DS12 Unit 3 Sprint 3 - Lawrence Kimsey

.gitignore

@@ -102,3 +102,10 @@ venv.bak/
 
 # mypy
 .mypy_cache/
+
+# PyCharm project files
+.idea
+
+# Development database:
+*.db
+*.sqlite3

Pipfile

@@ -0,0 +1,19 @@
+[[source]]
+name = "pypi"
+url = "https://pypi.org/simple"
+verify_ssl = true
+
+[dev-packages]
+
+[packages]
+flask = "*"
+flask-sqlalchemy = "*"
+flask-migrate = "*"
+basilica = "*"
+python-dotenv = "*"
+requests = "*"
+tweepy = "*"
+scikit-learn = "*"
+
+[requires]
+python_version = "3.7"

migrations/README

@@ -0,0 +1 @@
+Generic single-database configuration.

migrations/alembic.ini

@@ -0,0 +1,45 @@
+# A generic, single database configuration.
+
+[alembic]
+# template used to generate migration files
+# file_template = %%(rev)s_%%(slug)s
+
+# set to 'true' to run the environment during
+# the 'revision' command, regardless of autogenerate
+# revision_environment = false
+
+
+# Logging configuration
+[loggers]
+keys = root,sqlalchemy,alembic
+
+[handlers]
+keys = console
+
+[formatters]
+keys = generic
+
+[logger_root]
+level = WARN
+handlers = console
+qualname =
+
+[logger_sqlalchemy]
+level = WARN
+handlers =
+qualname = sqlalchemy.engine
+
+[logger_alembic]
+level = INFO
+handlers =
+qualname = alembic
+
+[handler_console]
+class = StreamHandler
+args = (sys.stderr,)
+level = NOTSET
+formatter = generic
+
+[formatter_generic]
+format = %(levelname)-5.5s [%(name)s] %(message)s
+datefmt = %H:%M:%S

migrations/env.py

@@ -0,0 +1,96 @@
+from __future__ import with_statement
+
+import logging
+from logging.config import fileConfig
+
+from sqlalchemy import engine_from_config
+from sqlalchemy import pool
+
+from alembic import context
+
+# this is the Alembic Config object, which provides
+# access to the values within the .ini file in use.
+config = context.config
+
+# Interpret the config file for Python logging.
+# This line sets up loggers basically.
+fileConfig(config.config_file_name)
+logger = logging.getLogger('alembic.env')
+
+# add your model's MetaData object here
+# for 'autogenerate' support
+# from myapp import mymodel
+# target_metadata = mymodel.Base.metadata
+from flask import current_app
+config.set_main_option(
+    'sqlalchemy.url',
+    str(current_app.extensions['migrate'].db.engine.url).replace('%', '%%'))
+target_metadata = current_app.extensions['migrate'].db.metadata
+
+# other values from the config, defined by the needs of env.py,
+# can be acquired:
+# my_important_option = config.get_main_option("my_important_option")
+# ... etc.
+
+
+def run_migrations_offline():
+    """Run migrations in 'offline' mode.
+
+    This configures the context with just a URL
+    and not an Engine, though an Engine is acceptable
+    here as well.  By skipping the Engine creation
+    we don't even need a DBAPI to be available.
+
+    Calls to context.execute() here emit the given string to the
+    script output.
+
+    """
+    url = config.get_main_option("sqlalchemy.url")
+    context.configure(
+        url=url, target_metadata=target_metadata, literal_binds=True
+    )
+
+    with context.begin_transaction():
+        context.run_migrations()
+
+
+def run_migrations_online():
+    """Run migrations in 'online' mode.
+
+    In this scenario we need to create an Engine
+    and associate a connection with the context.
+
+    """
+
+    # this callback is used to prevent an auto-migration from being generated
+    # when there are no changes to the schema
+    # reference: http://alembic.zzzcomputing.com/en/latest/cookbook.html
+    def process_revision_directives(context, revision, directives):
+        if getattr(config.cmd_opts, 'autogenerate', False):
+            script = directives[0]
+            if script.upgrade_ops.is_empty():
+                directives[:] = []
+                logger.info('No changes in schema detected.')
+
+    connectable = engine_from_config(
+        config.get_section(config.config_ini_section),
+        prefix='sqlalchemy.',
+        poolclass=pool.NullPool,
+    )
+
+    with connectable.connect() as connection:
+        context.configure(
+            connection=connection,
+            target_metadata=target_metadata,
+            process_revision_directives=process_revision_directives,
+            **current_app.extensions['migrate'].configure_args
+        )
+
+        with context.begin_transaction():
+            context.run_migrations()
+
+
+if context.is_offline_mode():
+    run_migrations_offline()
+else:
+    run_migrations_online()

migrations/script.py.mako

@@ -0,0 +1,24 @@
+"""${message}
+
+Revision ID: ${up_revision}
+Revises: ${down_revision | comma,n}
+Create Date: ${create_date}
+
+"""
+from alembic import op
+import sqlalchemy as sa
+${imports if imports else ""}
+
+# revision identifiers, used by Alembic.
+revision = ${repr(up_revision)}
+down_revision = ${repr(down_revision)}
+branch_labels = ${repr(branch_labels)}
+depends_on = ${repr(depends_on)}
+
+
+def upgrade():
+    ${upgrades if upgrades else "pass"}
+
+
+def downgrade():
+    ${downgrades if downgrades else "pass"}

migrations/versions/505cb269b18c_.py

@@ -0,0 +1,45 @@
+"""empty message
+
+Revision ID: 505cb269b18c
+Revises: 
+Create Date: 2020-03-26 16:16:14.208086
+
+"""
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision = '505cb269b18c'
+down_revision = None
+branch_labels = None
+depends_on = None
+
+
+def upgrade():
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.create_table('user',
+    sa.Column('id', sa.BigInteger(), nullable=False),
+    sa.Column('screen_name', sa.String(length=128), nullable=False),
+    sa.Column('name', sa.String(), nullable=True),
+    sa.Column('location', sa.String(), nullable=True),
+    sa.Column('followers_count', sa.Integer(), nullable=True),
+    sa.Column('latest_tweet_id', sa.BigInteger(), nullable=True),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_table('tweet',
+    sa.Column('id', sa.BigInteger(), nullable=False),
+    sa.Column('user_id', sa.BigInteger(), nullable=True),
+    sa.Column('full_text', sa.String(length=500), nullable=True),
+    sa.Column('embedding', sa.PickleType(), nullable=True),
+    sa.ForeignKeyConstraint(['user_id'], ['user.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    # ### end Alembic commands ###
+
+
+def downgrade():
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_table('tweet')
+    op.drop_table('user')
+    # ### end Alembic commands ###

notes.txt

@@ -0,0 +1,7 @@
+Flask commands:
+
+set FLASK_APP=web_app
+flask db init
+flask db migrate
+flask db upgrade
+flask run

web_app/__init__.py

@@ -0,0 +1,32 @@
+# web_app/__init__.py
+
+from flask import Flask
+
+from web_app.models import db, migrate
+from web_app.routes.home_routes import home_routes
+from web_app.routes.book_routes import book_routes
+from web_app.routes.twitter_routes import twitter_routes
+from web_app.routes.admin_routes import admin_routes
+from web_app.routes.stats_routes import stats_routes
+
+
+def create_app():
+    app = Flask(__name__)
+
+    app.config["SQLALCHEMY_DATABASE_URI"] = "sqlite:///web_app_12.db"
+
+    db.init_app(app)
+    migrate.init_app(app, db)
+
+    app.register_blueprint(home_routes)
+    app.register_blueprint(book_routes)
+    app.register_blueprint(twitter_routes)
+    app.register_blueprint(admin_routes)
+    app.register_blueprint(stats_routes)
+
+    return app
+
+
+if __name__ == "__main__":
+    my_app = create_app()
+    my_app.run(debug=True)

web_app/iris_classifier.py

@@ -0,0 +1,43 @@
+# web_app/iris_classifier.py
+
+import os
+import pickle
+
+from sklearn.datasets import load_iris
+from sklearn.linear_model import LogisticRegression
+
+MODEL_FILEPATH = os.path.join(os.path.dirname(__file__), "..", "statmodels", "latest_model.pkl")
+
+
+def train_and_save_model():
+    print("TRAINING THE MODEL...")
+    X, y = load_iris(return_X_y=True)
+    classifier = LogisticRegression()  # for example
+    classifier.fit(X, y)
+
+    print("SAVING THE MODEL...")
+    with open(MODEL_FILEPATH, "wb") as model_file:
+        pickle.dump(classifier, model_file)
+
+    return classifier
+
+
+def load_model():
+    print("LOADING THE MODEL...")
+    with open(MODEL_FILEPATH, "rb") as model_file:
+        saved_model = pickle.load(model_file)
+    return saved_model
+
+
+if __name__ == "__main__":
+    train_and_save_model()
+
+    clf = load_model()
+    print("CLASSIFIER:", clf)
+
+    X, y = load_iris(return_X_y=True)  # just to have some data to use when predicting
+    inputs = X[:2, :]
+    print(type(inputs), inputs)
+
+    result = clf.predict(inputs)
+    print("RESULT:", result)

web_app/models.py

@@ -0,0 +1,56 @@
+# web_app/models.py
+
+from flask_sqlalchemy import SQLAlchemy
+from flask_migrate import Migrate
+
+db = SQLAlchemy()
+
+migrate = Migrate()
+
+
+class Book(db.Model):
+    id = db.Column(db.Integer, primary_key=True)
+    title = db.Column(db.String(128))
+    author_id = db.Column(db.String(128))
+
+
+class User(db.Model):
+    id = db.Column(db.BigInteger, primary_key=True)
+    screen_name = db.Column(db.String(128), nullable=False)
+    name = db.Column(db.String)
+    location = db.Column(db.String)
+    followers_count = db.Column(db.Integer)
+    latest_tweet_id = db.Column(db.BigInteger)
+
+
+class Tweet(db.Model):
+    id = db.Column(db.BigInteger, primary_key=True)
+    user_id = db.Column(db.BigInteger, db.ForeignKey("user.id"))
+    full_text = db.Column(db.String(500))
+    embedding = db.Column(db.PickleType)
+
+    user = db.relationship("User", backref=db.backref("tweets", lazy=True))
+
+
+def parse_records(database_records):
+    """
+    A helper method for converting a list of database record objects into a list of dictionaries, so they can be returned as JSON
+
+    Param: database_records (a list of db.Model instances)
+
+    Example: parse_records(User.query.all())
+
+    Returns: a list of dictionaries, each corresponding to a record, like...
+        [
+            {"id": 1, "title": "Book 1"},
+            {"id": 2, "title": "Book 2"},
+            {"id": 3, "title": "Book 3"},
+        ]
+    """
+    parsed_records = []
+    for record in database_records:
+        print(record)
+        parsed_record = record.__dict__
+        del parsed_record["_sa_instance_state"]
+        parsed_records.append(parsed_record)
+    return parsed_records