# Table.to\_read\_streams

### Table.<mark style="color:purple;">to\_read\_streams</mark>(*target\_count=os.cpu\_count(), \*, variables=None*) → list([ReadStream](/api/client-libraries/redivis-python/reference/readstream.md))

Returns a list of ReadStreams that can be used to consume and process the table in parallel.

{% hint style="info" %}
Also callable on [Queries](/api/client-libraries/redivis-python/reference/query.md) and [Uploads](/api/client-libraries/redivis-python/reference/upload.md) →  `query.to_read_streams(...)` | `upload.to_read_streams(...)`
{% endhint %}

### **Parameters:**&#x20;

**`target_count` :&#x20;*****int, default os.cpu\_count()*** \
The target number of streams to return. Note that the actual number of streams returned may be different than this number – smaller tables will generally return fewer streams, and unreleased tables that span across mutliple uploads may return more streams.

**`variables` :&#x20;*****list\<str>, default None***\
A list of variable names to read, improving performance when not all variables are needed. If unspecified, all variables will be represented in the returned rows. Variable names are case-insensitive, though the names in the results will reflect the variable's true casing. The order of the columns returned will correspond to the order of names in this list.

### **Returns:**&#x20;

list( [ReadStream](/api/client-libraries/redivis-python/reference/readstream.md) )

### Examples:

```python
import redivis
from concurrent.futures import ThreadPoolExecutor, as_completed

table = redivis.table(
    "demo.cms_2014_medicare_data:349j.physicians_and_other_supplier:kn00"
)

streams = table.to_read_streams(
    variables=["average_submitted_chrg_amt"], target_count=4
)

def process_stream(stream):
    """Process a single stream, returning the sum and count for the column."""
    total = 0
    count = 0
    # Each stream can be read as an Arrow record batch reader

    for batch in stream.to_arrow_batch_iterator():
        column = batch.column("average_submitted_chrg_amt")
        # Filter out nulls
        valid = column.drop_null()
        total += valid.to_pylist().__len__() and sum(valid.to_pylist()) or 0
        count += len(valid)
    return total, count

# Process all streams in parallel using a thread pool
grand_total = 0
grand_count = 0

with ThreadPoolExecutor(max_workers=len(streams)) as executor:
    futures = {
        executor.submit(process_stream, stream): stream for stream in streams
    }
    for future in as_completed(futures):
        total, count = future.result()
        grand_total += total
        grand_count += count

average = grand_total / grand_count if grand_count > 0 else 0
print(f"Average submitted charge amount: ${average:.2f}")
print(f"Computed across {grand_count} rows using {len(streams)} parallel streams")
```


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.redivis.com/api/client-libraries/redivis-python/reference/table/table.to_read_streams.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.