Expose DataFrame-style read API (ReadBuilder / Scan / Split / TableRead) to Python

### Search before asking

- [x] I searched in the [issues](https://github.com/apache/paimon-rust/issues) and found nothing similar.

### Motivation

PyPaimon has two read paths today:

- **SQL** (`SQLContext.sql`) — already runs on the Rust DataFusion engine.
- **DataFrame** (`ReadBuilder → Split → TableRead.to_arrow/to_pandas/to_ray`) —
still **pure Python**, even though the Rust core already implements the same
model in `crates/paimon/src/table/read_builder.rs`. It's just not exposed
through `bindings/python` (`PyTable` only has `identifier/location/schema`).

Goal: expose the existing Rust read API to Python so the DataFrame read path can
optionally run on Rust. Initially this lands as a **basic, opt-in path behind a
config flag**, running alongside the pure-Python reader rather than replacing it,
so the Rust path can mature before it becomes a default. Write path is out of scope.

## Scope (incremental PRs)

This can be implemented incrementally:

- **PR 1** — Expose scan planning:
`new_read_builder()`, `with_projection()`, `with_limit()`, and
`new_scan().plan()` returning serializable splits.

- **PR 2** — Expose filter pushdown:
add `with_filter()` after the Python Predicate → Rust Predicate conversion
layer is defined.

- **PR 3** — Expose split → Arrow read:
`new_read().read(splits)` returning Arrow data backed by Rust `TableRead`.

- **PR 4** (in `apache/paimon`, `[python]`) — Wire PyPaimon's
`to_arrow` / `to_pandas` / `to_ray` to the Rust reader as an **opt-in path**
(config-gated), keeping the pure-Python reader as the default. Unsupported
capabilities error out rather than silently falling back.

PR 1–3 land here; PR 4 lands in the main repo once bindings are released.

### Notes

`with_filter()` is separated from the initial scan-planning PR because it
requires a dedicated Python Predicate → Rust Predicate conversion layer. PR 1
focuses on establishing the Python binding shape and serializable splits.

Design principle: in this model Rust both **plans and reads**.
`new_read().read(splits)` returns Arrow from the Rust `TableRead`, and splits
stay **opaque** on the Python side — a serializable transport token, not
something Python inspects or reads from. Exposing split internals would imply a
Rust-plans / Python-reads path, which is a different direction and out of scope
here.

### Solution

_No response_

### Anything else?

_No response_

### Willingness to contribute

- [x] I'm willing to submit a PR!

Beginnen Sie mit crates/paimon/src/table/read_builder.rs und dem Verzeichnis bindings/python, in dem PyTable derzeit nur identifier, location und schema bereitstellt. Implementieren Sie die in PRs 1–3 beschriebenen Bindings für inkrementelle Scan-Planung, Filterung und Arrow-Lesen, wobei Splits opak und serialisierbar bleiben; als erledigt gilt die Aufgabe, wenn die Rust-Lese-API verfügbar gemacht wurde, ohne den standardmäßigen Python-Reader zu ändern.

Vom Indexierungsmodell aus dem Issue-Text verfasst.