# SQLConn
## 한국어 버전(Korean Version)
SQLConn은 다양한 SQL 데이터베이스 관리 시스템(DBMS)에 연결하여 데이터를 쉽게 조작하고 관리할 수 있는 Python 패키지입니다. 이 패키지는 MySQL, PostgreSQL, Microsoft SQL Server 및 SQLite 데이터베이스에 대한 지원을 포함합니다.
### 기능
- 여러 데이터베이스에 대한 통합된 인터페이스 제공
- 데이터 조회 및 조작을 위한 간편한 함수 제공
- 데이터베이스 쿼리 결과를 DataFrame으로 변환
- CSV, Excel, TSV 파일로의 데이터 출력 지원
- 다른 데이터베이스로의 데이터 이동 지원
### 연결가능한 데이터베이스
- MySQL
- PostgreSQL
- Microsoft SQL Server
- SQLite
### 설치 방법
파이썬과 pip가 설치된 환경에서 다음 명령어를 통해 `SQLConn` 패키지를 설치할 수 있습니다:
```bash
pip install SQLConn
```
### 클래스 소개
| 클래스명 | 소개 | 특이 사항 |
| ------------------ | ----------------------------------------------------------------------- | --------------------------- |
| `SQLConn` | 다양한 SQL 데이터베이스 관리 시스템(DBMS)에 연결하기 위한 클래스입니다. | 추상 클래스입니다. |
| `MYSQLConn` | MySQL 데이터베이스와의 연결을 관리합니다. | SQLConn에게 상속 받았습니다 |
| `MSSQLConn` | Microsoft SQL Server 데이터베이스와의 연결을 관리합니다. | SQLConn에게 상속 받았습니다 |
| `PostgreSQLConn` | PostgreSQL 데이터베이스와의 연결을 관리합니다. | SQLConn에게 상속 받았습니다 |
| `SQLiteConn` | SQLite 파일 기반 데이터베이스와의 연결을 관리합니다. | SQLConn에게 상속 받았습니다 |
### 메소드 소개
| 메소드명 | 소개 | 특이사항 |
| ---------------- | -------------------------------------------------------------- | ------------------------------- |
| `to_DataFrame` | SQL 쿼리를 실행하고 결과를 pandas DataFrame으로 반환합니다. | Show, Select 커맨드만 가능 |
| `execute` | 데이터베이스에서 SQL 쿼리를 실행하되 결과를 반환하지 않습니다. | Show, Select 커맨드 사용 불가능 |
| `to_csv` | SQL 쿼리 결과를 CSV 파일로 저장합니다. | Show, Select 커맨드만 가능 |
| `to_excel` | SQL 쿼리 결과를 Excel 파일로 저장합니다. | Show, Select 커맨드만 가능 |
| `to_tsv` | SQL 쿼리 결과를 TSV 파일로 저장합니다. | Show, Select 커맨드만 가능 |
| `to_sql` | 다른 데이터베이스에 SQL 쿼리 결과를 저장합니다. | Show, Select 커맨드만 가능 |
| `URL` | 데이터베이스 연결 URL을 제공합니다. | 읽기용 프로퍼티 |
| `engine` | 데이터베이스 연결을 위한 SQLAlchemy 엔진을 제공합니다. | 읽기용 프로퍼티 |
### 사용예제
각 데이터베이스 연결 객체를 생성하고 사용하는 기본적인 방법은 다음과 같습니다:
```py
from SQLConn import MYSQLConn, PostgreSQLConn, MSSQLConn, SQLiteConn
# MySQL 데이터베이스에 연결
mysql_conn = MYSQLConn(host='your-host', user='your-user', password='your-password', database='your-database',port='your-port')
# MsSQL 데이터베이스에 연결
mssql_conn = MSSQLConn(host='your-host', user='your-user', password='your-password', database='your-database',port='your-port')
# PostgreSQL 데이터베이스에 연결
postgresql_conn = PostgreSQLConn(host='your-host', user='your-user', password='your-password', database='your-database',port='your-port')
# SQLite 데이터베이스에 연결
mssql_conn = SQLiteConn('your-host')
# 데이터 조회 예제
df = mysql_conn.to_DataFrame("SELECT * FROM your_table")
print(df)
```
### 로컬호스트에서 사용하기
로컬 호스트 데이터베이스 연결 객체를 생성하고 사용하는 기본적인 방법은 다음과 같습니다:
```py
from SQLConn import MYSQLConn, PostgreSQLConn, MSSQLConn
# MySQL 데이터베이스에 연결
mysql_conn = MYSQLConn('your-password')
# MsSQL 데이터베이스에 연결
mssql_conn = MSSQLConn('your-password')
# PostgreSQL 데이터베이스에 연결
postgresql_conn = PostgreSQLConn('your-password')
# 데이터 조회 예제
df = mysql_conn.to_DataFrame("SELECT * FROM your_table")
print(df)
```
### 패키지 주소
- [github](https://github.com/janyoungjin/SQLConn)
- [pypi](https://pypi.org/project/SQLConn/)
## English Version
SQLConn is a Python package that connects to various SQL database management systems (DBMS) to easily manipulate and manage data. This package includes support for MySQL, PostgreSQL, Microsoft SQL Server and SQLite databases.
### function
- Provides a unified interface to multiple databases
- Provides simple functions for data inquiry and manipulation
- Convert database query results to DataFrame
- Supports data output to CSV, Excel, TSV files
- Support for data movement to other databases
### Support database
- MySQL
- PostgreSQL
- Microsoft SQL Server
- SQLite
### How to install
In an environment where Python and pip are installed, you can install the `SQLConn` package using the following command:
```bash
pip install SQLConn
```
### class info
| class name | info | significant |
| ------------------ | ----------------------------------------------------------------------- | ------------------------ |
| `SQLConn` | Class for connecting to various SQL database management systems (DBMS). | It is an abstract class. |
| `MYSQLConn` | Manages MySQL database relationships. | protected SQLConn |
| `MSSQLConn` | Manages connections to Microsoft SQL Server databases. | protected SQLConn |
| `PostgreSQLConn` | Manages connections to PostgreSQL databases. | protected SQLConn |
| `SQLiteConn` | Manages SQLite file-based database relationships. | protected SQLConn |
### method info
| method name | info | significant |
| ---------------- | ------------------------------------------------------------------- | ---------------------------------- |
| `to_DataFrame` | Executes a SQL query and returns the results as a pandas DataFrame. | Show, Select commands only |
| `execute` | Executes a SQL query on a database but returns no results. | Show, Select command not available |
| `to_csv` | Save the SQL query results as a CSV file. | Show, Select commands only |
| `to_excel` | Save the SQL query results as an Excel file. | Show, Select commands only |
| `to_tsv` | Save the SQL query results as a TSV file. | Show, Select commands only |
| `to_sql` | Store SQL query results in another database. | Show, Select commands only |
| `URL` | Provide the database connection URL. | get property |
| `engine` | Provides SQLAlchemy engine for database connection. | get property |
### Example of use
The basic way to create and use each database connection object is as follows:
```py
from SQLConn import MYSQLConn, PostgreSQLConn, MSSQLConn, SQLiteConn
# Connect to MySQL database
mysql_conn = MYSQLConn(host='your-host', user='your-user', password='your-password', database='your-database',port='your-port')
# Connect to MsSQL database
mssql_conn = MSSQLConn(host='your-host', user='your-user', password='your-password', database='your-database',port='your-port')
# Connect to PostgreSQL database
postgresql_conn = PostgreSQLConn(host='your-host', user='your-user', password='your-password', database='your-database',port='your-port')
# Connect to SQLite database
mssql_conn = SQLiteConn('your-host')
# Data query example
df = mysql_conn.to_DataFrame("SELECT * FROM your_table")
print(df)
```
### Using on local host
The basic way to create and use a localhost database connection object is as follows:
```py
from SQLConn import MYSQLConn, PostgreSQLConn, MSSQLConn
# Connect to MySQL database
mysql_conn = MYSQLConn('your-password')
# Connect to MsSQL database
mssql_conn = MSSQLConn('your-password')
# Connect to PostgreSQL database
postgresql_conn = PostgreSQLConn('your-password')
# Data query example
df = mysql_conn.to_DataFrame("SELECT * FROM your_table")
print(df)
```
### package address
- [github](https://github.com/janyoungjin/SQLConn)
- [pypi](https://pypi.org/project/SQLConn/)
### warning
This document was converted from the Korean version to English through a translator, so the meaning may be strange.
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"description": "# SQLConn\r\n\r\n## \ud55c\uad6d\uc5b4 \ubc84\uc804(Korean Version)\r\n\r\nSQLConn\uc740 \ub2e4\uc591\ud55c SQL \ub370\uc774\ud130\ubca0\uc774\uc2a4 \uad00\ub9ac \uc2dc\uc2a4\ud15c(DBMS)\uc5d0 \uc5f0\uacb0\ud558\uc5ec \ub370\uc774\ud130\ub97c \uc27d\uac8c \uc870\uc791\ud558\uace0 \uad00\ub9ac\ud560 \uc218 \uc788\ub294 Python \ud328\ud0a4\uc9c0\uc785\ub2c8\ub2e4. \uc774 \ud328\ud0a4\uc9c0\ub294 MySQL, PostgreSQL, Microsoft SQL Server \ubc0f SQLite \ub370\uc774\ud130\ubca0\uc774\uc2a4\uc5d0 \ub300\ud55c \uc9c0\uc6d0\uc744 \ud3ec\ud568\ud569\ub2c8\ub2e4.\r\n\r\n### \uae30\ub2a5\r\n\r\n- \uc5ec\ub7ec \ub370\uc774\ud130\ubca0\uc774\uc2a4\uc5d0 \ub300\ud55c \ud1b5\ud569\ub41c \uc778\ud130\ud398\uc774\uc2a4 \uc81c\uacf5\r\n- \ub370\uc774\ud130 \uc870\ud68c \ubc0f \uc870\uc791\uc744 \uc704\ud55c \uac04\ud3b8\ud55c \ud568\uc218 \uc81c\uacf5\r\n- \ub370\uc774\ud130\ubca0\uc774\uc2a4 \ucffc\ub9ac \uacb0\uacfc\ub97c DataFrame\uc73c\ub85c \ubcc0\ud658\r\n- CSV, Excel, TSV \ud30c\uc77c\ub85c\uc758 \ub370\uc774\ud130 \ucd9c\ub825 \uc9c0\uc6d0\r\n- \ub2e4\ub978 \ub370\uc774\ud130\ubca0\uc774\uc2a4\ub85c\uc758 \ub370\uc774\ud130 \uc774\ub3d9 \uc9c0\uc6d0\r\n\r\n### \uc5f0\uacb0\uac00\ub2a5\ud55c \ub370\uc774\ud130\ubca0\uc774\uc2a4\r\n\r\n- MySQL\r\n- PostgreSQL\r\n- Microsoft SQL Server\r\n- SQLite\r\n\r\n### \uc124\uce58 \ubc29\ubc95\r\n\r\n\ud30c\uc774\uc36c\uacfc pip\uac00 \uc124\uce58\ub41c \ud658\uacbd\uc5d0\uc11c \ub2e4\uc74c \uba85\ub839\uc5b4\ub97c \ud1b5\ud574 `SQLConn` \ud328\ud0a4\uc9c0\ub97c \uc124\uce58\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4:\r\n\r\n```bash\r\npip install SQLConn\r\n```\r\n\r\n### \ud074\ub798\uc2a4 \uc18c\uac1c\r\n\r\n| \ud074\ub798\uc2a4\uba85 | \uc18c\uac1c | \ud2b9\uc774 \uc0ac\ud56d |\r\n| ------------------ | ----------------------------------------------------------------------- | --------------------------- |\r\n| `SQLConn` | \ub2e4\uc591\ud55c SQL \ub370\uc774\ud130\ubca0\uc774\uc2a4 \uad00\ub9ac \uc2dc\uc2a4\ud15c(DBMS)\uc5d0 \uc5f0\uacb0\ud558\uae30 \uc704\ud55c \ud074\ub798\uc2a4\uc785\ub2c8\ub2e4. | \ucd94\uc0c1 \ud074\ub798\uc2a4\uc785\ub2c8\ub2e4. |\r\n| `MYSQLConn` | MySQL \ub370\uc774\ud130\ubca0\uc774\uc2a4\uc640\uc758 \uc5f0\uacb0\uc744 \uad00\ub9ac\ud569\ub2c8\ub2e4. | SQLConn\uc5d0\uac8c \uc0c1\uc18d \ubc1b\uc558\uc2b5\ub2c8\ub2e4 |\r\n| `MSSQLConn` | Microsoft SQL Server \ub370\uc774\ud130\ubca0\uc774\uc2a4\uc640\uc758 \uc5f0\uacb0\uc744 \uad00\ub9ac\ud569\ub2c8\ub2e4. | SQLConn\uc5d0\uac8c \uc0c1\uc18d \ubc1b\uc558\uc2b5\ub2c8\ub2e4 |\r\n| `PostgreSQLConn` | PostgreSQL \ub370\uc774\ud130\ubca0\uc774\uc2a4\uc640\uc758 \uc5f0\uacb0\uc744 \uad00\ub9ac\ud569\ub2c8\ub2e4. | SQLConn\uc5d0\uac8c \uc0c1\uc18d \ubc1b\uc558\uc2b5\ub2c8\ub2e4 |\r\n| `SQLiteConn` | SQLite \ud30c\uc77c \uae30\ubc18 \ub370\uc774\ud130\ubca0\uc774\uc2a4\uc640\uc758 \uc5f0\uacb0\uc744 \uad00\ub9ac\ud569\ub2c8\ub2e4. | SQLConn\uc5d0\uac8c \uc0c1\uc18d \ubc1b\uc558\uc2b5\ub2c8\ub2e4 |\r\n\r\n### \uba54\uc18c\ub4dc \uc18c\uac1c\r\n\r\n| \uba54\uc18c\ub4dc\uba85 | \uc18c\uac1c | \ud2b9\uc774\uc0ac\ud56d |\r\n| ---------------- | -------------------------------------------------------------- | ------------------------------- |\r\n| `to_DataFrame` | SQL \ucffc\ub9ac\ub97c \uc2e4\ud589\ud558\uace0 \uacb0\uacfc\ub97c pandas DataFrame\uc73c\ub85c \ubc18\ud658\ud569\ub2c8\ub2e4. | Show, Select \ucee4\ub9e8\ub4dc\ub9cc \uac00\ub2a5 |\r\n| `execute` | \ub370\uc774\ud130\ubca0\uc774\uc2a4\uc5d0\uc11c SQL \ucffc\ub9ac\ub97c \uc2e4\ud589\ud558\ub418 \uacb0\uacfc\ub97c \ubc18\ud658\ud558\uc9c0 \uc54a\uc2b5\ub2c8\ub2e4. | Show, Select \ucee4\ub9e8\ub4dc \uc0ac\uc6a9 \ubd88\uac00\ub2a5 |\r\n| `to_csv` | SQL \ucffc\ub9ac \uacb0\uacfc\ub97c CSV \ud30c\uc77c\ub85c \uc800\uc7a5\ud569\ub2c8\ub2e4. | Show, Select \ucee4\ub9e8\ub4dc\ub9cc \uac00\ub2a5 |\r\n| `to_excel` | SQL \ucffc\ub9ac \uacb0\uacfc\ub97c Excel \ud30c\uc77c\ub85c \uc800\uc7a5\ud569\ub2c8\ub2e4. | Show, Select \ucee4\ub9e8\ub4dc\ub9cc \uac00\ub2a5 |\r\n| `to_tsv` | SQL \ucffc\ub9ac \uacb0\uacfc\ub97c TSV \ud30c\uc77c\ub85c \uc800\uc7a5\ud569\ub2c8\ub2e4. | Show, Select \ucee4\ub9e8\ub4dc\ub9cc \uac00\ub2a5 |\r\n| `to_sql` | \ub2e4\ub978 \ub370\uc774\ud130\ubca0\uc774\uc2a4\uc5d0 SQL \ucffc\ub9ac \uacb0\uacfc\ub97c \uc800\uc7a5\ud569\ub2c8\ub2e4. | Show, Select \ucee4\ub9e8\ub4dc\ub9cc \uac00\ub2a5 |\r\n| `URL` | \ub370\uc774\ud130\ubca0\uc774\uc2a4 \uc5f0\uacb0 URL\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4. | \uc77d\uae30\uc6a9 \ud504\ub85c\ud37c\ud2f0 |\r\n| `engine` | \ub370\uc774\ud130\ubca0\uc774\uc2a4 \uc5f0\uacb0\uc744 \uc704\ud55c SQLAlchemy \uc5d4\uc9c4\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4. | \uc77d\uae30\uc6a9 \ud504\ub85c\ud37c\ud2f0 |\r\n\r\n### \uc0ac\uc6a9\uc608\uc81c\r\n\r\n\uac01 \ub370\uc774\ud130\ubca0\uc774\uc2a4 \uc5f0\uacb0 \uac1d\uccb4\ub97c \uc0dd\uc131\ud558\uace0 \uc0ac\uc6a9\ud558\ub294 \uae30\ubcf8\uc801\uc778 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4:\r\n\r\n```py\r\nfrom SQLConn import MYSQLConn, PostgreSQLConn, MSSQLConn, SQLiteConn\r\n\r\n# MySQL \ub370\uc774\ud130\ubca0\uc774\uc2a4\uc5d0 \uc5f0\uacb0\r\nmysql_conn = MYSQLConn(host='your-host', user='your-user', password='your-password', database='your-database',port='your-port')\r\n\r\n# MsSQL \ub370\uc774\ud130\ubca0\uc774\uc2a4\uc5d0 \uc5f0\uacb0\r\nmssql_conn = MSSQLConn(host='your-host', user='your-user', password='your-password', database='your-database',port='your-port')\r\n\r\n# PostgreSQL \ub370\uc774\ud130\ubca0\uc774\uc2a4\uc5d0 \uc5f0\uacb0\r\npostgresql_conn = PostgreSQLConn(host='your-host', user='your-user', password='your-password', database='your-database',port='your-port')\r\n\r\n# SQLite \ub370\uc774\ud130\ubca0\uc774\uc2a4\uc5d0 \uc5f0\uacb0\r\nmssql_conn = SQLiteConn('your-host')\r\n\r\n# \ub370\uc774\ud130 \uc870\ud68c \uc608\uc81c\r\ndf = mysql_conn.to_DataFrame(\"SELECT * FROM your_table\")\r\nprint(df)\r\n```\r\n\r\n### \ub85c\uceec\ud638\uc2a4\ud2b8\uc5d0\uc11c \uc0ac\uc6a9\ud558\uae30\r\n\r\n\ub85c\uceec \ud638\uc2a4\ud2b8 \ub370\uc774\ud130\ubca0\uc774\uc2a4 \uc5f0\uacb0 \uac1d\uccb4\ub97c \uc0dd\uc131\ud558\uace0 \uc0ac\uc6a9\ud558\ub294 \uae30\ubcf8\uc801\uc778 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4:\r\n\r\n```py\r\nfrom SQLConn import MYSQLConn, PostgreSQLConn, MSSQLConn\r\n\r\n# MySQL \ub370\uc774\ud130\ubca0\uc774\uc2a4\uc5d0 \uc5f0\uacb0\r\nmysql_conn = MYSQLConn('your-password')\r\n\r\n# MsSQL \ub370\uc774\ud130\ubca0\uc774\uc2a4\uc5d0 \uc5f0\uacb0\r\nmssql_conn = MSSQLConn('your-password')\r\n\r\n# PostgreSQL \ub370\uc774\ud130\ubca0\uc774\uc2a4\uc5d0 \uc5f0\uacb0\r\npostgresql_conn = PostgreSQLConn('your-password')\r\n\r\n# \ub370\uc774\ud130 \uc870\ud68c \uc608\uc81c\r\ndf = mysql_conn.to_DataFrame(\"SELECT * FROM your_table\")\r\nprint(df)\r\n```\r\n\r\n### \ud328\ud0a4\uc9c0 \uc8fc\uc18c\r\n\r\n- [github](https://github.com/janyoungjin/SQLConn)\r\n- [pypi](https://pypi.org/project/SQLConn/)\r\n\r\n## English Version\r\n\r\nSQLConn is a Python package that connects to various SQL database management systems (DBMS) to easily manipulate and manage data. This package includes support for MySQL, PostgreSQL, Microsoft SQL Server and SQLite databases.\r\n\r\n### function\r\n\r\n- Provides a unified interface to multiple databases\r\n- Provides simple functions for data inquiry and manipulation\r\n- Convert database query results to DataFrame\r\n- Supports data output to CSV, Excel, TSV files\r\n- Support for data movement to other databases\r\n\r\n### Support database\r\n\r\n- MySQL\r\n- PostgreSQL\r\n- Microsoft SQL Server\r\n- SQLite\r\n\r\n### How to install\r\n\r\nIn an environment where Python and pip are installed, you can install the `SQLConn` package using the following command:\r\n\r\n```bash\r\npip install SQLConn\r\n```\r\n\r\n### class info\r\n\r\n| class name | info | significant |\r\n| ------------------ | ----------------------------------------------------------------------- | ------------------------ |\r\n| `SQLConn` | Class for connecting to various SQL database management systems (DBMS). | It is an abstract class. |\r\n| `MYSQLConn` | Manages MySQL database relationships. | protected SQLConn |\r\n| `MSSQLConn` | Manages connections to Microsoft SQL Server databases. | protected SQLConn |\r\n| `PostgreSQLConn` | Manages connections to PostgreSQL databases. | protected SQLConn |\r\n| `SQLiteConn` | Manages SQLite file-based database relationships. | protected SQLConn |\r\n\r\n### method info\r\n\r\n| method name | info | significant |\r\n| ---------------- | ------------------------------------------------------------------- | ---------------------------------- |\r\n| `to_DataFrame` | Executes a SQL query and returns the results as a pandas DataFrame. | Show, Select commands only |\r\n| `execute` | Executes a SQL query on a database but returns no results. | Show, Select command not available |\r\n| `to_csv` | Save the SQL query results as a CSV file. | Show, Select commands only |\r\n| `to_excel` | Save the SQL query results as an Excel file. | Show, Select commands only |\r\n| `to_tsv` | Save the SQL query results as a TSV file. | Show, Select commands only |\r\n| `to_sql` | Store SQL query results in another database. | Show, Select commands only |\r\n| `URL` | Provide the database connection URL. | get property |\r\n| `engine` | Provides SQLAlchemy engine for database connection. | get property |\r\n\r\n### Example of use\r\n\r\nThe basic way to create and use each database connection object is as follows:\r\n\r\n```py\r\nfrom SQLConn import MYSQLConn, PostgreSQLConn, MSSQLConn, SQLiteConn\r\n\r\n# Connect to MySQL database\r\nmysql_conn = MYSQLConn(host='your-host', user='your-user', password='your-password', database='your-database',port='your-port')\r\n\r\n# Connect to MsSQL database\r\nmssql_conn = MSSQLConn(host='your-host', user='your-user', password='your-password', database='your-database',port='your-port')\r\n\r\n# Connect to PostgreSQL database\r\npostgresql_conn = PostgreSQLConn(host='your-host', user='your-user', password='your-password', database='your-database',port='your-port')\r\n\r\n# Connect to SQLite database\r\nmssql_conn = SQLiteConn('your-host')\r\n\r\n# Data query example\r\ndf = mysql_conn.to_DataFrame(\"SELECT * FROM your_table\")\r\nprint(df)\r\n```\r\n\r\n### Using on local host\r\n\r\nThe basic way to create and use a localhost database connection object is as follows:\r\n\r\n```py\r\nfrom SQLConn import MYSQLConn, PostgreSQLConn, MSSQLConn\r\n\r\n# Connect to MySQL database\r\nmysql_conn = MYSQLConn('your-password')\r\n\r\n# Connect to MsSQL database\r\nmssql_conn = MSSQLConn('your-password')\r\n\r\n# Connect to PostgreSQL database\r\npostgresql_conn = PostgreSQLConn('your-password')\r\n\r\n# Data query example\r\ndf = mysql_conn.to_DataFrame(\"SELECT * FROM your_table\")\r\nprint(df)\r\n```\r\n\r\n### package address\r\n\r\n- [github](https://github.com/janyoungjin/SQLConn)\r\n\r\n- [pypi](https://pypi.org/project/SQLConn/)\r\n\r\n### warning\r\n\r\nThis document was converted from the Korean version to English through a translator, so the meaning may be strange.\r\n",
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