<h1 align="center">Pyexasol</h1>
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PyEXASOL is the officially supported Python connector for [Exasol](https://www.exasol.com). It helps to handle massive volumes of data commonly associated with this DBMS.
You may expect significant performance improvement over ODBC in a single process scenario involving pandas.
PyEXASOL provides API to read & write multiple data streams in parallel using separate processes, which is necessary to fully utilize hardware and achieve linear scalability. With PyEXASOL you are no longer limited to a single CPU core.
## Quick links
- [Getting started](#getting-started)
- [Reference](/docs/REFERENCE.md)
- [Examples](/docs/EXAMPLES.md)
- [Best practices](/docs/BEST_PRACTICES.md)
- [Local config (.ini file)](/docs/LOCAL_CONFIG.md)
- [SQL formatting](/docs/SQL_FORMATTING.md)
- [HTTP Transport](/docs/HTTP_TRANSPORT.md)
- [HTTP Transport (multiprocessing)](/docs/HTTP_TRANSPORT_PARALLEL.md)
- [Parallelism](/docs/PARALLELISM.md)
- [SSL encryption](/docs/ENCRYPTION.md)
- [WebSocket protocol versions](/docs/PROTOCOL_VERSION.md)
- [Performance tests](/docs/PERFORMANCE.md)
- [UDF scripts output](/docs/SCRIPT_OUTPUT.md)
- [DB-API 2.0 compatibility](/docs/DBAPI_COMPAT.md)
- [Optional dependencies](/docs/DEPENDENCIES.md)
- [Changelog](/CHANGELOG.md)
- [Developer Guide](/docs/DEVELOPER_GUIDE.md)
## PyEXASOL main concepts
- Based on [WebSocket protocol](https://github.com/exasol/websocket-api);
- Optimized for minimum overhead;
- Easy integration with pandas via HTTP transport;
- Compression to reduce network bottleneck;
## System requirements
- Exasol >= 7.1
- Python >= 3.9
## Getting started
Install PyEXASOL:
```
pip install pyexasol[pandas]
```
Run basic query:
```python
import pyexasol
C = pyexasol.connect(dsn='<host:port>', user='sys', password='exasol')
stmt = C.execute("SELECT * FROM EXA_ALL_USERS")
for row in stmt:
print(row)
```
Load data into `pandas.DataFrame`:
```python
import pyexasol
C = pyexasol.connect(dsn='<host:port>', user='sys', password='exasol', compression=True)
df = C.export_to_pandas("SELECT * FROM EXA_ALL_USERS")
print(df.head())
```
You may set up [local config](/docs/LOCAL_CONFIG.md) to store your personal Exasol credentials and connection options:
```python
import pyexasol
C = pyexasol.connect_local_config('my_config')
stmt = C.execute("SELECT CURRENT_TIMESTAMP")
print(stmt.fetchone())
```
Connect to Exasol SAAS using OpenID token for authentication:
```python
import pyexasol
C = pyexasol.connect(dsn='<host:port>', user='sys', refresh_token='<token>')
stmt = C.execute("SELECT * FROM EXA_ALL_USERS")
for row in stmt:
print(row)
```
## Created by
[Vitaly Markov](https://www.linkedin.com/in/markov-vitaly/), 2018 — 2022
Enjoy!
## Maintained by
[Exasol](https://www.exasol.com) 2023 — Today
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"description": "<h1 align=\"center\">Pyexasol</h1>\n<p align=\"center\">\n<a href=\"https://github.com/exasol/pyexasol/actions/workflows/ci-master.yml\">\n <img src=\"https://github.com/exasol/pyexasol/actions/workflows/ci-master.yml/badge.svg\" alt=\"Continuous Integration (master)\">\n</a>\n<a href=\"https://anaconda.org/conda-forge/pyexasol\">\n <img src=\"https://anaconda.org/conda-forge/pyexasol/badges/version.svg\" alt=\"Anaconda\">\n</a>\n<a href=\"https://pypi.org/project/pyexasol/\">\n <img src=\"https://img.shields.io/pypi/v/pyexasol\" alt=\"PyPi Package\">\n</a>\n<a href=\"https://pypi.org/project/pyexasol/\">\n <img src=\"https://img.shields.io/pypi/dm/pyexasol\" alt=\"Downloads\">\n</a>\n<a href=\"https://pypi.org/project/pyexasol/\">\n <img src=\"https://img.shields.io/pypi/pyversions/pyexasol\" alt=\"Supported Python Versions\">\n</a>\n</p>\n\nPyEXASOL is the officially supported Python connector for [Exasol](https://www.exasol.com). It helps to handle massive volumes of data commonly associated with this DBMS.\n\nYou may expect significant performance improvement over ODBC in a single process scenario involving pandas.\n\nPyEXASOL provides API to read & write multiple data streams in parallel using separate processes, which is necessary to fully utilize hardware and achieve linear scalability. With PyEXASOL you are no longer limited to a single CPU core.\n\n\n## Quick links\n- [Getting started](#getting-started)\n- [Reference](/docs/REFERENCE.md)\n- [Examples](/docs/EXAMPLES.md)\n- [Best practices](/docs/BEST_PRACTICES.md)\n- [Local config (.ini file)](/docs/LOCAL_CONFIG.md)\n- [SQL formatting](/docs/SQL_FORMATTING.md)\n- [HTTP Transport](/docs/HTTP_TRANSPORT.md)\n- [HTTP Transport (multiprocessing)](/docs/HTTP_TRANSPORT_PARALLEL.md)\n- [Parallelism](/docs/PARALLELISM.md)\n- [SSL encryption](/docs/ENCRYPTION.md)\n- [WebSocket protocol versions](/docs/PROTOCOL_VERSION.md)\n- [Performance tests](/docs/PERFORMANCE.md)\n- [UDF scripts output](/docs/SCRIPT_OUTPUT.md)\n- [DB-API 2.0 compatibility](/docs/DBAPI_COMPAT.md)\n- [Optional dependencies](/docs/DEPENDENCIES.md)\n- [Changelog](/CHANGELOG.md)\n- [Developer Guide](/docs/DEVELOPER_GUIDE.md)\n\n\n## PyEXASOL main concepts\n\n- Based on [WebSocket protocol](https://github.com/exasol/websocket-api);\n- Optimized for minimum overhead;\n- Easy integration with pandas via HTTP transport;\n- Compression to reduce network bottleneck;\n\n\n## System requirements\n\n- Exasol >= 7.1\n- Python >= 3.9\n\n\n## Getting started\n\nInstall PyEXASOL:\n```\npip install pyexasol[pandas]\n```\n\nRun basic query:\n```python\nimport pyexasol\n\nC = pyexasol.connect(dsn='<host:port>', user='sys', password='exasol')\n\nstmt = C.execute(\"SELECT * FROM EXA_ALL_USERS\")\n\nfor row in stmt:\n print(row)\n```\n\nLoad data into `pandas.DataFrame`:\n```python\nimport pyexasol\n\nC = pyexasol.connect(dsn='<host:port>', user='sys', password='exasol', compression=True)\n\ndf = C.export_to_pandas(\"SELECT * FROM EXA_ALL_USERS\")\nprint(df.head())\n```\n\nYou may set up [local config](/docs/LOCAL_CONFIG.md) to store your personal Exasol credentials and connection options:\n```python\nimport pyexasol\n\nC = pyexasol.connect_local_config('my_config')\n\nstmt = C.execute(\"SELECT CURRENT_TIMESTAMP\")\nprint(stmt.fetchone())\n```\n\nConnect to Exasol SAAS using OpenID token for authentication:\n\n```python\nimport pyexasol\n\nC = pyexasol.connect(dsn='<host:port>', user='sys', refresh_token='<token>')\n\nstmt = C.execute(\"SELECT * FROM EXA_ALL_USERS\")\n\nfor row in stmt:\n print(row)\n```\n\n## Created by\n[Vitaly Markov](https://www.linkedin.com/in/markov-vitaly/), 2018 \u2014 2022\n\nEnjoy!\n\n## Maintained by\n[Exasol](https://www.exasol.com) 2023 \u2014 Today \n",
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