> ## Documentation Index
> Fetch the complete documentation index at: https://arize-ax.mintlify.dev/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Migrate Exporter Client

> Migrate from ArizeExportClient to the unified ArizeClient. Export spans and ML model data with the v8 SDK.

The Exporter functionality has been restructured in v8. Instead of a dedicated `ArizeExportClient`, export methods are now integrated directly into the unified `ArizeClient` via resource-specific methods.

<CodeGroup>
  ```python Version 7 theme={null}
  from arize.exporter import ArizeExportClient

  client = ArizeExportClient(api_key="your-api-key")
  ```

  ```python Version 8 theme={null}
  from arize import ArizeClient

  # Export methods are integrated into the unified client
  client = ArizeClient(api_key="your-api-key")
  ```
</CodeGroup>

## Exporting Spans/Traces (LLM Data)

In v8, span export methods are available on `client.spans`.

### export\_model\_to\_df() for Spans

The `export_model_to_df()` method for tracing data migrates to `client.spans.export_to_df()`.

#### Parameter Reference

| Parameter                  | v7       | v8         | Changes                    |
| -------------------------- | -------- | ---------- | -------------------------- |
| `space_id`                 | Required | Required   | --                         |
| `model_id`                 | Required | Required   | Renamed to `project_name`  |
| `project_name`             | N/A      | ✅ Required | Renamed from `model_id`    |
| `environment`              | Required | ❌ Removed  | Always `TRACING` for spans |
| `start_time`               | Required | Required   | --                         |
| `end_time`                 | Required | Required   | --                         |
| `include_actuals`          | Optional | ❌ Removed  | Not applicable to spans    |
| `model_version`            | Optional | ❌ Removed  | Not applicable to spans    |
| `batch_id`                 | Optional | ❌ Removed  | Not applicable to spans    |
| `where`                    | Optional | Optional   | --                         |
| `similarity_search_params` | Optional | Optional   | --                         |
| `columns`                  | Optional | Optional   | --                         |
| `stream_chunk_size`        | Optional | Optional   | --                         |
| `parallelize_exports`      | Optional | ❌ Removed  | No longer supported        |

#### Side-by-Side Comparison

<CodeGroup>
  ```python Version 7 theme={null}
  from arize.exporter import ArizeExportClient
  from arize.utils.types import Environments
  from datetime import datetime

  # Client initialization
  client = ArizeExportClient(api_key="your-api-key")

  # Export spans/traces to DataFrame
  df = client.export_model_to_df(
      space_id="your-space-id",
      model_id="my-llm-project",
      environment=Environments.TRACING,
      start_time=datetime(2024, 1, 1),
      end_time=datetime(2024, 1, 31),
      where="span.name = 'generate'",
      columns=["span_id", "parent_span_id", "span.name"],
      stream_chunk_size=1000,
      parallelize_exports=True
  )
  ```

  ```python Version 8 theme={null}
  from arize import ArizeClient
  from datetime import datetime

  # Client initialization
  client = ArizeClient(api_key="your-api-key")

  # Export spans/traces to DataFrame
  df = client.spans.export_to_df(
      space_id="your-space-id",
      project_name="my-llm-project",  # Renamed from model_id
      start_time=datetime(2024, 1, 1),
      end_time=datetime(2024, 1, 31),
      where="span.name = 'generate'",
      columns=["span_id", "parent_span_id", "span.name"],
      stream_chunk_size=1000
      # environment removed (always TRACING)
      # include_actuals removed (not applicable)
      # model_version removed (not applicable)
      # batch_id removed (not applicable)
      # parallelize_exports removed
  )
  ```
</CodeGroup>

### export\_model\_to\_parquet() for Spans

The `export_model_to_parquet()` method for tracing data migrates to `client.spans.export_to_parquet()`.

#### Parameter Reference

| Parameter                  | v7       | v8         | Changes                    |
| -------------------------- | -------- | ---------- | -------------------------- |
| `path`                     | Required | Required   | --                         |
| `space_id`                 | Required | Required   | --                         |
| `model_id`                 | Required | Required   | Renamed to `project_name`  |
| `project_name`             | N/A      | ✅ Required | Renamed from `model_id`    |
| `environment`              | Required | ❌ Removed  | Always `TRACING` for spans |
| `start_time`               | Required | Required   | --                         |
| `end_time`                 | Required | Required   | --                         |
| `include_actuals`          | Optional | ❌ Removed  | Not applicable to spans    |
| `model_version`            | Optional | ❌ Removed  | Not applicable to spans    |
| `batch_id`                 | Optional | ❌ Removed  | Not applicable to spans    |
| `where`                    | Optional | Optional   | --                         |
| `similarity_search_params` | Optional | Optional   | --                         |
| `columns`                  | Optional | Optional   | --                         |
| `stream_chunk_size`        | Optional | Optional   | --                         |
| `parallelize_exports`      | Optional | ❌ Removed  | No longer supported        |

#### Side-by-Side Comparison

<CodeGroup>
  ```python Version 7 theme={null}
  from arize.exporter import ArizeExportClient
  from arize.utils.types import Environments
  from datetime import datetime

  # Client initialization
  client = ArizeExportClient(api_key="your-api-key")

  # Export spans/traces to Parquet
  client.export_model_to_parquet(
      path="/path/to/output.parquet",
      space_id="your-space-id",
      model_id="my-llm-project",
      environment=Environments.TRACING,
      start_time=datetime(2024, 1, 1),
      end_time=datetime(2024, 1, 31),
      where="span.name = 'generate'",
      columns=["span_id", "parent_span_id", "span.name"],
      stream_chunk_size=1000,
      parallelize_exports=True
  )
  ```

  ```python Version 8 theme={null}
  from arize import ArizeClient
  from datetime import datetime

  # Client initialization
  client = ArizeClient(api_key="your-api-key")

  # Export spans/traces to Parquet
  client.spans.export_to_parquet(
      path="/path/to/output.parquet",
      space_id="your-space-id",
      project_name="my-llm-project",  # Renamed from model_id
      start_time=datetime(2024, 1, 1),
      end_time=datetime(2024, 1, 31),
      where="span.name = 'generate'",
      columns=["span_id", "parent_span_id", "span.name"],
      stream_chunk_size=1000
      # environment removed (always TRACING)
      # include_actuals removed (not applicable)
      # model_version removed (not applicable)
      # batch_id removed (not applicable)
      # parallelize_exports removed
  )
  ```
</CodeGroup>

## Exporting Models (Traditional ML Data)

In v8, model export methods are available on `client.ml`.

### export\_model\_to\_df() for Models

The `export_model_to_df()` method for traditional ML models migrates to `client.ml.export_to_df()`.

#### Parameter Reference

| Parameter                  | v7       | v8         | Changes                 |
| -------------------------- | -------- | ---------- | ----------------------- |
| `space_id`                 | Required | Required   | --                      |
| `model_id`                 | Required | Required   | Renamed to `model_name` |
| `model_name`               | N/A      | ✅ Required | Renamed from `model_id` |
| `environment`              | Required | Required   | --                      |
| `start_time`               | Required | Required   | --                      |
| `end_time`                 | Required | Required   | --                      |
| `include_actuals`          | Optional | Optional   | --                      |
| `model_version`            | Optional | Optional   | --                      |
| `batch_id`                 | Optional | Optional   | --                      |
| `where`                    | Optional | Optional   | --                      |
| `similarity_search_params` | Optional | Optional   | --                      |
| `columns`                  | Optional | Optional   | --                      |
| `stream_chunk_size`        | Optional | Optional   | --                      |
| `parallelize_exports`      | Optional | ❌ Removed  | No longer supported     |

#### Side-by-Side Comparison

<CodeGroup>
  ```python Version 7 theme={null}
  from arize.exporter import ArizeExportClient
  from arize.utils.types import Environments
  from datetime import datetime

  # Client initialization
  client = ArizeExportClient(api_key="your-api-key")

  # Export model data to DataFrame
  df = client.export_model_to_df(
      space_id="your-space-id",
      model_id="fraud-detection",
      environment=Environments.PRODUCTION,
      start_time=datetime(2024, 1, 1),
      end_time=datetime(2024, 1, 31),
      include_actuals=True,
      model_version="v1.0",
      where="prediction_score > 0.8",
      columns=["prediction_id", "prediction_label", "actual_label"],
      stream_chunk_size=1000,
      parallelize_exports=True
  )
  ```

  ```python Version 8 theme={null}
  from arize import ArizeClient
  from arize.ml.types import Environments
  from datetime import datetime

  # Client initialization
  client = ArizeClient(api_key="your-api-key")

  # Export model data to DataFrame
  df = client.ml.export_to_df(
      space_id="your-space-id",
      model_name="fraud-detection",  # Renamed from model_id
      environment=Environments.PRODUCTION,
      start_time=datetime(2024, 1, 1),
      end_time=datetime(2024, 1, 31),
      include_actuals=True,
      model_version="v1.0",
      where="prediction_score > 0.8",
      columns=["prediction_id", "prediction_label", "actual_label"],
      stream_chunk_size=1000
      # parallelize_exports removed
  )
  ```
</CodeGroup>

### export\_model\_to\_parquet() for Models

The `export_model_to_parquet()` method for traditional ML models migrates to `client.ml.export_to_parquet()`.

#### Parameter Reference

| Parameter                  | v7       | v8         | Changes                 |
| -------------------------- | -------- | ---------- | ----------------------- |
| `path`                     | Required | Required   | --                      |
| `space_id`                 | Required | Required   | --                      |
| `model_id`                 | Required | Required   | Renamed to `model_name` |
| `model_name`               | N/A      | ✅ Required | Renamed from `model_id` |
| `environment`              | Required | Required   | --                      |
| `start_time`               | Required | Required   | --                      |
| `end_time`                 | Required | Required   | --                      |
| `include_actuals`          | Optional | Optional   | --                      |
| `model_version`            | Optional | Optional   | --                      |
| `batch_id`                 | Optional | Optional   | --                      |
| `where`                    | Optional | Optional   | --                      |
| `similarity_search_params` | Optional | Optional   | --                      |
| `columns`                  | Optional | Optional   | --                      |
| `stream_chunk_size`        | Optional | Optional   | --                      |
| `parallelize_exports`      | Optional | ❌ Removed  | No longer supported     |

#### Side-by-Side Comparison

<CodeGroup>
  ```python Version 7 theme={null}
  from arize.exporter import ArizeExportClient
  from arize.utils.types import Environments
  from datetime import datetime

  # Client initialization
  client = ArizeExportClient(api_key="your-api-key")

  # Export model data to Parquet
  client.export_model_to_parquet(
      path="/path/to/output.parquet",
      space_id="your-space-id",
      model_id="fraud-detection",
      environment=Environments.PRODUCTION,
      start_time=datetime(2024, 1, 1),
      end_time=datetime(2024, 1, 31),
      include_actuals=True,
      model_version="v1.0",
      where="prediction_score > 0.8",
      columns=["prediction_id", "prediction_label", "actual_label"],
      stream_chunk_size=1000,
      parallelize_exports=True
  )
  ```

  ```python Version 8 theme={null}
  from arize import ArizeClient
  from arize.ml.types import Environments
  from datetime import datetime

  # Client initialization
  client = ArizeClient(api_key="your-api-key")

  # Export model data to Parquet
  client.ml.export_to_parquet(
      path="/path/to/output.parquet",
      space_id="your-space-id",
      model_name="fraud-detection",  # Renamed from model_id
      environment=Environments.PRODUCTION,
      start_time=datetime(2024, 1, 1),
      end_time=datetime(2024, 1, 31),
      include_actuals=True,
      model_version="v1.0",
      where="prediction_score > 0.8",
      columns=["prediction_id", "prediction_label", "actual_label"],
      stream_chunk_size=1000
      # parallelize_exports removed
  )
  ```
</CodeGroup>