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This sample demonstrates a data cleaning pipeline with Azure Functions written in Python triggered off a HTTP event from Event Grid to perform some pandas cleaning and reconciliation of CSV files.
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Using this sample we demonstrate a real use case where this is used to perform cleaning tasks.
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# Getting Started
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## Getting Started
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## Deploy to Azure
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### Deploy to Azure
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### Prerequisites
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#### Prerequisites
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- Install Python 3.6+
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- Install [Functions Core Tools](https://docs.microsoft.com/en-us/azure/azure-functions/functions-run-local#v2)
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- Install Docker
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- Note: If run on Windows, use Ubuntu WSL to run deploy script
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### Steps
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#### Steps
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- Deploy through Azure CLI
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- Open AZ CLI and run `az group create -l [region] -n [resourceGroupName]` to create a resource group in your Azure subscription (i.e. [region] could be westus2, eastus, etc.)
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- [Create/Activate virtual environment](https://docs.microsoft.com/en-us/azure/azure-functions/functions-create-first-function-python#create-and-activate-a-virtual-environment)
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- Run `func azure functionapp publish [functionAppName] --build-native-deps`
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## Test
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### Test
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- Upload s1.csv file into c1raw container
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- Watch event grid trigger the CleanTrigger1 function and produce a "cleaned_s1_raw.csv"
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- Watch it produce final.csv file
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- Can use a logic app to call the reconcile method with batch id's
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# References
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## References
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- [Create your first Python Function](https://docs.microsoft.com/en-us/azure/azure-functions/functions-create-first-function-python)

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