# DataElevate
**DataElevate** is a Python library designed to streamline the process of downloading, loading, and extracting data from various sources such as Google Drive, Kaggle, and local archives. It simplifies working with data files, enabling developers and analysts to focus on their data analysis tasks.
---
## Features
- **Download Data**:
- Easily download files from Google Drive and Kaggle.
- **Load Data**:
- Load data directly from CSV, Excel, text, or other supported file formats.
- **Extract Archives**:
- Extract files from compressed archives (e.g., `.zip`, `.tar`, `.gz`).
---
## Installation
Install the package using pip:
```bash
pip install DataElevate
```
---
## Quickstart
Here's how to get started with DataElevate:
### 1. Import the Library
```python
from DataElevate import Download_data, Load_data, Extractor
```
## 2. Download Data
### `GoogleDrive`
Downloads a files/ folders from Google Drive.
### File download
```python
Download_data.GoogleDrive.download_file(url/ file_id: str, destination: str) #destination: Optional
```
### Folder download
```python
Download_data.GoogleDrive.download_folder(url/ file_id: str, destination: str) #destination: Optional
```
### Check FileName
```python
Download_data.GoogleDrive.check_filename(url/ file_id: str)
```
### Get Id of file
```python
Download_data.GoogleDrive.get_file_id(url : str)
```
### Kaggle
```python
# Provide Kaggle dataset path and destination
Download_data.Kaggle.from_kaggle(dataset="kaggle-dataset-URL", destination="path/to/save") #destination: Optional
```
## 3. Load Data
### From Local (CSV, Text, Excel)
```python
data = Load_data.from_local("path/to/your_file")
```
### From Kaggle
```python
data = Load_data.from_kaggle(url = "kaggle-dataset-URL")
```
### From Drive (Under Maintenance)
```python
data = Load_data.from_drive(url = "dataset url from drive")
```
### From Database (Under Maintenance)
#### Supported Databases
The following databases are supported:
- PostgreSQL
- MySQL
- Microsoft SQL Server (MSSQL)
- Oracle
- SQLite
- MariaDB
- Amazon RDS
- Azure SQL
#### Usage Examples
### Loading Data from PostgreSQL (Under Maintenance)
To load data from a PostgreSQL database, use the `from_postgresql` method:
```python
data = Load_data.Database.from_postgresql(
db_name='your_database_name',
table_name='your_table_name',
username='your_username',
password='your_password',
host='your_host',
port='your_port'
)
```
### Loading Data from SQLite (Under Maintenance)
To load data from an SQLite database, use the sqlite method:
```python
data = Load_data.Database.sqlite(
db_name='your_database_name',
table_name='your_table_name'
)
```
### Generalized Syntax for Other Databases (Under Maintenance)
```python
data = Load_data.Database.DataBase_Type(
db_name='your_database_name',
table_name='your_table_name',
username='your_username',
password='your_password',
host='your_host',
port='your_port'
)
```
### Example
```python
data = Load_data.Database.from_mysql(
db_name='your_database_name',
table_name='your_table_name',
username='your_username',
password='your_password',
host='your_host',
port='your_port'
)
```
## 4. Extract Archives
```python
Extractor.extract_archive("path/to/your_archive.zip", destination="path/to/extract") destination: Optional
```
---
## Contributing
Contributions are welcome! Feel free to submit a pull request or raise issues for any bugs or feature requests.
---
## License
This project is licensed under the MIT License.
See the LICENSE file for more details.
---
## Author
**Name:** Moanl Bhiwgade
**Email:** 3051monal@gmail.com
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"description": "# DataElevate\r\n\r\n**DataElevate** is a Python library designed to streamline the process of downloading, loading, and extracting data from various sources such as Google Drive, Kaggle, and local archives. It simplifies working with data files, enabling developers and analysts to focus on their data analysis tasks.\r\n\r\n---\r\n\r\n## Features\r\n\r\n- **Download Data**: \r\n - Easily download files from Google Drive and Kaggle.\r\n- **Load Data**: \r\n - Load data directly from CSV, Excel, text, or other supported file formats.\r\n- **Extract Archives**:\r\n - Extract files from compressed archives (e.g., `.zip`, `.tar`, `.gz`).\r\n\r\n---\r\n\r\n## Installation\r\n\r\nInstall the package using pip:\r\n\r\n```bash\r\npip install DataElevate\r\n```\r\n\r\n---\r\n\r\n## Quickstart\r\n\r\nHere's how to get started with DataElevate:\r\n\r\n### 1. Import the Library\r\n\r\n```python\r\nfrom DataElevate import Download_data, Load_data, Extractor\r\n```\r\n\r\n## 2. Download Data\r\n\r\n### `GoogleDrive`\r\nDownloads a files/ folders from Google Drive.\r\n\r\n### File download\r\n```python\r\nDownload_data.GoogleDrive.download_file(url/ file_id: str, destination: str) #destination: Optional\r\n```\r\n\r\n### Folder download\r\n```python \r\nDownload_data.GoogleDrive.download_folder(url/ file_id: str, destination: str) #destination: Optional\r\n```\r\n\r\n### Check FileName\r\n```python\r\nDownload_data.GoogleDrive.check_filename(url/ file_id: str)\r\n```\r\n\r\n### Get Id of file\r\n```python\r\nDownload_data.GoogleDrive.get_file_id(url : str)\r\n```\r\n\r\n### Kaggle\r\n\r\n```python\r\n# Provide Kaggle dataset path and destination\r\nDownload_data.Kaggle.from_kaggle(dataset=\"kaggle-dataset-URL\", destination=\"path/to/save\") #destination: Optional\r\n```\r\n\r\n## 3. Load Data\r\n\r\n### From Local (CSV, Text, Excel)\r\n\r\n```python\r\ndata = Load_data.from_local(\"path/to/your_file\")\r\n```\r\n### From Kaggle\r\n\r\n```python\r\ndata = Load_data.from_kaggle(url = \"kaggle-dataset-URL\")\r\n```\r\n\r\n### From Drive (Under Maintenance)\r\n\r\n```python\r\ndata = Load_data.from_drive(url = \"dataset url from drive\")\r\n```\r\n\r\n### From Database (Under Maintenance)\r\n\r\n#### Supported Databases\r\nThe following databases are supported:\r\n- PostgreSQL\r\n- MySQL\r\n- Microsoft SQL Server (MSSQL)\r\n- Oracle\r\n- SQLite\r\n- MariaDB\r\n- Amazon RDS\r\n- Azure SQL\r\n\r\n#### Usage Examples\r\n\r\n### Loading Data from PostgreSQL (Under Maintenance)\r\nTo load data from a PostgreSQL database, use the `from_postgresql` method:\r\n```python\r\ndata = Load_data.Database.from_postgresql(\r\n db_name='your_database_name',\r\n table_name='your_table_name',\r\n username='your_username',\r\n password='your_password',\r\n host='your_host',\r\n port='your_port'\r\n)\r\n```\r\n### Loading Data from SQLite (Under Maintenance)\r\nTo load data from an SQLite database, use the sqlite method:\r\n\r\n```python\r\ndata = Load_data.Database.sqlite(\r\n db_name='your_database_name',\r\n table_name='your_table_name'\r\n)\r\n```\r\n### Generalized Syntax for Other Databases (Under Maintenance)\r\n\r\n```python \r\ndata = Load_data.Database.DataBase_Type(\r\n db_name='your_database_name',\r\n table_name='your_table_name',\r\n username='your_username',\r\n password='your_password',\r\n host='your_host',\r\n port='your_port'\r\n)\r\n```\r\n### Example\r\n```python\r\ndata = Load_data.Database.from_mysql(\r\n db_name='your_database_name',\r\n table_name='your_table_name',\r\n username='your_username',\r\n password='your_password',\r\n host='your_host',\r\n port='your_port'\r\n)\r\n```\r\n\r\n## 4. Extract Archives\r\n\r\n```python\r\nExtractor.extract_archive(\"path/to/your_archive.zip\", destination=\"path/to/extract\") destination: Optional\r\n```\r\n\r\n---\r\n\r\n\r\n## Contributing\r\n\r\nContributions are welcome! Feel free to submit a pull request or raise issues for any bugs or feature requests.\r\n\r\n---\r\n\r\n## License\r\n\r\nThis project is licensed under the MIT License.\r\nSee the LICENSE file for more details.\r\n\r\n---\r\n\r\n## Author\r\n\r\n**Name:** Moanl Bhiwgade \r\n**Email:** 3051monal@gmail.com\r\n",
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