details!

FME Hub user oliver.morris just uploaded a new transformer to the FME Hub.OverviewThis transformer works with the Google AI and its Gemini multi-modal models the support image analysis. This enables FME to pass images to the Gemini models and respond with text.An API Key is required via https://aistudio.google.com/app/apikey, currently Google is not charging for API calls to the two models!More information about the model, including limitations: https://ai.google.dev/gemini-api/docsCurrently this transformer supports JPG, JPEG and PNG file formats of up to 5MB in size but of any dimensions.This is a ‘no cost’ Publisher Tensing License: It has no license restrictions.If you have any questions regarding this transformer please email uk@avineon-tensing.comTensing is a partner of Safe Software and a Value Added Reseller, with over 80 FME Certified Professiona

FME Hub user geospatialize just uploaded a new transformer to the FME Hub.OverviewCustom transformer designed to address a common issue when working with resolved domain columns in FME. When a reader is set to resolve domains, but the coded value is not found in the corresponding domain, the "_resolved" field is populated as null. This can lead to inconsistencies and require manual intervention to handle the null values. The ResolvedDomainPopulator automatically populates these null values in the "_resolved" columns with the corresponding values from the original columns. It ensures data consistency and eliminates the need for additional transformers or manual effort to handle the null values. However, it is important to note that this transformer assumes that all resolvable domains have been properly resolved before its application. It does not perform the actual resolution process itself. To maintain data in

FME Hub user keziaatsafe just uploaded a new transformer to the FME Hub.DetailsThe transformer is designed to require only the essential parameters to update a Task to a Case in Cityworks with an option to include additional parameters. An HTTPCaller is used to make the call to the Cityworks API, followed by a JSONExtractor to extract valuable information from the response. Further configuration of the JSONExtractor can allow you to pull out more attributes from the response based on your custom needs. Similarly, additional parameters can be provided in the Additional Request Parameters field to send a more detailed request to Cityworks. The User Parameter for_ca_task_id may need configuration to reflect the details of your Cityworks instance.Would you like to know more? Clic

FME Hub user keziaatsafe just uploaded a new transformer to the FME Hub.DescriptionThis transformer leverages the Cityworks REST API to create a Case within Cityworks from FME. It is designed to be used with an authenticated web connection to Cityworks.DetailsThe transformer is designed to require only the essential parameters to create a Case in Cityworks with an option to include additional parameters. An HTTPCaller is used to make the call to the Cityworks API, followed by a JSONExtractor to extract valuable information from the response. Further configuration of the JSONExtractor can allow you to pull out more attributes from the response based on your custom needs. Similarly, additional parameters can be provided in the Additional Request Parameters field to send a more detailed request to Cityworks. The User Parameter for_case_type may need configuration to reflect the details of your Cityw

FME Hub user keziaatsafe just uploaded a new transformer to the FME Hub.DescriptionThis transformer leverages the Cityworks REST API to add a Task to a Case within Cityworks from FME. It is designed to be used with an authenticated web connection to Cityworks.DetailsThe transformer is designed to require only the essential parameters to add a Task to a Case in Cityworks with an option to include additional parameters. An HTTPCaller is used to make the call to the Cityworks API, followed by a JSONExtractor to extract valuable information from the response. Further configuration of the JSONExtractor can allow you to pull out more attributes from the response based on your custom needs. Similarly, additional parameters can be provided in the Additional Request Parameters field to send a more detailed request to Cityworks. The User Parameter for_task_id may need configuration to reflect the details o

FME Hub user nils95 just uploaded a new transformer to the FME Hub.Calculates the angle in degrees for every polygon node.INPUT:PolygonsNeeded attribute: "OBJECTID"OUTPUT:Points with calculated angle between lines Attribute: "OBJECTID_pt" (OBJECTID of the associated polygon as attribute)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.Google Gemini Service ConnectorOverviewThe Google Gemini Service Connector is a Custom Transformer for FME that facilitates interaction with Google's Vertex AI Gemini Model via REST API. This transformer allows users to leverage the advanced capabilities of Gemini, Google's large language model, to generate text-based outputs by providing specific prompts and configuring various parameters. This enables a broad range of applications, from content generation to data enrichment across different industries.For more information, please see the Gemini API documentation.Note: by default, this transformer is configured to use the Auto Updated Gemini model.Would you like to know more?

FME Hub user chrisatsafe just uploaded a new web_connection to the FME Hub.Web Service Setup InstructionsCreate an Auth client ID. See Creating OAuth 2.0 to Access Google Protocols for more information. Fill in your client id and client secret into the Google Cloud Al Auth webservice. See the Managing Web Services documentation for more details on how to manage the webservice Would you like to know more? Click here to find out more details!

FME Hub user chriswilson just uploaded a new transformer to the FME Hub.Python caller that takes in 'attr_name' and 'attr_value' attributes, searches for attr_name in the incoming feature's attribute list and will update the values of any matched attributes.Relies on firstly features being counted - hence also taking in a _count attribute that will be used to group features - and then all of their attribute names having been exposed as 'attr_name' and values as 'attr_value' in an AttributeExploder previously, then some other work having occurred to for example join or modify those attributes (e.g. mapping attribute values to domain codes) and also some tidying of that work so that duplicate records or null values are removed from 'attr_name' and 'attr_value', so that the result is you have at least some attributes from your original features that need to be updated but you don't know which ones that will be going into the process run. H

FME Hub user konnorporter just uploaded a new transformer to the FME Hub.Takes a set of points with a start/end point and creates a minimum spanning length network/tree.The parameter Start/End Node determines which node(s) to use as a seed for the algorithm.0 or any false-ish value means not a starting node, while 1 (or any positive result) results in that feature being used as a starting node.Placing a 0 in that parameter, or giving a parameter that is false-ish, will result in the first node being used as the seed.Choosing multiple starting points will result in a forest of Minimum Spanning Trees, i.e. several disconnected networks. This is useful for if you want to add more nodes to a pre-existing network, by setting all the nodes in that network to 1, and the nodes yet to be added to 0.Would you like to know more?

FME Hub user haider just uploaded a new transformer to the FME Hub.Transposes attributes so that the values in any selected Column Attribute are transposed into their own individual columns. The corresponding selected Row Attribute(s) will also be transposed in accordance with the selected column and its attributes. Aggregation works by grouping the results into desired Group-By column categories. This transformer also allows you to add a suffix to the end of the newly transposed column names in order to maintain clarity and produce distinction between previously defined data columns.(Example):The table below shows the inputs offered by the transformer:The data structure below shows the data before it is transposed. The next image shows the state of data after it has gone through the transformer using the inputs specified in Image 1. This displays the tranposing + aggr

FME Hub user haider just uploaded a new transformer to the FME Hub.Transposes attributes so that the values in any selected Column Attribute are transposed into their own individual columns. The corresponding selected Row Attribute(s) will also be transposed in accordance with the selected column and its attributes. Aggregation works by grouping the results into desired Group-By categories. This transformer also allows you to add a suffix to the end of the newly transposed column names in order to maintain clarity and distinction between previously defined data. ### Examples The table below shows the original input features:- Column Attribute -> Allows you to choose one column to tranpose their values into individual columns. (REQUIRED)- Row Attribute(s) -> Allows you to choose multiple columns so that their values can be transposed under the new co

FME Hub user dmitribagh just uploaded a new transformer to the FME Hub.takes the extents and a simple text input in a form of comma- or semicolon-separated list of objects which a user would like to extract from OpenStreetMap database.This is a highly experimental transformer and should rather serve for inspiration and experimentation than real work - the current results generated by OpenAI API do not always return the expected or satisfactory results.As an experimental transformer, it wasn't passed through a thorough QC process, it does not handle all possible errors or exceptions. Feel free to look inside and edit the transformer as much as your imagination allows and adjust it for your needs.How does it work?The transformer populates a pre-created prompt with parameters such as extents of the are of interest, and the keywords defining the objects that will be read from the OSM database. The pr

FME Hub user abizien just uploaded a new transformer to the FME Hub.Use ip-api.com API to geolocate IP addresses.The API accept 45 requests per minute from an IP address. Entities are decelerated by this transformer.Would you like to know more? Click here to find out more details!