# Framework3
Framework3 is an innovative platform designed to simplify and accelerate the development of machine learning models. It provides data scientists and machine learning engineers with a flexible and powerful tool to create, experiment with, and deploy models efficiently and in a structured manner. [https://manucouto1.github.io/framework3](https://manucouto1.github.io/framework3)
## Key Features
- Modular and flexible architecture
- Customizable pipelines for ML workflows
- Extensible plugin system for filters, metrics, and storage
- Support for distributed processing with MapReduce
- Integrated model evaluation and optimization tools
## Prerequisites
Before installing Framework3, ensure you have the following prerequisites:
1. Python 3.11 or higher
2. pip (Python package installer)
## Installation Options
You have two options to install Framework3:
### Option 1: Install from PyPI
The easiest way to install Framework3 is directly from PyPI using pip:
```bash
pip install framework3
```
This will install the latest stable version of Framework3 and its dependencies.
### Option 2: Install from Source
2. Clone the repository:
```
git clone https://github.com/manucouto1/framework3.git
```
3. Navigate to the project directory:
```
cd framework3
```
4. Install the dependencies using pip:
```
pip install -r requirements.txt
```
## Basic Usage
Here's a basic example of how to use Framework3:
```python
from framework3.plugins.pipelines import F3Pipeline
from framework3.plugins.filters.classification import KnnFilter
from framework3.plugins.metrics import F1, Precision, Recall
# Create a pipeline
pipeline = F3Pipeline(
plugins=[KnnFilter()],
metrics=[F1(), Precision(), Recall()]
)
# Fit the model
pipeline.fit(X_train, y_train)
# Make predictions
predictions = pipeline.predict(X_test)
# Evaluate the model
evaluation = pipeline.evaluate(X_test, y_test, y_pred=predictions)
print(evaluation)
```
## Documentation
For more detailed information on how to use Framework3, check out our complete documentation at:
[https://manucouto1.github.io/framework3](https://manucouto1.github.io/framework3)
## Contributing
Contributions are welcome. Please read our contribution guidelines before submitting pull requests.
## License
This project is licensed under the AGPL-3.0 license. See the `LICENSE` file for more details.
## Contact
If you have any questions or suggestions, don't hesitate to open an issue in this repository or contact the development team.
---
Thank you for your interest in Framework3! We hope this tool will be useful in your machine learning projects.
Raw data
{
"_id": null,
"home_page": null,
"name": "framework3",
"maintainer": null,
"docs_url": null,
"requires_python": "<4.0,>=3.11",
"maintainer_email": null,
"keywords": "machine learning, framework, pipeline, ML, AI, data science",
"author": "Manuel Couto Pintos",
"author_email": "manuel.couto.pintos@usc.es",
"download_url": "https://files.pythonhosted.org/packages/ab/f1/c433c210ee2f16b7e4b5482ceff14bff41b9bcd08990896e4e63ac68c74d/framework3-1.0.7.tar.gz",
"platform": null,
"description": "# Framework3\n\nFramework3 is an innovative platform designed to simplify and accelerate the development of machine learning models. It provides data scientists and machine learning engineers with a flexible and powerful tool to create, experiment with, and deploy models efficiently and in a structured manner. [https://manucouto1.github.io/framework3](https://manucouto1.github.io/framework3)\n\n## Key Features\n\n- Modular and flexible architecture\n- Customizable pipelines for ML workflows\n- Extensible plugin system for filters, metrics, and storage\n- Support for distributed processing with MapReduce\n- Integrated model evaluation and optimization tools\n\n## Prerequisites\n\nBefore installing Framework3, ensure you have the following prerequisites:\n\n1. Python 3.11 or higher\n2. pip (Python package installer)\n\n## Installation Options\n\nYou have two options to install Framework3:\n\n### Option 1: Install from PyPI\n\nThe easiest way to install Framework3 is directly from PyPI using pip:\n\n```bash\npip install framework3\n```\n\nThis will install the latest stable version of Framework3 and its dependencies.\n\n### Option 2: Install from Source\n\n2. Clone the repository:\n ```\n git clone https://github.com/manucouto1/framework3.git\n ```\n\n3. Navigate to the project directory:\n ```\n cd framework3\n ```\n\n4. Install the dependencies using pip:\n ```\n pip install -r requirements.txt\n ```\n\n## Basic Usage\n\nHere's a basic example of how to use Framework3:\n\n```python\nfrom framework3.plugins.pipelines import F3Pipeline\nfrom framework3.plugins.filters.classification import KnnFilter\nfrom framework3.plugins.metrics import F1, Precision, Recall\n\n# Create a pipeline\npipeline = F3Pipeline(\n plugins=[KnnFilter()],\n metrics=[F1(), Precision(), Recall()]\n)\n\n# Fit the model\npipeline.fit(X_train, y_train)\n\n# Make predictions\npredictions = pipeline.predict(X_test)\n\n# Evaluate the model\nevaluation = pipeline.evaluate(X_test, y_test, y_pred=predictions)\nprint(evaluation)\n```\n\n## Documentation\n\nFor more detailed information on how to use Framework3, check out our complete documentation at:\n\n[https://manucouto1.github.io/framework3](https://manucouto1.github.io/framework3)\n\n## Contributing\n\nContributions are welcome. Please read our contribution guidelines before submitting pull requests.\n\n## License\n\nThis project is licensed under the AGPL-3.0 license. See the `LICENSE` file for more details.\n\n## Contact\n\nIf you have any questions or suggestions, don't hesitate to open an issue in this repository or contact the development team.\n\n---\n\nThank you for your interest in Framework3! We hope this tool will be useful in your machine learning projects.\n",
"bugtrack_url": null,
"license": "AGPL-3.0-or-later",
"summary": "A flexible framework for machine learning pipelines",
"version": "1.0.7",
"project_urls": {
"Documentation": "https://manucouto1.github.io/framework3/",
"Homepage": "https://github.com/manucouto1/framework3",
"Repository": "https://github.com/manucouto1/framework3.git"
},
"split_keywords": [
"machine learning",
" framework",
" pipeline",
" ml",
" ai",
" data science"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "7daa3bb1f16d16a9f294e99a1661074ac2bc1d820626a99f61dfa4fd5474b414",
"md5": "0449b2f35dfa60d571644ea2d9598e33",
"sha256": "e7c9aceca3a7186210c0bfed7b9d11df9b4de09b2f1654310bc2c6e690d52622"
},
"downloads": -1,
"filename": "framework3-1.0.7-py3-none-any.whl",
"has_sig": false,
"md5_digest": "0449b2f35dfa60d571644ea2d9598e33",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": "<4.0,>=3.11",
"size": 71585,
"upload_time": "2024-12-07T08:48:17",
"upload_time_iso_8601": "2024-12-07T08:48:17.260277Z",
"url": "https://files.pythonhosted.org/packages/7d/aa/3bb1f16d16a9f294e99a1661074ac2bc1d820626a99f61dfa4fd5474b414/framework3-1.0.7-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "abf1c433c210ee2f16b7e4b5482ceff14bff41b9bcd08990896e4e63ac68c74d",
"md5": "565c85181595e08e9778a781d473a713",
"sha256": "5dc0345dcffff5ed9ab39936044ff7bfc5d8695b3d65420b2d6958ea0788f33b"
},
"downloads": -1,
"filename": "framework3-1.0.7.tar.gz",
"has_sig": false,
"md5_digest": "565c85181595e08e9778a781d473a713",
"packagetype": "sdist",
"python_version": "source",
"requires_python": "<4.0,>=3.11",
"size": 51358,
"upload_time": "2024-12-07T08:48:18",
"upload_time_iso_8601": "2024-12-07T08:48:18.902539Z",
"url": "https://files.pythonhosted.org/packages/ab/f1/c433c210ee2f16b7e4b5482ceff14bff41b9bcd08990896e4e63ac68c74d/framework3-1.0.7.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-12-07 08:48:18",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "manucouto1",
"github_project": "framework3",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"requirements": [
{
"name": "typeguard",
"specs": [
[
"==",
"4.4.1"
]
]
},
{
"name": "multimethod",
"specs": [
[
"==",
"1.12"
]
]
},
{
"name": "pyspark",
"specs": [
[
"==",
"3.5.3"
]
]
},
{
"name": "fastapi",
"specs": [
[
"==",
"0.115.5"
]
]
},
{
"name": "pandas",
"specs": [
[
"==",
"2.2.3"
]
]
},
{
"name": "torch",
"specs": [
[
"==",
"2.5.1"
]
]
},
{
"name": "scipy",
"specs": [
[
"==",
"1.13.1"
]
]
},
{
"name": "rich",
"specs": [
[
"==",
"13.9.4"
]
]
},
{
"name": "boto3",
"specs": [
[
"==",
"1.35.73"
]
]
},
{
"name": "scikit-learn",
"specs": [
[
"==",
"1.5.2"
]
]
},
{
"name": "cloudpickle",
"specs": [
[
"==",
"3.1.0"
]
]
},
{
"name": "tqdm",
"specs": [
[
"==",
"4.67.1"
]
]
},
{
"name": "nltk",
"specs": [
[
"==",
"3.9.1"
]
]
},
{
"name": "transformers",
"specs": [
[
"==",
"4.46.3"
]
]
},
{
"name": "gensim",
"specs": [
[
"==",
"4.3.3"
]
]
},
{
"name": "wandb",
"specs": [
[
"==",
"0.18.7"
]
]
}
],
"lcname": "framework3"
}
JSON
