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new bfa48045ef [Python] Update Doc for Read Splits and Data Types (#6254)
bfa48045ef is described below
commit bfa48045ef60ef922a673b292464d25506ace276
Author: ChengHui Chen <27797326+chenghuic...@users.noreply.github.com>
AuthorDate: Mon Sep 15 11:59:50 2025 +0800
[Python] Update Doc for Read Splits and Data Types (#6254)
---
docs/content/program-api/python-api.md | 53 ++++++++++++++++++++++------------
1 file changed, 35 insertions(+), 18 deletions(-)
diff --git a/docs/content/program-api/python-api.md
b/docs/content/program-api/python-api.md
index ab4967a895..a5ab249cc5 100644
--- a/docs/content/program-api/python-api.md
+++ b/docs/content/program-api/python-api.md
@@ -25,9 +25,7 @@ specific language governing permissions and limitations
under the License.
-->
-# Java-based Implementation For Python API
-
-[Python SDK ](https://github.com/apache/paimon-python) has defined Python API
for Paimon.
+# Python API
## Environment Settings
@@ -65,7 +63,7 @@ Table is located in a database. If you want to create table
in a new database, y
```python
catalog.create_database(
name='database_name',
- ignore_if_exists=True, # If you want to raise error if the database
exists, set False
+ ignore_if_exists=True, # To raise error if the database exists, set False
properties={'key': 'value'} # optional database properties
)
```
@@ -138,7 +136,7 @@ schema = ...
catalog.create_table(
identifier='database_name.table_name',
schema=schema,
- ignore_if_exists=True # If you want to raise error if the table exists,
set False
+ ignore_if_exists=True # To raise error if the table exists, set False
)
```
@@ -193,10 +191,10 @@ API:
```python
# overwrite whole table
-write_builder.overwrite()
+write_builder = table.new_batch_write_builder().overwrite()
# overwrite partition 'dt=2024-01-01'
-write_builder.overwrite({'dt': '2024-01-01'})
+write_builder = table.new_batch_write_builder().overwrite({'dt': '2024-01-01'})
```
## Batch Read
@@ -272,7 +270,7 @@ You can also read data into a `pyarrow.RecordBatchReader`
and iterate record bat
```python
table_read = read_builder.new_read()
-for batch in table_read.to_iterator(splits):
+for batch in table_read.to_arrow_batch_reader(splits):
print(batch)
# pyarrow.RecordBatch
@@ -283,6 +281,19 @@ for batch in table_read.to_iterator(splits):
# f1: ["a","b","c"]
```
+#### Python Iterator
+You can read the data row by row into a native Python iterator.
+This is convenient for custom row-based processing logic.
+
+```python
+table_read = read_builder.new_read()
+for row in table_read.to_iterator(splits):
+ print(row)
+
+# [1,2,3]
+# ["a","b","c"]
+```
+
#### Pandas
This requires `pandas` to be installed.
@@ -351,16 +362,22 @@ print(ray_dataset.to_pandas())
```
## Data Types
-
-| pyarrow | Paimon
|
-|:-----------------------------------------------------------------|:---------|
-| pyarrow.int8() | TINYINT |
-| pyarrow.int16() | SMALLINT |
-| pyarrow.int32() | INT |
-| pyarrow.int64() | BIGINT |
-| pyarrow.float16() <br/>pyarrow.float32() <br/>pyarrow.float64() | FLOAT |
-| pyarrow.string() | STRING |
-| pyarrow.boolean() | BOOLEAN |
+| Python Native Type | PyArrow Type | Paimon Type |
+| :--- | :--- | :--- |
+| `int` | `pyarrow.int8()` | `TINYINT` |
+| `int` | `pyarrow.int16()` | `SMALLINT` |
+| `int` | `pyarrow.int32()` | `INT` |
+| `int` | `pyarrow.int64()` | `BIGINT` |
+| `float` | `pyarrow.float32()` | `FLOAT` |
+| `float` | `pyarrow.float64()` | `DOUBLE` |
+| `bool` | `pyarrow.bool_()` | `BOOLEAN` |
+| `str` | `pyarrow.string()` | `STRING`, `CHAR(n)`, `VARCHAR(n)` |
+| `bytes` | `pyarrow.binary()` | `BYTES`, `VARBINARY(n)` |
+| `bytes` | `pyarrow.binary(length)` | `BINARY(length)` |
+| `decimal.Decimal` | `pyarrow.decimal128(precision, scale)` |
`DECIMAL(precision, scale)` |
+| `datetime.datetime` | `pyarrow.timestamp(unit, tz=None)` | `TIMESTAMP(p)` |
+| `datetime.date` | `pyarrow.date32()` | `DATE` |
+| `datetime.time` | `pyarrow.time32(unit)` or `pyarrow.time64(unit)` |
`TIME(p)` |
## Predicate
