Merge pull request #8 from isabelizimm/write-docker-file

Write docker file

Author: isabelizimm

examples/coffeeratings.py

@@ -0,0 +1,46 @@
+import pandas as pd
+from sklearn import model_selection
+from sklearn.linear_model import LinearRegression
+import vetiver
+from vetiver.pin_read_write import vetiver_pin_write
+from pathlib import Path
+
+# Load training data
+raw = pd.read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-07-07/coffee_ratings.csv')
+df = pd.DataFrame(raw)
+coffee = df[["total_cup_points", "aroma", "flavor", "sweetness", "acidity", \
+    "body", "uniformity", "balance"]].dropna()
+
+X_train, X_test, y_train, y_test = model_selection.train_test_split(coffee.iloc[:,1:],coffee['total_cup_points'],test_size=0.2)
+
+# fit model
+lr_fit = LinearRegression().fit(X_train, y_train)
+
+# create vetiver model
+v = vetiver.VetiverModel(lr_fit, save_ptype = True, ptype_data=X_train, model_name = "v")
+
+# version model via pin
+from pins import board_folder
+
+path = "./examples/coffeeratings/"
+
+model_board = board_folder(path=path, versioned=True, allow_pickle_read=True)
+vetiver_pin_write(board=model_board, model=v)
+
+myapp = vetiver.VetiverAPI(v, check_ptype = True)
+api = myapp.app
+
+# next, run myapp.run() to start API and see visual documentation
+# create app.py file that includes pinned VetiverAPI to be deployed
+vetiver.vetiver_write_app(model_board, "v", file = path+"app.py")
+
+# automatically create requirements.txt
+vetiver.load_pkgs(model=v, path=path)
+
+# write Dockerfile
+vetiver.vetiver_write_docker(path=path, host="0.0.0.0", port="80")
+
+## to run Dockerfile, in CLI
+# cd ./coffeeratings
+# docker build -t myimage .
+# docker run -d --name mycontainer -p 80:80 myimage

examples/coffeeratings/Dockerfile

@@ -0,0 +1,18 @@
+# # Generated by the vetiver package; edit with care
+#
+FROM python:3.8
+
+#
+WORKDIR /code
+
+#
+COPY vetiver_requirements.txt /code/requirements.txt
+
+#
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+# edited to copy all information into Dockerfile
+COPY . /code/app
+
+#
+CMD ["uvicorn", "app.app:api", "--host", "0.0.0.0", "--port", "80"]

examples/coffeeratings/app.py

@@ -0,0 +1,9 @@
+import vetiver
+import pins
+
+# edited to reflect Docker container path, and allow_pickle_read=True
+b = pins.board_folder('/code/app', allow_pickle_read=True)
+v = vetiver.vetiver_pin_read(b, 'v', version = '20220415T174503Z-06d9b')
+
+vetiver_api = vetiver.VetiverAPI(v)
+api = vetiver_api.app

examples/coffeeratings/v/20220415T174503Z-06d9b/data.txt

@@ -0,0 +1,15 @@
+api_version: 1
+created: 20220415T174503Z
+description: Scikit-learn model of type <class 'sklearn.linear_model._base.LinearRegression'>
+file: v.joblib
+file_size: 1035
+pin_hash: 06d9b5c677c7dcd0
+title: 'v: a pinned LinearRegression object'
+type: joblib
+user:
+  ptype: '{"aroma": 7.5, "flavor": 7.67, "sweetness": 10.0, "acidity": 7.67, "body":
+    7.58, "uniformity": 10.0, "balance": 7.42}'
+  required_pkgs:
+  - vetiver
+  - scikit-learn
+  save_ptype: true

examples/coffeeratings/v/20220415T174503Z-06d9b/v.joblib

@@ -0,0 +1,75 @@
+#
+# This file is autogenerated by pip-compile with python 3.8
+# To update, run:
+#
+#    pip-compile --output-file=./examples/coffeeratings/vetiver_requirements.txt /var/folders/5w/dhznpltj14n3nxr4fybjj8_w0000gn/T/tmpwe9ooski.in
+#
+anyio==3.5.0
+    # via starlette
+asgiref==3.5.0
+    # via uvicorn
+certifi==2021.10.8
+    # via requests
+charset-normalizer==2.0.12
+    # via requests
+click==8.1.2
+    # via uvicorn
+fastapi==0.75.1
+    # via vetiver
+h11==0.13.0
+    # via uvicorn
+idna==3.3
+    # via
+    #   anyio
+    #   requests
+joblib==1.1.0
+    # via
+    #   scikit-learn
+    #   vetiver
+nest-asyncio==1.5.5
+    # via vetiver
+numpy==1.22.3
+    # via
+    #   pandas
+    #   scikit-learn
+    #   scipy
+    #   vetiver
+pandas==1.4.2
+    # via vetiver
+pydantic==1.9.0
+    # via
+    #   fastapi
+    #   vetiver
+python-dateutil==2.8.2
+    # via pandas
+pytz==2022.1
+    # via pandas
+requests==2.27.1
+    # via vetiver
+scikit-learn==1.0.2
+    # via
+    #   -r /var/folders/5w/dhznpltj14n3nxr4fybjj8_w0000gn/T/tmpwe9ooski.in
+    #   vetiver
+scipy==1.8.0
+    # via scikit-learn
+six==1.16.0
+    # via python-dateutil
+sniffio==1.2.0
+    # via anyio
+starlette==0.17.1
+    # via fastapi
+threadpoolctl==3.1.0
+    # via scikit-learn
+torch==1.11.0
+    # via vetiver
+typing-extensions==4.1.1
+    # via
+    #   pydantic
+    #   torch
+urllib3==1.26.9
+    # via requests
+uvicorn==0.17.6
+    # via vetiver
+
+# manually edited to reflect appropriate versions of packages currently being developed
+git+https://github.com/isabelizimm/vetiver-python.git@37dff15a63238b1e6c44788af70473f19c29d83e

examples/coffeeratings/vetiver_requirements.txt

@@ -166,3 +166,5 @@ uvicorn==0.17.6
     # via vetiver (setup.py)
 zipp==3.7.0
     # via importlib-metadata
+# manually added
+git+https://github.com/machow/pins-python.git

requirements/dev.txt

@@ -33,6 +33,7 @@ install_requires =
     nest-asyncio
     torch
     requests
+    pins @ git+https://github.com/machow/pins-python@f9391b5937b3a13b2a2c841855ca94ab281b2cef
 
 [options.extras_require]
 dev =

setup.cfg

@@ -4,7 +4,16 @@
 __author__ = "Isabel Zimmerman <isabel.zimmerman@rstudio.com>"
 __all__ = []
 
+import importlib
 from .ptype import *
 from .vetiver_model import *
 from .server import *
 from .mock import *
+from .pin_read_write import *
+from .attach_pkgs import *
+from .meta import *
+from .write_docker import *
+from .write_fastapi import * 
+from .handlers._interface import *
+from .handlers.sklearn_vt import *
+from .handlers.pytorch_vt import *

vetiver/__init__.py

@@ -0,0 +1,31 @@
+import tempfile
+import os
+from vetiver import VetiverModel
+
+def load_pkgs(model: VetiverModel = None, packages: list = None, path=""):
+    """Load packages necessary for predictions
+
+    Args
+    ----
+        model: VetiverModel
+            VetiverModel to extract packages from
+        packages: list
+            List of extra packages to include
+        path: str
+            Where to save output file
+    """
+
+    required_pkgs = ["vetiver"]
+    if packages:
+        required_pkgs = list(set(required_pkgs + packages))
+    if model.metadata.get("required_pkgs"):
+        required_pkgs = list(set(required_pkgs + model.metadata.get("required_pkgs")))
+
+
+    tmp = tempfile.NamedTemporaryFile(suffix='.in')
+
+    with open(tmp.name, 'a') as f:
+        for package in required_pkgs:
+            f.write(package + '\n')
+
+    os.system(f"pip-compile {f.name} --output-file={path}vetiver_requirements.txt")