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

# Quick Start

> Get data in 30 seconds

<img src="https://mintcdn.com/jmail/F-FAi3RZzojcIyie/images/jmail-app.png?fit=max&auto=format&n=F-FAi3RZzojcIyie&q=85&s=3d45d0246f3c69c7024d9a467fcfad28" alt="Jmail" style={{ width: '64px', marginBottom: '16px' }} width="207" height="207" data-path="images/jmail-app.png" />

## Python (recommended)

No install required -- uses [PEP 723](https://peps.python.org/pep-0723/) inline dependencies with [`uv`](https://docs.astral.sh/uv/).

```bash theme={null}
# Show first 5 emails
uv run clients/python/jmail.py emails --head 5

# Network-only view (no body text, much smaller)
uv run clients/python/jmail.py emails --slim --head 10

# List all dataset URLs
uv run clients/python/jmail.py urls
```

Or use as a library:

```python theme={null}
from jmail import JmailClient

client = JmailClient()
df = client.emails(slim=True)
print(df.head())
```

## DuckDB (zero download)

Query Parquet files directly over HTTP -- nothing to install beyond DuckDB:

```sql theme={null}
SELECT sender, COUNT(*) as n
FROM read_parquet('https://data.jmail.world/v1/emails-slim.parquet')
GROUP BY sender ORDER BY n DESC LIMIT 20;
```

## Direct Download

Grab any dataset directly:

```bash theme={null}
# Parquet
curl -O https://data.jmail.world/v1/emails-slim.parquet

# NDJSON (gzipped)
curl -O https://data.jmail.world/v1/emails-slim.ndjson.gz
```

## What's Next?

<CardGroup cols={2}>
  <Card title="Browse Datasets" icon="table" href="/datasets">
    See all available datasets and their schemas.
  </Card>

  <Card title="Python Client Reference" icon="python" href="/python-client">
    Full client documentation with caching, options, and CLI.
  </Card>
</CardGroup>