Python is dynamically typed and non-compiled language. Python requires that the environment you run in has an appropriate Python interpreter and the ability to install the libraries and packages you need.
https://github.com/erkansirin78/fastapi-advertising-prediction.git
conda activate fastapi
pip install -r requirements
[metadata]
name = fastapi_advertising_prediction
version = 0.0.1
author = Erkan SIRIN
author_email = erkansirin.datalonga@gmail.com
description = ML model deployment of Advertising dataset.
long_description = file: README.md
long_description_content_type = text/markdown
url = https://github.com/erkansirin78/fastapi-advertising-prediction
classifiers =
Programming Language :: Python :: 3
License :: OSI Approved :: MIT License
Operating System :: OS Independent
[options]
packages = find:
python_requires = >=3.7
include_package_data = True
- If you update, change version.
[build-system]
requires = [
"setuptools>=54",
"wheel"
]
build-backend = "setuptools.build_meta"
- Wheels are a component of the Python ecosystem that helps to make package installs just work. They allow for faster installations and more stability in the package distribution process.
- https://realpython.com/python-wheels/#what-is-a-python-wheel
- Create LICENCE file
- Visit https://choosealicense.com/ and pick-up that suits your need.
python -m build
- Build will create new files
.
├── dist
│ ├── fastapi_advertising_prediction-0.0.1-py3-none-any.whl
│ └── fastapi_advertising_prediction-0.0.1.tar.gz
├── fastapi_advertising_prediction
│ ├── Dockerfile
│ ├── __init__.py
│ ├── main.py
│ ├── __pycache__
│ │ ├── __init__.cpython-38.pyc
│ │ ├── main.cpython-38.pyc
│ │ ├── schemas.cpython-38.pyc
│ │ └── train.cpython-38.pyc
│ ├── requirements.txt
│ ├── saved_models
│ │ └── 03.randomforest_with_advertising.pkl
│ ├── schemas.py
│ └── train.py
├── fastapi_advertising_prediction.egg-info
│ ├── dependency_links.txt
│ ├── PKG-INFO
│ ├── SOURCES.txt
│ └── top_level.txt
├── LICENSE
├── pyproject.toml
├── README.md
└── setup.cfg
5 directories, 21 files
- Check dist folder
tree dist/
dist/
├── fastapi_advertising_prediction-0.0.1-py3-none-any.whl
└── fastapi_advertising_prediction-0.0.1.tar.gz
- Before sending packages to pypi, first we upload test.pypi to see everything is all right.
twine upload --repository testpypi --skip-existing dist/* --verbose
- Expected output
Uploading distributions to https://test.pypi.org/legacy/
INFO dist/fastapi_advertising_prediction-0.0.1-py3-none-any.whl (4.6 KB)
INFO dist/fastapi_advertising_prediction-0.0.1.tar.gz (3.3 KB)
INFO Querying keyring for username
Enter your username: erkansirin
INFO Querying keyring for password
WARNING No recommended backend was available. Install a recommended 3rd party backend
package; or, install the keyrings.alt package if you want to use the
non-recommended backends. See https://pypi.org/project/keyring for details.
Enter your password:
INFO username: erkansirin
INFO password: <hidden>
Uploading fastapi_advertising_prediction-0.0.1-py3-none-any.whl
100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 8.9/8.9 kB • 00:00 • 1.6 MB/s
INFO Response from https://test.pypi.org/legacy/:
200 OK
Uploading fastapi_advertising_prediction-0.0.1.tar.gz
100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 7.6/7.6 kB • 00:00 • ?
INFO Response from https://test.pypi.org/legacy/:
200 OK
View at:
https://test.pypi.org/project/fastapi-advertising-prediction/0.0.1/
pip install -i https://test.pypi.org/simple/ fastapi-advertising-prediction==0.0.1
- Ignore following error and try again.
ERROR: No matching distribution found for fastapi-advertising-prediction==0.0.1
- Create test directory
mkdir /tmp/fasttest
cd /tmp/fasttest
- Create a module for training and saving model.
cat <<EOF > train_run.py
from fastapi_advertising_prediction import train
if __name__=='__main__':
train.read_and_train()
EOF
-
Run:
python train_run.py -
Expected output
ID TV Radio Newspaper Sales
0 1 230.1 37.8 69.2 22.1
1 2 44.5 39.3 45.1 10.4
2 3 17.2 45.9 69.3 9.3
3 4 151.5 41.3 58.5 18.5
4 5 180.8 10.8 58.4 12.9
(200, 3)
[[230.1 37.8 69.2]
[ 44.5 39.3 45.1]
[ 17.2 45.9 69.3]]
(200,)
0 22.1
1 10.4
2 9.3
3 18.5
4 12.9
5 7.2
Name: Sales, dtype: float64
R2: 0.9825966330409427
current_dir: /home/train/miniconda3/envs/fastapi/lib/python3.8/site-packages/fastapi_advertising_prediction
FileExistsError: File exists.
/home/train/miniconda3/envs/fastapi/lib/python3.8/site-packages/fastapi_advertising_prediction/saved_models
X_manual_test [[230.1, 37.8, 69.2]]
prediction [21.986]
- create a module
cat<<EOF > main.py
from fastapi_advertising_prediction import main
import uvicorn
app = main.app
if __name__ == "__main__":
uvicorn.run("main:app", host="0.0.0.0", port=8000, reload=True,
log_level="debug", debug=True,
workers=4, limit_concurrency=10, limit_max_requests=10)
EOF
-
Run:
python main.py -
Open browser: http://localhost:8000/docs
-
Test API
# Uninstall
pip uninstall fastapi-advertising-prediction
# Delete all files in the dist folder.
rm -rf dist/
# Update the version number in the setup.cfg file.
# Re-create the wheels:
python -m build
# Re-upload the new files:
twine upload --repository testpypi dist/* --verbose
pip install -i https://test.pypi.org/simple/ fastapi-advertising-prediction==0.0.2
twine upload --repository pypi dist/* --verbose