[{"data":1,"prerenderedAt":78},["ShallowReactive",2],{"pattern-textract-lambda-sam-python":3},{"id":4,"title":5,"architectureURL":6,"cleanup":7,"contributors":10,"deploy":12,"description":15,"extension":16,"framework":17,"gitHub":18,"highlight":6,"introBox":24,"language":30,"level":31,"meta":32,"patternArch":33,"resources":62,"s3URL":6,"services":6,"stem":73,"testing":74,"videoId":6,"__hash__":77},"patterns\u002Fpatterns\u002Ftextract-lambda-sam-python.json","Automatic Text Detection with Amazon Textract",null,{"text":8},[9],"Delete the stack: sam delete",[11],"content\u002Fcontributors\u002Fjack-le-bon.json",{"text":13},[14],"sam deploy","An event-driven workflow to automatically detect and store text found within pdf files by leveraging Amazon Textract, AWS Lambda, and Amazon DynamoDB.","json","AWS SAM",{"template":19},{"repoURL":20,"templateURL":21,"projectFolder":22,"templateFile":23},"https:\u002F\u002Fgithub.com\u002Faws-samples\u002Fserverless-patterns\u002Ftree\u002Fmain\u002Ftextract-lambda-sam-python","https:\u002F\u002Fgithub.com\u002Faws-samples\u002Fserverless-patterns\u002Fmain\u002Ftextract-lambda-sam-python\u002Ftemplate.yaml","textract-lambda-sam-python","template.yaml",{"headline":25,"text":26},"How it works",[27,28,29],"This sample project demonstrates how to deliver an event-driven architecture to detect text within pdf files, while storing the results in Amazon DynamoDB.","Upon an object creation in the S3 bucket, a Lambda function is invoked, which initiates Amazon Textracts's DetectDocumentText function. Textract returns the results to the Lambda function which stores this information in the DynamoDB table.","This pattern deploys 1 S3 bucket, 1 Lambda Function, and 1 DynamoDB Table.","Python","200",{},{"icon1":34,"icon2":39,"icon3":43,"icon4":48,"line1":52,"line2":56,"line3":59},{"x":35,"y":36,"service":37,"label":38},10,50,"s3","Amazon S3",{"x":40,"y":36,"service":41,"label":42},40,"lambda","AWS Lambda",{"x":44,"y":45,"service":46,"label":47},80,25,"textract","Amazon Textract",{"x":44,"y":49,"service":50,"label":51},70,"dynamodb","Amazon DynamoDB",{"from":53,"to":54,"label":55},"icon1","icon2","Object Created",{"from":54,"to":57,"label":58},"icon3","Document",{"from":54,"to":60,"label":61},"icon4","Results",{"bullets":63},[64,67,69,71],{"text":65,"link":66},"Amazon Simple Storage Service (S3)","https:\u002F\u002Faws.amazon.com\u002Fs3\u002F",{"text":42,"link":68},"https:\u002F\u002Faws.amazon.com\u002Flambda\u002F",{"text":47,"link":70},"https:\u002F\u002Faws.amazon.com\u002Ftextract\u002F",{"text":51,"link":72},"https:\u002F\u002Faws.amazon.com\u002Fdynamodb\u002F","patterns\u002Ftextract-lambda-sam-python",{"text":75},[76],"See the GitHub repo for detailed testing instructions.","EzGx9EyEdIkMXT855R_ZjcYxCPhZUvt5LBI2EGkxY7g",1778846888625]