# BurrowTS
The BurrowTS is a Python library that provides a simple and efficient time series database for storing and retrieving time-stamped values.
## Features
- Insert values into the time series database with an associated timestamp.
- Retrieve time series data for a given series name.
- Retrieve time series data for a given series name by timestamp range.
- Thread-safe operations using a lock.
- Data persistence using pickle.
## Installation
You can install the BurrowTS using pip:
```
pip install burrowts
```
## Usage
Here's an example of how to use the BurrowTS:
```python
from burrowts import BurrowTS
db = BurrowTS()
# Insert values
db.insert("cpu", 12.3)
db.insert("cpu", 14.9)
db.insert("mem", 20.4)
# Retrieve time series data
cpu_data = db.get_series("cpu")
print("CPU Data:", cpu_data)
```
## Data Persistence
The BurrowTS uses pickle for data persistence. The database data is stored in a pickle file specified by the `file_path` parameter. The data is automatically saved to the file after each insertion operation.
## Thread Safety
The BurrowTS ensures thread safety by using a lock. This allows for concurrent access from multiple threads while maintaining data integrity.
## Contributing
Contributions are welcome! If you have any ideas, suggestions, or bug reports, please open an issue or submit a pull request.
## License
This project is licensed under the [MIT License](LICENSE).
Raw data
{
"_id": null,
"home_page": "https://github.com/iunary/burrowts",
"name": "burrowts",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.8",
"maintainer_email": "",
"keywords": "timeseries,stime-stamped,timeseries store,time series,thread-safe",
"author": "Yusuf",
"author_email": "contact@yusuf.im",
"download_url": "https://files.pythonhosted.org/packages/94/80/d962450a038da6feb7882944e7f897e2a4f450b0268e91d0452e62ea7003/burrowts-0.0.1.tar.gz",
"platform": null,
"description": "# BurrowTS\n\nThe BurrowTS is a Python library that provides a simple and efficient time series database for storing and retrieving time-stamped values.\n\n## Features\n\n- Insert values into the time series database with an associated timestamp.\n- Retrieve time series data for a given series name.\n- Retrieve time series data for a given series name by timestamp range.\n- Thread-safe operations using a lock.\n- Data persistence using pickle.\n\n## Installation\n\nYou can install the BurrowTS using pip:\n\n```\npip install burrowts\n```\n\n## Usage\n\nHere's an example of how to use the BurrowTS:\n\n```python\nfrom burrowts import BurrowTS\n\ndb = BurrowTS()\n\n# Insert values\ndb.insert(\"cpu\", 12.3)\ndb.insert(\"cpu\", 14.9)\ndb.insert(\"mem\", 20.4)\n\n# Retrieve time series data\ncpu_data = db.get_series(\"cpu\")\nprint(\"CPU Data:\", cpu_data)\n```\n\n## Data Persistence\n\nThe BurrowTS uses pickle for data persistence. The database data is stored in a pickle file specified by the `file_path` parameter. The data is automatically saved to the file after each insertion operation.\n\n## Thread Safety\n\nThe BurrowTS ensures thread safety by using a lock. This allows for concurrent access from multiple threads while maintaining data integrity.\n\n## Contributing\n\nContributions are welcome! If you have any ideas, suggestions, or bug reports, please open an issue or submit a pull request.\n\n## License\n\nThis project is licensed under the [MIT License](LICENSE).\n\n",
"bugtrack_url": null,
"license": "MIT",
"summary": "Simple plug and play timeseries database for storing and retreiving time-stamped values",
"version": "0.0.1",
"project_urls": {
"Homepage": "https://github.com/iunary/burrowts"
},
"split_keywords": [
"timeseries",
"stime-stamped",
"timeseries store",
"time series",
"thread-safe"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "d12c93f372fc0a931667017873cd79af4cf562c89c6ee81911feb059df1291e6",
"md5": "b4ce5671a7043daff29e3c7ee1a9a737",
"sha256": "4889c9f55af7c3c3c19d4676efbce2bcd54b0775a99e742782527fc5d0729349"
},
"downloads": -1,
"filename": "burrowts-0.0.1-py3-none-any.whl",
"has_sig": false,
"md5_digest": "b4ce5671a7043daff29e3c7ee1a9a737",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.8",
"size": 5042,
"upload_time": "2023-05-25T12:10:13",
"upload_time_iso_8601": "2023-05-25T12:10:13.707883Z",
"url": "https://files.pythonhosted.org/packages/d1/2c/93f372fc0a931667017873cd79af4cf562c89c6ee81911feb059df1291e6/burrowts-0.0.1-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "9480d962450a038da6feb7882944e7f897e2a4f450b0268e91d0452e62ea7003",
"md5": "11df0a970d81b9625d2dd3ff30e29f83",
"sha256": "6bc9857daf883e4950f757e87eb08dcae74448b94901763b00a3f61a7422b32a"
},
"downloads": -1,
"filename": "burrowts-0.0.1.tar.gz",
"has_sig": false,
"md5_digest": "11df0a970d81b9625d2dd3ff30e29f83",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.8",
"size": 4381,
"upload_time": "2023-05-25T12:10:15",
"upload_time_iso_8601": "2023-05-25T12:10:15.590564Z",
"url": "https://files.pythonhosted.org/packages/94/80/d962450a038da6feb7882944e7f897e2a4f450b0268e91d0452e62ea7003/burrowts-0.0.1.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-05-25 12:10:15",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "iunary",
"github_project": "burrowts",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"tox": true,
"lcname": "burrowts"
}
JSON
