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# Examples of Batch Statistical Workflow

The requests below are written in Python. To execute them, you need to create an OAuth client as is explained [here](https://docs.planet.com/develop/authentication.md#sentinel-hub-authentication). It is named `oauth` in these examples.

## Create a Batch Statistical Request

This request defines which data is requested and how it will be processed. In this example, we will receive the statistics for a single band on a given day. To create a batch statistical request, replace the `input.features.s3.url` field with the actual path to the GeoPackage features, and the `output.s3.url` field with the desired path where the output data will be processed.

* Python SDK

```
evalscript = """

//VERSION=3

function setup() {

  return {

    input: [{

      bands: [

        "B04",

        "dataMask"

      ]

    }],

    output: [

      {

        id: "output_B04",

        bands: 1,

        sampleType: "FLOAT32"

      },

      {

        id: "dataMask",

        bands: 1

      }]

  }

}

function evaluatePixel(samples) {

    return {

        output_B04: [samples.B04],

        dataMask: [samples.dataMask]

        }

}

"""



request_payload = {

  "input": {

  "features":{

      "s3": {

          "url": "s3://{bucket}/{path-to-geopackage}",

          "accessKey": "{access-key},

          "secretAccessKey": "{secret-access-key}

      }

  },

    "data": [

      {

        "type": "sentinel-2-l2a",

        "dataFilter": {

            "mosaickingOrder": "leastCC"

        }

      }

    ]

  },

  "aggregation": {

    "timeRange": {

            "from": "2020-06-01T00:00:00Z",

            "to": "2020-07-31T00:00:00Z"

      },

    "aggregationInterval": {

        "of": "P30D"

    },

    "evalscript": evalscript,

    "resx": 10,

    "resy": 10

  },

  "output": {

      "s3": {

          "url": "s3://{bucket}/{key}",

          "accessKey": "{access-key},

          "secretAccessKey": "{secret-access-key}

      }

  }

}



headers = {

  'Content-Type': 'application/json',

   'Accept': 'application/json'

}



url = "https://services.sentinel-hub.com/statistics/batch/v1"



response = oauth.request("POST", url=url, headers=headers, json=request_payload)



request_id = response.json()['id']
```

Note that in the above example, we are specifying an `accessKey` and `secretAccessKey`, so we can read and write to the user's bucket. You can find more details about this under the [Object Storage Configuration section](https://docs.planet.com/develop/apis/batch-statistical.md#object-storage-configuration).

## Create a Batch Statistical Request with Google Storage

This example demonstrates how to use Google Cloud Storage for both GeoPackage input and delivery of results instead of S3.

* Python SDK

```
evalscript = """

//VERSION=3

function setup() {

  return {

    input: [{

      bands: [

        "B04",

        "dataMask"

      ]

    }],

    output: [

      {

        id: "output_B04",

        bands: 1,

        sampleType: "FLOAT32"

      },

      {

        id: "dataMask",

        bands: 1

      }]

  }

}

function evaluatePixel(samples) {

    return {

        output_B04: [samples.B04],

        dataMask: [samples.dataMask]

        }

}

"""



request_payload = {

  "input": {

  "features":{

      "gs": {

          "url": "gs://{bucket}/{path-to-geopackage}",

          "credentials": "{base64-encoded-credentials}"

      }

  },

    "data": [

      {

        "type": "sentinel-2-l2a",

        "dataFilter": {

            "mosaickingOrder": "leastCC"

        }

      }

    ]

  },

  "aggregation": {

    "timeRange": {

            "from": "2020-06-01T00:00:00Z",

            "to": "2020-07-31T00:00:00Z"

      },

    "aggregationInterval": {

        "of": "P30D"

    },

    "evalscript": evalscript,

    "resx": 10,

    "resy": 10

  },

  "output": {

      "gs": {

          "url": "gs://{bucket}/{key}",

          "credentials": "{base64-encoded-credentials}"

      }

  }

}



headers = {

  'Content-Type': 'application/json',

   'Accept': 'application/json'

}



url = "https://services.sentinel-hub.com/statistics/batch/v1"



response = oauth.request("POST", url=url, headers=headers, json=request_payload)



request_id = response.json()['id']
```

To prepare your Google Cloud Storage credentials, download your service account credentials in JSON format and encode them as base64:

* CURL

```
cat my_creds.json | base64
```

Replace `{base64-encoded-credentials}` with the output of this command in both the input and output sections of your request.

### Get Information About a Batch Statistical Request

* Python SDK

```
response = oauth.request("GET", f"https://services.sentinel-hub.com/statistics/batch/v1/{request_id}")



response.json()
```

### Get Status Information About a Batch Statistical Request

* Python SDK

```
response = oauth.request("GET", f"https://services.sentinel-hub.com/statistics/batch/v1/{request_id}/status")



response.json()
```

### Request Analysis of a Batch Statistical Request (ANALYSIS)

* Python SDK

```
response = oauth.request("POST", f"https://services.sentinel-hub.com/statistics/batch/v1/{request_id}/analyse")



response.status_code
```

### Request the Start of a Batch Statistical Request (START)

* Python SDK

```
response = oauth.request("POST", f"https://services.sentinel-hub.com/statistics/batch/v1/{request_id}/start")



response.status_code
```

### Stop a Batch Statistical Request (STOP)

* Python SDK

```
response = oauth.request("POST", f"https://services.sentinel-hub.com/statistics/batch/v1/{request_id}/stop")



response.status_code
```