# Share a D-Tale View — Without Leaving the Server Running

Canonical: https://commareports.com/share-dtale-report
Published: 2026-09-14

> D-Tale is a Flask app on your laptop, so the link dies when you close the notebook. Export the static chart or profile and publish it to Comma for a URL that outlives the session.

# Share a D-Tale view

D-Tale is excellent at the thing it does: one line in a notebook and you have a
real grid over a DataFrame, with filters, describe, correlations and charts.
The line is also the problem.

```python
import dtale
dtale.show(df)
# http://your-laptop:40000/dtale/main/1
```

That is a Flask server running on your machine. The URL is bound to a process
in your kernel, on your network, behind whatever VPN you are on. Sent to a
colleague it fails immediately; kept for tomorrow it fails when the kernel
restarts. Every "can you send me that view?" ends in a screenshot.

## Export the view, not the server

D-Tale exports static versions of the pieces that carry findings:

```python
import dtale

# a self-contained chart
html = dtale.offline_chart(
    df, chart_type="bar", x="region", y="revenue", agg="sum"
)
open("revenue.html", "w").write(html)
```

And the frame itself, when the finding is the rows:

```python
df.query("nulls > 0").to_html("suspect_rows.html", index=False)
```

`offline_chart` renders without the backend — that is its whole purpose — so
the result is a file that survives being moved.

## Publish it

Drop the HTML into [Comma](https://commareports.com/), or from the notebook:

```python
import requests, os

requests.post(
    "https://commareports.com/api/v1/reports",
    headers={"Authorization": f"Bearer {os.environ['COMMA_API_TOKEN']}"},
    json={"title": "Revenue by region — Q3", "html": html},
).raise_for_status()
```

Scripts run inside a sandboxed iframe (`allow-scripts`, no `allow-same-origin`),
so the exported Plotly chart keeps its hover, zoom and legend toggles — the
interaction that a screenshot of the same chart throws away. See the
[API reference](/docs/api).

## Publish the profile, not the grid

The instinct is to want the whole interactive grid shared. It is worth being
honest about what the reader actually needs: the grid is an exploration tool
for the person who knows the data. The reviewer needs the finding.

So publish:

- the **chart** that shows the anomaly,
- the **describe/correlation** panel that supports it,
- the **filtered rows** as an HTML table — the evidence.

That set is readable in a minute and is exactly what a screenshot fails to
carry, because the numbers in a screenshot cannot be selected, searched or
commented on.

## Comments where the column is

Data review dies in messaging apps: "the revenue column looks off after June"
with an image attached, and three people re-deriving the same query. Anchored
threads keep the observation on the column or the row it is about, and the
report takes a revision every time you republish with fresh data — so the
conversation and the data stay together. See
[commenting on HTML](/comment-on-html).

## Who can see it

Per report: private, your team, anyone signed in at your domain, or anyone with
the link. Exported rows are real data — restrict accordingly, and aggregate
before publishing when the rows are personal. See
[sharing & access control](/docs/sharing).

## Limits

- **Entry HTML: 5 MB.** A `to_html()` of a large frame blows past that quickly —
  publish an aggregate or a sample, which is also more readable.
- Assets: 25 MB per file, **250 MB and 500 files total**.
- **60 requests/minute per token.**

## Try it

Comma is free — unlimited reports, unlimited commenters, unlimited revision
history.

**[Publish a data view →](https://commareports.com/)**

### Related

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- [Share a Sweetviz report](/share-sweetviz-report) · [Share an EDA report](/share-eda-report)
- [Share a Streamlit app](/share-streamlit-app) · [localhost links don't work for others](/fix/localhost-link-doesnt-work-for-others)