src/UserGuide/latest/QuickStart/QuickStart-PYTHON.md

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# Quick Start - Python

## Dependencies and Installation

### Install From Pypi

1. Platform support:

| Platform      | python                           |
| ------------- | -------------------------------- |
| Linux_x86_64  | py39, py310, py311, py312, py313 |
| Linux_aarch64 | py39, py310, py311, py312, py313 |
| MacOS_arm64   | py39, py310, py311, py312, py313 |
| MacOS_X86_64  | py39, py310, py311, py312, py313 |
| Win_amd64     | py39, py310, py311, py312, py313 |

2. Dependencies:

   * numpy >= 1.26.4
   * pandas >= 2.2.2

3. Use pip to install the latest version from pypi:

```shell
pip install tsfile
```

### Install From Wheel File

1. Download wheel from pypi: https://pypi.org/project/tsfile/#files
2. Install the wheel file using the pip install command.
```bash
pip install tsfile.wheel
```

### Install From Source Code Compilation
1. Dependencies

   - CMake >=3.11
   - Maven >=3.9.6
   - GCC >=4.8.5
   - Make >=4.3
   - cython >= 3.0.10
   - numpy >= 1.26.4
   - pandas >= 2.2.2
   - setuptools >= 70.0.0

2. Installation steps

* Clone the source code from git:

```shell
git clone https://github.com/apache/tsfile.git
```
* Run Maven to compile in the TsFile root directory:

```shell
mvn clean install -P with-python -DskipTests
```

* If Maven is not installed, you can compile tsfile using the following command:

  * Linux or Macos:
    ```shell
    mvnw clean install -P with-python -DskipTests
    ```
  * Windows:
    ```shell
    mvnw.cmd clean install -P with-python -DskipTests
    ```
* After successful compilation, the wheel file will be located in the `tsfile/python/dist` directory and can be installed locally using the pip install command (assuming its name is `tsfile.wheel`).
```bash
pip install tsfile.wheel
```


## Writing Process

```Python
import os
from tsfile import *

table_data_dir = os.path.join(os.path.dirname(__file__), "table_data.tsfile")
if os.path.exists(table_data_dir):
    os.remove(table_data_dir)

column1 = ColumnSchema("id", TSDataType.STRING, ColumnCategory.TAG)
column2 = ColumnSchema("id2", TSDataType.STRING, ColumnCategory.TAG)
column3 = ColumnSchema("value", TSDataType.DOUBLE, ColumnCategory.FIELD)
table_schema = TableSchema("test_table", columns=[column1, column2, column3])


### Free resource automatically
with TsFileTableWriter(table_data_dir, table_schema) as writer:
    tablet_row_num = 100
    tablet = Tablet(
                    ["id", "id2", "value"],
                    [TSDataType.STRING, TSDataType.STRING, TSDataType.DOUBLE],
                    tablet_row_num)

    for i in range(tablet_row_num):
        tablet.add_timestamp(i, i * 10)
        tablet.add_value_by_name("id", i, "test1")
        tablet.add_value_by_name("id2", i, "test" + str(i))
        tablet.add_value_by_index(2, i, i * 100.2)

    writer.write_table(tablet)
```

## Reading process (table model)

`TsFileReader` also supports **tree** queries: `query_table_on_tree`, `query_tree_by_row`, and `query_timeseries` — see [Python interface definition](./InterfaceDefinition/InterfaceDefinition-Python.md).

```Python
import os
from tsfile import * 

table_data_dir = os.path.join(os.path.dirname(__file__), "table_data.tsfile")
### Free resource automatically
with TsFileReader(table_data_dir) as reader:
    print(reader.get_all_table_schemas())
    with reader.query_table("test_table", ["id2", "value"], 0, 50) as result:
        print(result.get_metadata())
        while result.next():
            print(result.get_value_by_name("id2"))
            print(result.get_value_by_name("value"))
            print(result.read_data_frame())
```

Use `to_dataframe` to read tsfile as dataframe.

```Python
import os
import tsfile as ts
table_data_dir = os.path.join(os.path.dirname(__file__), "table_data.tsfile")
print(ts.to_dataframe(table_data_dir))
```

## Sample Code

The sample code of using these interfaces is in：https://github.com/apache/tsfile/blob/develop/python/examples/example.py

> The snippets above use the **table** writer/reader. Tree-style usage is documented in [Python interface definition](./InterfaceDefinition/InterfaceDefinition-Python.md) (`query_table_on_tree`, `query_tree_by_row`, etc.). C++ tree APIs are `TsFileTreeReader` / `TsFileTreeWriter` in the source headers `tsfile_tree_reader.h` / `tsfile_tree_writer.h`.