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Update README with badges, centered logo, emojis, and download instructions
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‎.gitignore

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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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cover/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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db.sqlite3-journal
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# Flask stuff:
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instance/
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.webassets-cache
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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.pybuilder/
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target/
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# Jupyter Notebook
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.ipynb_checkpoints
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# IPython
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profile_default/
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ipython_config.py
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# pyenv
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# For a library or package, you might want to ignore these files since the code is
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# intended to run in multiple environments; otherwise, check them in:
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# .python-version
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# pipenv
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
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# having no cross-platform support, pipenv may install dependencies that don't work, or not
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# install all needed dependencies.
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#Pipfile.lock
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# poetry
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# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
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# This is especially recommended for binary packages to ensure reproducibility, and is more
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# commonly ignored for libraries.
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# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
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#poetry.lock
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# pdm
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# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
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#pdm.lock
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# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
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# in version control.
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# https://pdm.fming.dev/latest/usage/project/#working-with-version-control
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.pdm.toml
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.pdm-python
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.pdm-build/
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
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__pypackages__/
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# Celery stuff
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celerybeat-schedule
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celerybeat.pid
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*.sage.py
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ENV/
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venv.bak/
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# Spyder project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/
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# pytype static type analyzer
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.pytype/
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# Cython debug symbols
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cython_debug/
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# PyCharm
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# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
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# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
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# and can be added to the global gitignore or merged into this file. For a more nuclear
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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#.idea/

‎README.md

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# JsonDB Project
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<p align="center">
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<img src="./assets/logo.png" alt="Logo" height="128px">
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</p>
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<p align="center">
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<img src="https://img.shields.io/badge/python-%2314354C.svg?&style=for-the-badge&logo=python&logoColor=white"/>
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<img src="https://img.shields.io/badge/json-%23000000.svg?&style=for-the-badge&logo=json&logoColor=white"/>
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</p>
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The JsonDB Project provides a lightweight, file-based database system, designed to make data storage and retrieval simple and intuitive. Built in Python, it leverages the versatility of JSON for data manipulation, making it an ideal solution for small projects, prototypes, or for educational purposes where a full-scale database system isn't required.
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## Features
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## 🚀 Features
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- **Simple CRUD Operations**: Easily create, read, update, and delete records with straightforward Python methods.
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- **Lightweight and Portable**: No need for complex database setups. Your data is stored in a single JSON file.
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- **Flexible Data Models**: Store anything from simple key-value pairs to complex nested structures.
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- **Search Functionality**: Includes basic search capabilities to filter through data based on keys or patterns.
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- **Minimal Setup**: With just a few lines of code, integrate JsonDB into any Python project.
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## Getting Started
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## 🏁 Getting Started
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### Prerequisites
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- Python 3.6 or newer
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### Installation
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To use the JsonDB in your project, you simply need to include the `jsonDB.py` file in your project directory. There's no need to install any packages or run any setup scripts. Just make sure that `jsonDB.py` is in the same folder as the Python script where you intend to use the database.
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You can download the `jsonDB.py` file directly for your platform using the following commands:
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#### Windows
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**Option 1: Using PowerShell (no extra installations needed)**:
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Open PowerShell and run:
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```powershell
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Invoke-WebRequest -Uri https://raw.githubusercontent.com/DavyJonesCodes/json-db-python/master/jsonDB.py -OutFile jsonDB.py
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```
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**Option 2: Using `wget`**:
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If you have `wget` installed, you can use the following command in Command Prompt or PowerShell:
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```cmd
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wget -O jsonDB.py https://raw.githubusercontent.com/DavyJonesCodes/json-db-python/master/jsonDB.py
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```
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#### Linux and macOS
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Open your terminal and run:
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```bash
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wget -O jsonDB.py https://raw.githubusercontent.com/DavyJonesCodes/json-db-python/master/jsonDB.py
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```
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### Usage
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print(db.keys('user.*')) # Output: ['user1']
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```
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## Project Structure
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## 📁 Project Structure
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- `jsonDb.py`: The core database module, implementing CRUD operations and data storage in JSON format.
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- `main.py`: An example script demonstrating how to use the JsonDB for basic data management tasks.
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- `data.json`: A sample JSON file used by `main.py` to illustrate data storage and retrieval.
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## Contributing
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## 🤝 Contributing
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Contributions to the JsonDB Project are welcome! Whether it's reporting a bug, discussing potential improvements, or contributing code, we value your input.
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Please feel free to submit issues and pull requests.
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## 📜 License
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This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

‎assets/logo.png

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