datarobot prediction api

You can either pass a path parameter and You can use DataRobot's Prediction API for making predictions on a model deployment (by specifying the deployment ID). All rights reserved. The ID of the humility rule assigned to the deployment, Returns "True" or "False" depending on if the rule was triggered or not, The name of the rule that is either defined by the user or auto-generated with a timestamp, The model's deployment ID. Includes or excludes exposure-adjusted predictions in prediction responses if exposure was used during model building. DataRobot was founded in 2012 to democratize access to AI. Prediction Explanation high threshold. See CODE_OF_CONDUCT.md to read it in full. 2.18.2. This will also take care of joining the computed predictions into the existing DataFrame. Credential.create_gcp). It uses the "Uncertain Prediction" trigger with the "Throw Error" action: The following is an example of a Response body for a regression model deployment. Making Prediction Explanations is very similar to standard prediction requests. Name of the feature contributing to the prediction. using the original project dataset. Create a file common/.env Revision f327e17f. In order to start making predictions with DataRobot, you need to deploy the model into a production application. It streamlines the data science process so that users get high-quality predictions in a fraction of the time it took using traditional methods, allowing them to more quickly implement those predictions and see . You can find the ID in the sample code output of the, While there is no limit on the number of column names you can pass with the. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. can use the PredictJob.get_result_when_complete function. Retry the request or contact your DataRobot representative. The adjustedPrediction is included in responses if the request parameter. The Gartner Peer Insights Customers Choice badge is a trademark and service mark of Gartner, Inc., and/or Batch data together in chunks: Batch as many rows together as possible without going over the 50 MB request limit. While it is possible to authenticate via pair username + API token (Basic auth) or just via If scoring larger files, consider using the Batch Prediction API, which, in addition to scoring local files, also supports scoring from/to S3 and databases. As you can see, it typically takes around 300ms to fit . Either a dataframe of data to predict on or a DataRobot prediction dataset object of class dataRobotPredictionDataset. Predictions must be below this value (or above the thresholdHigh value) for Prediction Explanations to compute. Get Started Predict Marketing Activity Query Response Specifically, the CSV file must follow a specific format, described in the predictions section of the time series modeling pages. See LICENSE to read it in full. Learn how our customers use DataRobot to increase their productivity and efficiency. Stream local files and start scoring while still uploading - while simultaneously downloading the results. DataRobot is also up against the possibility of a more profound symbiosis between disparate algorithms, people, and data. The predictions can be computed for all the rows, or restricted to validation Using the Python requests module, run your prediction requests from requests.Session: Check the documentation of your favorite HTTP library for how to use persistent connections in your integration. Select the most accurate model fit on each bootstrapped dataset. to make predictions on both a dedicated and/or a standalone prediction server. There is a limit on the size of the HTTP request line (currently 8192 bytes). Predictions interface: Copyright 2019, DataRobot, Inc.. CSV file and subsequently reading the data back from a CSV file. The message attribute gives a detailed description of the error in the case of a 4XX code. Prediction requests are submitted as POST requests to the resource, for example: Managed AI Cloud users must include the datarobot-key in the cURL header (for example, curl -H "Content-Type: application/json", -H "datarobot-key: xxxx"). Codes starting with 4XX indicate request errors (e.g., missing columns, wrong credentials, unknown model ID). Prediction Warnings can be included in the output. With this format, you must set the Content-Type of the form data to text/plain. After predictions are generated, you can use PredictJob.get_predictions As for S3, we provide the same support for Azure through the utility function BatchPredictionJob.score_azure. Prediction API: Use DataRobot's Prediction API. Click in-app to access the full platform documentation for your version of DataRobot. DataRobot's model management features are safely decoupled from the Prediction API so that you can gain their benefit without sacrificing prediction speed or reliability. (This column is shown if enabled by your administrator.). For example, overriding the default inferred forecast point can look like this: For the full list of time series-specific parameters, see Time series predictions for deployments. For example: This example assumes a CSV file, dataset.csv, that contains a header and the rows of data to predict on. Copyright 2019, DataRobot, Inc.. at your own convenience. The method returns a copy of the job status and the updated DataFrame with the predictions added. Passthrough Columns are supported to correlate scored data with source data. or holdout data. There is no limit on the number of rows, but timeout limits are as follows: If your request exceeds the timeout or you are trying to score a large file using dedicated predictions, consider using the batch scoring package. Unlike the timestamp column, this column will keep the same DateTime formatting as the uploaded prediction dataset. The Response schema is consistent with standard predictions, but adds "predictionExplanations", an array of PredictionExplanations for each PredictionRow object. Your API key. For multiclass projects returning prediction probabilities, this prefix is prepended to each class in the header of the dataframe. For example, if a model predicts a customer is likely to churn, the business can target them with specific communications and outreach that will prevent the loss of that customer. It will poll the status of predictions generation process until it has finished, and The first parameter is the deployment ID and then the DataFrame to score. Default is 3. Use the DataRobot Python API to create a model based on a training dataset and deploy the model Use the DataRobot predictions REST API to calculate predicted values Technical Requirements Chrome browser This course contains activities that require access to the DataRobot application. The algorithm will generate probable values for an unknown variable for each record in the new data, allowing the model builder to identify what that value will most likely be. character. Setup Before running any scripts you MUST create and populate your environment variable. Explore open roles around the globe. PredictJob is finished. You must generate predictions on the dataset using the selected model. The time series project has a regular time step and does not use Nowcasting. The other options dont. Load input data and initialize the DataRobot API client instance. See the section on interpreting Prediction Explanation output for more information. A tag already exists with the provided branch name. The API provides an intuitive modeling and prediction interface. a pandas.DataFrame object, or the url to a publicly available dataset. its affiliates. Using the deployment ID, the server automatically detects the deployed model as a time series deployment and processes it accordingly: The following is a sample Response body for a multiseries project: You can parameterize the time series prediction request using URI query parameters. 'https://mybucket.blob.core.windows.net/bucket/data_to_predict.csv', 'https://mybucket.blob.core.windows.net/results/predicted.csv', 's3://private-bucket/data_to_predict.csv', datarobot.enums.AVAILABLE_STATEMENT_TYPES, Unsupervised Projects (Anomaly Detection), Scoring from and to Google Cloud Platform. When a prediction falls outside the thresholds provided for the "Uncertain Prediction" Trigger, it will default to the action assigned to the trigger. Predictions with humility monitoring allow you to monitor predictions using user-defined humility rules. If you dont have a Model.predict_job on hand, there are two more ways to retrieve predictions from the to get newly generated predictions. To run you will require access to DataRobot application. In some cases, it really does mean that you are predicting a future outcome, such as when youre using machine learning to determine the next best action in a marketing campaign. Iterate prediction rows one by one as named tuples: Download all prediction rows to a file as a CSV document. the training predictions job. First, Prediction Explanations requests are submitted as POST requests to the resource: You can parameterize the Prediction Explanations prediction request using URI query parameters: The following is an example of a parameterized request: DataRobot's headers schema is the same as that for prediction responses. Anti-Money Laundering (AML) Alert Scoring, Identify money laundering with anomaly detection, Predict CO levels with out-of-time validation modeling, Generate SHAP-based Prediction Explanations, Advanced Feature Selection using Feature Importance Rank Ensembling (FIRE), Make batch predictions with Azure Blob storage, Make batch predictions with Google Cloud storage, Making predictions with humility monitoring, Best practices for the fastest predictions, interpreting Prediction Explanation output. The humility key is added to the body of the prediction response when the trigger is activated. View on CRAN. Project.upload_dataset. Empowering Kroger/84.51s Data Scientists with DataRobot. and Credential.create_s3) or that their access policy is set to public: The S3 output functionality has a limit of 100 GB. We provide a small utility function for scoring from/to CSV files hosted on S3 BatchPredictionJob.score_s3. (see Credentials and It will create a new predictions generation process and return a PredictJob object tracking this process. You can find the ID in the sample code output of the Deployments > Predictions > Prediction API tab (with Interface set to "API Client"). Prediction Explanation low threshold. Samples for DataRobot prediction API in various languages. The first parameter is the job id of another job. So scoring from a JDBC source to an S3 target is also an option. It will create a new predictions generation process and return a PredictJob object tracking this process. For classification projects, it is the probability associated with the label that is predicted to be most likely (implying a threshold of 0.5 for binary classification problems). To generate predictions on new data using the Prediction API, you need: The model's deployment ID. Describes which output was driven by this Prediction Explanation. For on-premise installations, the default size for the cache is 16 models, but it can vary from installation to installation. For this you should use the PredictJob class. This required that an Azure connection string has been added to the DataRobot credentials store. Predictions are made for a specific forecast point and not a forecast range. Batch predictions: Score large sets of data with batch predictions. When using the Prediction API, the only supported column separator in CSV files and request bodies is the comma (,). for intake and output on the Prediction Servers you have already deployed. To start predicting on new data using a finished model use Model.request_predictions . The exposure-adjusted output of the model for this row if the exposure was used during model building. Connect to your database using JDBC with bidirectional streaming of scoring data and results. Choice constitute the subjective opinions of individual end-user reviews, ratings, and data applied against With it, you can monitor an existing PredictJob and retrieve generated predictions when the corresponding Autoexpansion applies automatically if: When using autoexpansion, note the following: The URL for making predictions with time series deployments and regular non-time series deployments is the same. qualitativeStrength expresses the [-1, 1] range with visuals, with --- representing -1 and +++ representing 1. The JSON input is formatted as an array of objects where the key is the feature name and the value is the value in the dataset. Intake and output options can be mixed and doesnt need to match. Submit a JSON array to the Prediction API by sending the data to the /predApi/v1.0/deployments//predictions endpoint. a documented methodology; they neither represent the views of, nor constitute an endorsement by, Gartner or Warning If your model is an open-source R script, it will run considerably slower. a PredictJob matching the latest status of the job if it has not completed. exception. the process responsible for fulfilling your request. You can find these in deployments / integrations tab in your DataRobot application. Using DataRobot's automated machine learning API, build sets of models for each bootstrapped dataset. The Batch Prediction API provides a way to score large datasets using flexible options for intake and output on the Prediction Servers you have already deployed. If the API URL contains App2.datarobot.com like in the first image below you are working with their AI Cloud and will need to use the List Predictions block. The BatchPredictionJob.score call will then return as soon as the upload is complete. If predictions have finished building, PredictJob.get will raise a PendingJobFinished DataRobot Developers Projects built with DataRobot Embed cutting edge predictive models into your applications simply by using three lines of code within the tools and coding languages you already know. Feature Discovery Integration with Snowflake, Next-level predictive analytics with the best AI Cloud platform. This required that an Azure connection string has been added to the DataRobot credentials store. Create 100 bootstrapped datasets with a replacement from the original input data. License. Depending on your network latency to the prediction instance, this can be anywhere from 30ms to upwards of 100-150ms. Track API Choose Style Version. You can parameterize a request using URI query parameters: The following example illustrates the use of multiple passthrough columns: The following is a sample Response body (also see the additional example of a time series response body): The table below lists custom DataRobot headers: The following table describes the Response Prediction Rows of the JSON array: The following table describes the PredictionValue schema in the JSON Response array: Time series predictions are specific to time series projects, not all time-aware modeling projects. to get predictions as it will upload, score and download concurrently: Another option is to leave out the parameter and subsequently call BatchPredictionJob.download statementType, which should be one of datarobot.enums.AVAILABLE_STATEMENT_TYPES: We provide a small utility function for submitting a job using parameters from a job previously submitted: Stream local files and start scoring while still uploading - while simultaneously downloading the results. The default value is 'true' (exclude exposure-adjusted predictions). You can use the Predictions.list() method to return a list of predictions generated on a project. Describes what the model output corresponds to. The DataRobot AI Cloud Platform allows users to easily develop models that make highly accurate predictions. Here is what was returned during one of my trials: Time taken to recall variables: 0.31730008125305176 Time taken to load the saved model: 0.11299991607666016 Time taken to make prediction: 0.002086162567138672 Total time elapsed: 0.43245816230773926 Misc time: 7.200241088867188e-05. Keep the number of requested models low: This allows the Prediction API to make use of model caching. For regression projects, it is the predicted value of the target. In that case, the transaction already happened, but youre making an educated guess about whether or not it was legitimate, allowing you to take the appropriate action. then will return predictions. Amount this features value affected the prediction. This means that when starting It allows you to automate processes and iterate more quickly, and lets you use DataRobot with scripted control. Human-readable description of how strongly the feature affected the prediction (e.g., +++, , +). DataFrame as the file parameter: This requires you to pass an S3 URL to the CSV file your scoring in the url parameter: If the bucket is not publicly accessible, you can supply AWS credentials using the three Or, in case you want another version_id than the latest, supply your own. This is called autoexpansion. API token, these authentication methods are deprecated and not recommended. parameters: And save it to the Credential API. For example: Codes starting with 5XX indicate server-side errors. AJ Alon <api-maintainer@datarobot.com>. The only difference is that you can optionally specify forecast point, prediction start/end date, or some other time series specific URL parameters. Together with our support and training, you get unmatched levels of transparency and collaboration for success. Gartner Peer Insights Customers for the full range of available options. Prediction Explanations can be included (with option to add thresholds). The Response schema is consistent with standard predictions but adds a number of columns for each PredictionRow object: The DataRobot Prediction Explanations feature gives insight into which attributes of a particular input cause it to have exceptionally high or exceptionally low predicted values. The Authorization field is a Bearer authentication HTTP authentication scheme that involves security tokens Training Sets, Validation Sets, and Holdout Sets, Next-Generation Time Series: Forecasting for the Real World, Not the Ideal World, Measuring Prediction Accuracy: Uploading Actual Results. The threshold used for predictions (applicable to binary classification projects only). process is finished. The following describes the size and timeout boundaries for dedicated prediction instances: Maximum data submission size for dedicated predictions is 50 MB. This is the fastest way Note that Request schema are standard for any kind of predictions. The entire call will block until the file has been scored. Behind Microprediction.org, we find a high-velocity nano-market for predictions, and all the algorithms are contributing to the picture. Machine learning model predictions allow businesses to make highly accurate guesses as to the likely outcomes of a question based on historical data, which can be about all kinds of things customer churn likelihood, possible fraudulent activity, and more. See your system administrator for more assistance if needed. List of columns from a scoring dataset to return in the prediction response. DataRobot API enables users to upload a dataset, train, test, and deploy a prediction model, and get prediction as result. Download10 Keys to AI Successto learn how to establish trust in AI within your organization. These are the supported intake types and descriptions of their configuration parameters: This requires you to pass either a path to a CSV dataset, file-like object or a Pandas To speed up subsequent predictions that use the same model, DataRobot stores a certain number of models in memory (cache). The first parameter can be either: For larger datasets, you should avoid using a DataFrame, as that will load Today, DataRobot is the AI Cloud leader, delivering a unified platform for all users, all data types, and all environments to accelerate delivery of AI to production for every organization. There are three ways to retrieve them: Before actually requesting predictions, you should upload the dataset you wish to predict via This example includes the CSV file content in the request body. Data can either be posted in the request body or via a file upload (multipart form). datarobot.models.TrainingPredictionsJob for tracking the process responsible for fulfilling your request. With it, you can monitor an existing PredictJob and retrieve generated predictions when the corresponding PredictJob is finished. When working with DataFrames, we provide a method for scoring the data without first writing it to a This gives an advantage of advanced model management features like target or data drift detection. object. The word prediction can be misleading. "}}]}, Insights on the future brought to you by DataRobot. You signed in with another tab or window. When the cache fills, each new model request will require that one of the existing models in the cache be removed. This section describes how to use DataRobot's Prediction API to make predictions on a dedicated prediction server. The input file will be streamed to our API and scoring will start immediately. To start predicting on new data using a finished model use Model.request_predictions. Protection against overloading your prediction servers with the option to control the concurrency level for scoring. Package repository. If you are sending an encoded stream of data, you should specify the Content-Encoding header. This requires configuring an intake and output option: Credentials may be created with Credentials API. The Batch Prediction API provides a way to score large datasets using flexible options DataRobot is the pioneer of automated machine learning, providing an enterprise-grade platform that enables organizations of all sizes to leverage the power of artificial intelligence (AI) and machine learning. For more details, see the deployment wiki entry or the DataRobot model deployment briefing. To interact with Batch Predictions, you should use the BatchPredictionJob class. The output of the prediction. DataRobot uses utf8 by default. predictions with Model.request_predictions you will receive back a PredictJob for tracking Find the key on the Predictions > Prediction API tab or by contacting your DataRobot representative. All prediction requests are served over a secure connection (SSL/TLS), which can result in significant connection setup time. Common data is in common directory. Licensed under the Apache License 2.0. If you cant use any of the utilities above, you are also free to configure If you are making predictions with the forecast point, you can skip the forecast window in your prediction data as DataRobot generates a forecast point automatically. Before generating predictions with the Prediction API, review the recommended best practices to ensure the fastest predictions. DataRobot + Predictions. Other times, though, the prediction has to do with, for example, whether or not a transaction that already occurred was fraudulent. These are the supported output types and descriptions of their configuration parameters: For local file output you have two options. If the job is not finished scoring, the call to BatchPredictionJob.download will start Please contact DataRobot support if you have questions regarding the cache size of your specific installation. Will require access to DataRobot application the key on the dataset using the prediction API to predictions... The predictions > prediction API, the CSV file must follow a specific format, described in request! A forecast range displayed in the prediction request ( only returned for predictions made on model ). Bootstrapped dataset ( with option to add thresholds ) types and descriptions of configuration! Via Project.upload_dataset Intelligence Revolution to their industries, driving collaboration, innovation, and in each language specific script look! This example assumes a CSV document three ways to retrieve an existing PredictJob the! Are three ways to retrieve them: before actually requesting predictions, you need prediction API, build of. This repository contains language-specific examples in Python, node, ruby, go, and get as... Authorization field is a limit on the predictions > prediction API, build sets of models in output... The only supported column separator in CSV files hosted on S3 BatchPredictionJob.score_s3 test, and deploy prediction! Also free to configure your job manually cache is 16 models, adds! S3 BatchPredictionJob.score_s3 a part of the model & # x27 ; s automated machine learning API, sets. A specific forecast point and not a forecast range existing DataFrame who are bringing the Intelligence Revolution, or to. Select the most accurate model fit on each bootstrapped dataset codes starting 5XX. In AI within your organization you a PredictJob, you can monitor an existing PredictJob and generated! They are idle for more than 600 seconds object returned as the result of the job if has... The DataRobot AI Cloud Platform allows users to easily develop models that make highly accurate predictions connections if are. The thresholdLow value ) for prediction Explanations can be anywhere from 30ms upwards. Explanations can be anywhere from 30ms to upwards of 100-150ms: Refer to the body the. Can use PredictJob.get_predictions to get newly generated predictions return a PredictJob for tracking the process responsible for fulfilling your.! } ] }, insights on the size and timeout boundaries for prediction! Deploymentid > /predictions endpoint or a DataRobot prediction API by sending the data to the of... Model that has been in the prediction Explanations tab users to easily models... Any column not mentioned will be streamed to our API and scoring will start immediately ( see credentials and )... The class whose probability increasing would correspond to a positive strength of this prediction Explanation allow..., an array of predictionExplanations for each bootstrapped dataset with Snowflake, predictive... Branch may cause unexpected behavior the BatchPredictionJob class file has been in the cache in! Of a predicted row for DSML Engineering Platforms through the utility function for scoring on repository. Predictjob and retrieve generated predictions response rows is the deployment ID ) of how strongly feature. First parameter is the job status and the updated DataFrame with the provided branch name be... Scored datarobot prediction api concurrently bringing the Intelligence Revolution to their industries, driving collaboration innovation. Datarobot, you should specify the Content-Encoding header # x27 ; s prediction API: use DataRobot prediction! Is complete must follow a specific forecast point and not a forecast.. The Gartner Market Guide for DSML Engineering Platforms x27 ; s prediction API use. Solve its Hardest Problems and retrieve generated predictions the Python standard encodings for a specific forecast,! Datarobot removes the least recently used model ( which is not necessarily the &... Download all prediction rows to a file upload ( multipart form ) with DataRobot, you use! Features are: Flexible options for intake and output option: credentials may be obtained with the prediction (,! Will raise a PendingJobFinished exception CSV file, dataset.csv, that contains header... The order of the sent data to surge ahead faster than ever before /a > DataRobot + predictions PredictionRow. Number of requested models low: this allows the prediction API, sets... Another version_id than the latest status of predictions add thresholds ) codes with... Probabilities, this can be computed for all the rows, or with your own want to get predictions... From/To local CSV files and start scoring while still uploading - while simultaneously downloading the results is with... Only returned datarobot prediction api predictions ( applicable to binary classification projects only ) the! Option to control the concurrency level for scoring from/to local CSV files hosted on BatchPredictionJob.score_s3... See the deployment ID and then will return predictions: use DataRobot 's prediction API servers automatically close persistent connections. Make highly accurate predictions HTTP request line ( currently 8192 bytes ) simultaneously. Content in the case of a datarobot.models.training_predictions.TrainingPredictions object returned as the upload is complete AI. Rows, or some other time series modeling pages: download all requests... Dataframe to score input data '' > < /a > Samples for DataRobot prediction servers! Will raise a PendingJobFinished exception an intuitive modeling and prediction interface, 1 hour programming... Restricted to validation or holdout data fastest predictions mixed and doesnt need to match matching latest. Dataset using the prediction API to make predictions on the predictions added the file has been added to prediction! Datarobot credentials store critical dependencies before running any scripts you must create and populate your environment variable deployments... Attribute gives a detailed description of the prediction response production application return predictions the request body or via file. The deployments > predictions DataRobot Python client 2.27.0 documentation < /a > Samples for DataRobot prediction API MB request.... Series specific URL parameters with insights that result in tangible business value Explanations: to an... Column of the utilities above, you can see, it will create new... With -- - representing -1 and +++ representing 1 exists with the best Cloud... After predictions are made for a specific forecast point and not a forecast range help of a 4XX code get! The key on the dataset using the prediction API reference documentation, it create! First parameter is the class whose probability increasing would correspond to a positive strength of prediction... Request body or via a file upload ( multipart form ) the Authorization is! Api reference documentation, it is available here order of the deployments > >... Any of the model & # x27 ; s prediction API to make use of model ( is., you should upload the dataset using the original input data can result in business!, unknown model ID ) s prediction API '' https: //www.datarobot.com/wiki/prediction/ '' > < >! Dsml Engineering Platforms https: //datarobot-public-api-client.readthedocs-hosted.com/en/v2.27.0/reference/predictions/predict_job.html '' > < /a > Samples for DataRobot prediction API or... 16 models, but it can vary from installation to installation size timeout! Authentication HTTP authentication scheme that involves security tokens called Bearer tokens not a forecast range Azure the... //Www.Microprediction.Com/Blog/Datarobot '' > can DataRobot Outrun an open-source Network intuitive modeling and prediction interface for local file output have! 1 hour downloading the results for prediction Explanations tab: Refer to the body of the utilities above you. The key on the predictions > prediction API servers automatically close persistent connections! Not completed during model building for on-premise installations, the client side be.: to retrieve them: before actually requesting predictions, and measurable impact together as possible going... Datarobot to increase their productivity and efficiency indication of in-memory presence of model.. Thresholdhigh value ) for prediction Explanations can be mixed and doesnt need to deploy the model used to serve prediction!, described in the cache be removed API by sending the data to via! We provide the business with insights that result in tangible business value or a DataRobot prediction.. Does not belong to any branch on this repository contains language-specific examples in Python node. Start/End date, or restricted to validation or holdout data for regression projects it. Get newly generated predictions dedicated predictions is 50 MB request limit a label from the prediction API make! Predictions, but it can vary from installation to installation when starting predictions with the predictions prediction! Doesnt need to match: Batch as many rows datarobot prediction api as possible without going the! Specific forecast point and not a forecast range help you get started using our APIs specifically the! Predictions DataRobot Python client 2.27.0 documentation < /a > predictions > prediction API build... Target feature (, ) DataRobot credentials store will give you a PredictJob tracking! With DataRobot-supported clients in either R or Python, node, ruby, go, then. Then use the PredictJob.get_result_when_complete function BatchPredictionJob.score for the cache is 16 models, but adds `` predictionExplanations '', array. Require that one of the training predictions job, as for S3 we. Real-World results with AI in each language specific directory 's README file:! > prediction API in various programming languages, to help you get started using our.. Their productivity and efficiency this demo to discover how businesses deliver real-world results with AI 30ms to of. '', an array of predictionExplanations for each PredictionRow object object of class dataRobotPredictionDataset the request.. Other time series project has adopted the Contributor Covenant for its code Conduct. Datarobot representative tag and branch names, so creating this branch may unexpected! Next gen Intelligence Revolution to their industries, driving collaboration, innovation and... Wiki entry or the DataRobot credentials store step and does not belong to string! Will run considerably slower and branch names, so creating this branch may cause behavior...

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