brian/visual_critical_discourse_analysis
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docker_webserver #2

Merged
brian merged 3 commits from docker_webserver into main 2024-02-15 22:45:41 +01:00
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Dockerfile
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###########
# BUILDER #
###########
# pull official base image
FROM python:3.12-slim-bullseye as BUILDER
# set environment variables
ENV PYTHONUNBUFFERED=1 \
PYTHONDONTWRITEBYTECODE=1 \
PIP_NO_CACHE_DIR=off \
PIP_DISABLE_PIP_VERSION_CHECK=ON \
PIP_DEFAULT_TIMEOUT=100 \
DEBIAN_FRONTEND=noninteractive \
POETRY_HOME=/etc/poetry \
POETRY_VERSION=1.7.1 \
POETRY_VIRTUALENVS_IN_PROJECT=1 \
POETRY_VIRTUALENVS_CREATE=1 \
POETRY_NO_INTERACTION=1 \
POETRY_CACHE_DIR=/tmp/poetry_cache \
APP_HOME=/home/app
# update system
RUN apt-get update \
&& apt-get install -y --no-install-recommends \
build-essential \
curl \
&& apt-get clean
# install poetry
RUN curl -sSL https://install.python-poetry.org | python3 -
ENV PATH="${POETRY_HOME}/bin:$PATH"
# install runtime dependencies
WORKDIR ${APP_HOME}
COPY poetry.lock pyproject.toml ./
RUN --mount=type=cache,target=${POETRY_CACHE_DIR} poetry install --no-root
#########
# FINAL #
#########
# pull official base image
FROM python:3.12-slim-bullseye
# copy virtualenv made by poetry
ENV APP_HOME=/home/app \
VIRTUAL_ENV=/home/app/.venv
COPY --from=builder ${VIRTUAL_ENV} ${VIRTUAL_ENV}
ENV PATH="${VIRTUAL_ENV}/bin:${PATH}"
# create home directory and app user
RUN mkdir -p /home/app && \
addgroup --system app && \
adduser --system --group app
# add code while changing ownership
WORKDIR $APP_HOME
COPY --chown=app:app ./src .
# change to the app user
USER app
ENTRYPOINT [ "gunicorn", "web:server", "-b", "0.0.0.0:8050" ]
docker-compose.local.yml
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services:
app:
image: visual_critical_discourse_analysis:dev
container_name: visual_critical_discourse_analysis
build:
context: .
dockerfile: Dockerfile
ports:
- 8050:8050
networks:
- backend
networks:
backend:
external: false
poetry.lock
Generated
+636
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# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
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version = "1.7.0"
description = "Fast, simple object-to-object and broadcast signaling"
optional = false
python-versions = ">=3.8"
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]
[[package]]
name = "certifi"
version = "2024.2.2"
description = "Python package for providing Mozilla's CA Bundle."
optional = false
python-versions = ">=3.6"
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version = "3.3.2"
description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
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[metadata]
lock-version = "2.0"
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content-hash = "b80bd2598b5e94ab048aff2a8615067d938b520c5e4e131547e4cbc1a8f664d5"
pyproject.toml
+20
View File
@@ -0,0 +1,20 @@
[tool.poetry]
name = "visual-critical-discourse-analysis"
version = "0.1.0"
description = ""
authors = ["Brian Bjarke Jensen <[email protected]>"]
readme = "README.md"
[tool.poetry.dependencies]
python = "^3.12"
gunicorn = "^21.2.0"
python-logging-discord-handler = "^0.1.4"
python-dotenv = "^1.0.1"
dash = "^2.15.0"
dash-bootstrap-components = "^1.5.0"
dash-mantine-components = "^0.12.1"
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"
src/defaults.ini
+6
View File
@@ -0,0 +1,6 @@
[main]
logger_level=debug
[discord]
service_name=visual_critical_discourse_analysis
logger_level=warning
src/main.py
+98
View File
@@ -0,0 +1,98 @@
import logging
from discord_logging.handler import DiscordHandler
from dotenv import load_dotenv
from configparser import ConfigParser
from pathlib import Path
import logging
import os
from web import app
# load default values
config = ConfigParser()
config.read(Path(__file__).parent / 'defaults.ini')
LOGGER_LEVEL = config.get('main', 'logger_level')
DISCORD_SERVICE_NAME = config.get('discord', 'service_name')
DISCORD_LOGGER_LEVEL = config.get('discord', 'logger_level')
def setup_logging(
discord_webhook_url: str,
discord_service_name: str = DISCORD_SERVICE_NAME,
discord_logger_level: str = DISCORD_LOGGER_LEVEL,
logger_level: str = LOGGER_LEVEL,
) -> None:
# setup stream handler
fmt = (
'%(asctime)s | '
'%(levelname)s | '
'%(filename)s | '
'%(funcName)s | '
'%(message)s'
)
datefmt = '%Y-%m-%d %H:%M:%S'
level = getattr(logging, logger_level.upper())
logging.basicConfig(format=fmt, datefmt=datefmt, level=level)
logger = logging.getLogger()
# add discord handler
discord_handler = DiscordHandler(
service_name=discord_service_name,
webhook_url=discord_webhook_url,
)
discord_handler.setFormatter(logging.Formatter('%(message)s'))
level = getattr(logging, discord_logger_level.upper())
discord_handler.setLevel(level=level)
logger.addHandler(discord_handler)
logging.debug('finished')
def initialise_app() -> None:
"""
Ensure all necessary environment variables are provided
"""
# load env vars
load_dotenv()
# ensure env vars set
necesasary_var_map = {
'LOGGER_LEVEL': False,
'DISCORD_SERVICE_NAME': False,
'DISCORD_WEBHOOK_URL': True,
'DISCORD_LOGGER_LEVEL': False,
'DATABASE_HOST': True,
'DATABASE_PORT': True,
'DATABASE_ENGINE': True,
'DATABASE_DATABASE': True,
'DATABASE_USERNAME': True,
'DATABASE_PASSWORD': True,
}
for env_var, must_be_set in necesasary_var_map.items():
if must_be_set:
# ensure env var set
assert (
env_var in os.environ
), (
f"environment variable not set: {env_var}"
)
# set variable from env var
locals()[env_var.lower()] = os.getenv(key=env_var)
else:
# ensure default value set
assert env_var in globals(), f"default variable not set: {env_var}"
# set variable from env var with backup from default value
locals()[env_var.lower()] = os.getenv(
key=env_var,
default=globals()[env_var]
)
setup_logging(
discord_webhook_url=locals()['discord_webhook_url'],
discord_service_name=locals()['discord_service_name'],
discord_logger_level=locals()['discord_logger_level'],
logger_level=locals()['logger_level'],
)
logging.debug('finished')
if __name__ == "__main__":
# initialise_app()
app.run(debug=True)
logging.info("started app")
src/model_experiential/__init__.py
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from .output import model_labels
src/model_experiential/output.py
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model_labels = [
"non transactional action",
"non transactional reaction",
"unidirectional transactional action",
"unidirectional transactional reaction",
"bidirectional transactional action",
"bidirectional transactional reaction",
"conversion",
"speech process",
"classification overt taxonomy",
"analytical exhaustive",
"analytical disarranged",
"analytical temporal",
"analytical distributed",
"anaytical topological",
"analytical exploded",
"analytical inclusive",
"symbolic suggestive",
"symbolic attributive"
]
src/model_interpersonal/__init__.py
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from .output import model_labels
src/model_interpersonal/output.py
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model_labels = {
"contact": [
"contact offer",
"contact demand"
],
"angle": [
"high",
"eye-level",
"low"
],
"point-of-view": [
"frontal",
"oblique"
],
"distance": [
"long",
"medium",
"close"
],
"modality lighting": [
"high",
"medium",
"low"
],
"modality color": [
"high",
"medium",
"low"
],
"modality depth": [
"high",
"medium",
"low"
]
}
src/model_textual/__init__.py
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from .output import model_labels
src/model_textual/output.py
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model_labels = {
"information value": [
"given-new",
"ideal-real",
"central-marginal"
],
"framing": [
"frame lines",
"empty space",
"colour contrast",
"form contrast"
],
"salience": [
"size",
"colour",
"tone",
"form",
"positioning"
]
}
src/web/__init__.py
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from .app import (
app,
server
)
src/web/app.py
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from dash import Dash, html, Input, Output, State, page_container, page_registry
import dash_bootstrap_components as dbc
import dash_mantine_components as dmc
from .header import generate_header
from .body import generate_body
from model_experiential import model_labels as experiential_labels
from model_interpersonal import model_labels as interpersonal_labels
from model_textual import model_labels as textual_labels
app = Dash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP])
server = app.server
app.layout = dmc.MantineProvider(
theme={
'fontFamily': '"Inter", sans-serif',
"components": {
"NavLink":{'styles':{'label':{'color':'#c2c7d0'}}}
},
},
children=[
dmc.Container([
generate_header(),
generate_body(
experiential_labels,
interpersonal_labels,
textual_labels
),
]),
],
)
src/web/body.py
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import dash_mantine_components as dmc
from dash import dcc, html
def generate_body(
experiential_labels,
interpersonal_labels,
textual_labels
):
image_container = dmc.Image(
width=400,
height=400,
withPlaceholder=True,
placeholder=[dmc.Loader(color="gray", size="md")],
)
experiential_labels_container = dmc.Container(
children=[
html.H4("experiential labels".title()),
dcc.RadioItems(options=list(experiential_labels)),
]
)
interpersonal_labels_container = dmc.Container(
children=[]
)
for category, options in interpersonal_labels.items():
interpersonal_labels_container.children.append(html.H4(category.title()))
interpersonal_labels_container.children.append(dcc.RadioItems(options))
textual_labels_container = dmc.Container(
children=[]
)
for category, options in textual_labels.items():
textual_labels_container.children.append(html.H4(category.title()))
textual_labels_container.children.append(dcc.RadioItems(options))
label_container = dmc.Container(
children=[
experiential_labels_container,
dmc.Divider(),
interpersonal_labels_container,
dmc.Divider(),
textual_labels_container,
dmc.Divider(),
html.Button(
"confirm",
id="submit-button"
)
]
)
body_container = dmc.Container(
dmc.Grid(
children=[
dmc.Col(
image_container,
span=5,
),
dmc.Col(
dmc.Divider(orientation="vertical"),
span=1,
),
dmc.Col(
# radio buttons part
label_container,
span=5,
),
], grow=True
)
)
return body_container
src/web/header.py
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import dash_mantine_components as dmc
from dash import html
def generate_header():
header = dmc.Header(
height=80,
children=[
dmc.Container(
children=[
html.H2(children="Visual Critical Discourse Analysis Tool", style={"margin-left": "20px", "padding-top": "-5px"}),
], size="xl", px="xl",
),
]
)
return header