Multi Tenancy Support (got it working this time!)

.github/workflows/build_exe.yml

@@ -2,6 +2,18 @@ name: Build Executables
 
 on:
   workflow_call:
+    secrets:
+      APPLE_DEV_EMAIL:
+      APP_SPEC_PASS:
+      DEV_APP_CERT:
+      DEV_APP_CERT_PASS:
+      DEV_INST_CERT:
+      DEV_INST_CERT_PASS:
+      APPLE_KEY_PASS:
+      APPLE_APP_CERT_ID:
+      APPLE_INST_CERT_ID:
+      TEAM_ID:
+
     inputs:
       is_release:
         default: false
@@ -62,7 +74,7 @@ jobs:
           echo "PYINST_BIN=\"$(which pyinstaller)\"" >> "$GITHUB_ENV"
       - name: Create macOS keychain
         id: keychain
-        if: runner.os == 'macOS'
+        if: runner.os == 'macOS' && inputs.is_release
         env:
           APPLE_DEV_EMAIL: ${{secrets.APPLE_DEV_EMAIL}}
           APP_SPEC_PASS: ${{secrets.APP_SPEC_PASS}}
@@ -113,7 +125,7 @@ jobs:
         run: ${{ matrix.sha_command }}
 
       - name: Create and sign mac package
-        if: runner.os == 'macOS'
+        if: runner.os == 'macOS' && inputs.is_release
         env:
           APPLE_INST_CERT_ID: ${{secrets.APPLE_INST_CERT_ID}}
           APPLE_KEYCHAIN_PASS: ${{secrets.APPLE_KEY_PASS}}
@@ -127,27 +139,27 @@ jobs:
           pkgbuild --identifier "org.mangotango.cli" --timestamp --root /tmp/mangotango --install-location /Applications "./dist/mangotango_${{matrix.artifact_name}}_signed.pkg" --sign "$APPLE_INST_CERT_ID"
 
       - name: Notarize Mac package
-        if: runner.os == 'macOS'
+        if: runner.os == 'macOS' && inputs.is_release
         env:
           APPLE_DEV_EMAIL: ${{secrets.APPLE_DEV_EMAIL}}
           APPLE_TEAM_ID: ${{secrets.TEAM_ID}}
           APP_SPEC_PASS: ${{secrets.APP_SPEC_PASS}}
-        run: xcrun notarytool submit dist/mangotango_${{matrix.artifact_name}}_signed.pkg --apple-id $APPLE_DEV_EMAIL --team-id $APPLE_TEAM_ID --password $APP_SPEC_PASS --wait > notarization_output.txt
+        run: xcrun notarytool submit dist/mangotango_${{matrix.artifact_name}}_signed.pkg --apple-id $APPLE_DEV_EMAIL --team-id $APPLE_TEAM_ID --password $APP_SPEC_PASS --wait
 
       - name: Staple the notarization ticket
-        if: runner.os == 'macOS'
+        if: runner.os == 'macOS' && inputs.is_release
         run: xcrun stapler staple dist/mangotango_${{matrix.artifact_name}}_signed.pkg
 
       - name: Clean up macOS Artifacts
-        if: runner.os == 'macOS'
+        if: runner.os == 'macOS' && inputs.is_release
         run: |
           rm -rf /tmp/mangotango
           rm -rf dist/mangotango_${{matrix.artifact_name}}
           rm -rf dist/mangotango_${{matrix.artifact_name}}.pkg
           mv dist/mangotango_${{matrix.artifact_name}}_signed.pkg dist/mangotango_${{matrix.artifact_name}}.pkg
 
       - name: Compute the SHA1 hashsum for macOS .pkg
-        if: runner.os == 'macOS'
+        if: runner.os == 'macOS' && inputs.is_release
         run: ${{ matrix.sha_command_pkg }}
 
       - name: Inspect the dist/ directory before uploading artifacts
@@ -160,4 +172,3 @@ jobs:
           name: ${{ matrix.artifact_name }}
           path: |
             dist/*
-

analyzer_interface/context.py

@@ -1,9 +1,12 @@
 from abc import ABC, abstractmethod
-from typing import TypeVar
+from typing import Any, Callable, Optional, TypeVar, Union
 
 import polars as pl
 from dash import Dash
+from polars import DataFrame
 from pydantic import BaseModel
+from shiny import Inputs, Outputs, Session
+from shiny.ui._navs import NavPanel
 
 from .interface import SecondaryAnalyzerInterface
 from .params import ParamValue
@@ -155,3 +158,25 @@ def parquet_path(self) -> str:
         file to it.
         """
         pass
+
+
+ServerCallback = Union[
+    Callable[[Inputs], None], Callable[[Inputs, Outputs, Session], None]
+]
+
+
+class ShinyContext(BaseModel):
+    panel: NavPanel = None
+    server_handler: Optional[ServerCallback] = None
+
+    class Config:
+        arbitrary_types_allowed = True
+
+
+class FactoryOutputContext(BaseModel):
+    shiny: Optional[ShinyContext] = None
+    api: Optional[dict[str, Any]] = None
+    data_frames: Optional[dict[str, DataFrame]] = None
+
+    class Config:
+        arbitrary_types_allowed = True

analyzer_interface/declaration.py

@@ -1,6 +1,7 @@
-from typing import Callable
+from typing import Callable, Union
 
 from .context import (
+    FactoryOutputContext,
     PrimaryAnalyzerContext,
     SecondaryAnalyzerContext,
     WebPresenterContext,
@@ -69,11 +70,17 @@ def __init__(self, interface: SecondaryAnalyzerInterface, main: Callable):
 
 
 class WebPresenterDeclaration(WebPresenterInterface):
-    factory: Callable[["WebPresenterContext"], None]
-
+    factory: Callable[["WebPresenterContext"], Union[FactoryOutputContext, None]]
+    shiny: bool
     server_name: str
 
-    def __init__(self, interface: WebPresenterInterface, factory: Callable, name: str):
+    def __init__(
+        self,
+        interface: WebPresenterInterface,
+        factory: Callable,
+        name: str,
+        shiny: bool,
+    ):
         """Creates a web presenter declaration
 
         Args:
@@ -99,4 +106,6 @@ def __init__(self, interface: WebPresenterInterface, factory: Callable, name: st
             https://docs.python.org/3/tutorial/modules.html
 
         """
-        super().__init__(**interface.model_dump(), factory=factory, server_name=name)
+        super().__init__(
+            **interface.model_dump(), factory=factory, server_name=name, shiny=shiny
+        )

analyzers/example/example_web/__init__.py

@@ -9,4 +9,5 @@
     # You must pass __name__ here. It's to make Dash happy.
     # See: http://dash.plotly.com/urls
     name=__name__,
+    shiny=False,
 )

analyzers/hashtags_web/__init__.py

@@ -4,5 +4,5 @@
 from .interface import interface
 
 hashtags_web = WebPresenterDeclaration(
-    interface=interface, factory=factory, name=__name__
+    interface=interface, factory=factory, name=__name__, shiny=True
 )

analyzers/hashtags_web/app.py

@@ -2,23 +2,24 @@
 
 import numpy as np
 import polars as pl
-from shiny import App, reactive, render, ui
+from shiny import reactive, render, ui
 from shinywidgets import output_widget, render_widget
 
 from ..hashtags.interface import COL_AUTHOR_ID, COL_POST, COL_TIME
 from .analysis import secondary_analyzer
 from .plots import plot_bar_plotly, plot_gini_plotly, plot_users_plotly
 
-MANGO_ORANGE2 = "#f3921e"
-LOGO_URL = "https://raw.githubusercontent.com/CIB-Mango-Tree/CIB-Mango-Tree-Website/main/assets/images/mango-text.PNG"
-
 # https://icons.getbootstrap.com/icons/question-circle-fill/
 question_circle_fill = ui.HTML(
     '<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="currentColor" class="bi bi-question-circle-fill mb-1" viewBox="0 0 16 16"><path d="M16 8A8 8 0 1 1 0 8a8 8 0 0 1 16 0zM5.496 6.033h.825c.138 0 .248-.113.266-.25.09-.656.54-1.134 1.342-1.134.686 0 1.314.343 1.314 1.168 0 .635-.374.927-.965 1.371-.673.489-1.206 1.06-1.168 1.987l.003.217a.25.25 0 0 0 .25.246h.811a.25.25 0 0 0 .25-.25v-.105c0-.718.273-.927 1.01-1.486.609-.463 1.244-.977 1.244-2.056 0-1.511-1.276-2.241-2.673-2.241-1.267 0-2.655.59-2.75 2.286a.237.237 0 0 0 .241.247zm2.325 6.443c.61 0 1.029-.394 1.029-.927 0-.552-.42-.94-1.029-.94-.584 0-1.009.388-1.009.94 0 .533.425.927 1.01.927z"/></svg>'
 )
 
+df_global = None
+context_global = None
+df_raw = None
+
 
-def _set_df_global_state(df_input, df_output):
+def set_df_global_state(df_input, df_output):
     global df_global, df_raw
     df_global = df_output
     df_raw = df_input  # Will be loaded from context when needed
@@ -36,9 +37,6 @@ def get_raw_data_subset(time_start, time_end, user_id, hashtag):
 
 
 # Global variables for CLI integration
-df_global = None
-context_global = None
-df_raw = None
 
 
 def select_users(secondary_output, selected_hashtag):
@@ -154,46 +152,6 @@ def select_users(secondary_output, selected_hashtag):
     ui.output_data_frame("tweets"),
 )
 
-analysis_panel_elements = [
-    page_dependencies,
-    analysis_panel,
-    ui.layout_columns(
-        hashtag_plot_panel,
-        users_plot_panel,
-    ),
-    tweet_explorer,
-]
-
-
-ABOUT_TEXT = ui.markdown(
-    f"""
-
-<img src="{LOGO_URL}" alt="logo" style="width:200px;"/>
-
-CIB Mango Tree, a collaborative and open-source project to develop software that tests for coordinated inauthentic behavior (CIB) in datasets of online activity.
-
-[mangotree.org](https://mangotree.org)
-
-A project of [Civic Tech DC](https://www.civictechdc.org/), our mission is to share methods to uncover how disruptive actors seek to hack our legitimate online discourse regarding health, politics, and society. The CIB Mango Tree presents the most simple tests for CIB first – the low-hanging fruit. These tests are easy to run and interpret. They will reveal signs of unsophisticated CIB. As you move up the Mango Tree, tests become harder and will scavenge for higher-hanging fruit.
-
-"""
-)
-app_layout = ui.page_navbar(
-    ui.nav_panel(
-        "Dashboard",
-        analysis_panel_elements,
-    ),
-    ui.nav_panel(
-        "About",
-        ui.card(
-            ui.card_header("About the Mango Tree project"),
-            ABOUT_TEXT,
-            ui.card_footer("PolyForm Noncommercial License 1.0.0"),
-        ),
-    ),
-    title="Hashtag analysis dashboard",
-)
-
 
 def server(input, output, session):
     @reactive.calc

analyzers/hashtags_web/factory.py

@@ -1,26 +1,28 @@
 import polars as pl
-from pydantic import BaseModel
+from dash import html
+from shiny.ui import layout_columns, nav_panel
 
-from analyzer_interface.context import WebPresenterContext
+from analyzer_interface.context import (
+    FactoryOutputContext,
+    ShinyContext,
+    WebPresenterContext,
+)
+from app.shiny import page_dependencies
 
 from ..hashtags.interface import COL_AUTHOR_ID, COL_POST, COL_TIME, OUTPUT_GINI
-from .app import _set_df_global_state, app_layout, server
-
-
-# config used by AnalysisWebServerContext._start_shiny_server()
-class ShinyServerConfig(BaseModel):
-    server: object
-    port: int = 8051
-
-
-class ShinyAppConfig(BaseModel):
-    app_layout: object
-    server_config: ShinyServerConfig
+from .app import (
+    analysis_panel,
+    hashtag_plot_panel,
+    server,
+    set_df_global_state,
+    tweet_explorer,
+    users_plot_panel,
+)
 
 
 def factory(
     web_context: WebPresenterContext,
-):
+) -> FactoryOutputContext:
     # Load the primary output associated with this project
     df_hashtags = pl.read_parquet(web_context.base.table(OUTPUT_GINI).parquet_path)
 
@@ -41,26 +43,33 @@ def factory(
         pl.col(COL_TIME)
     )
 
-    # Create app layout and server with processed data
-    _set_df_global_state(df_input=df_raw, df_output=df_hashtags)
-
-    # For now, mount the Shiny app via iframe in Dash
-    # This preserves the existing CLI integration
-    from dash import html
-
-    app = web_context.dash_app
+    set_df_global_state(
+        df_input=df_raw,
+        df_output=df_hashtags,
+    )
 
-    app.layout = html.Div(
+    web_context.dash_app.layout = html.Div(
         [
             html.H1("Hashtag Analysis Dashboard"),
             html.Iframe(
-                src="http://localhost:8051",  # Shiny app will run on port 8051
+                src="http://localhost:8050/shiny",  # Shiny app will run on port 8051
                 style={"width": "100%", "height": "800px", "border": "none"},
             ),
         ]
     )
 
-    # Return Shiny app configuration for the webserver context to handle
-    return ShinyAppConfig(
-        app_layout=app_layout, server_config=ShinyServerConfig(server=server, port=8051)
+    return FactoryOutputContext(
+        shiny=ShinyContext(
+            server_handler=server,
+            panel=nav_panel(
+                "Dashboard",
+                page_dependencies,
+                analysis_panel,
+                layout_columns(
+                    hashtag_plot_panel,
+                    users_plot_panel,
+                ),
+                tweet_explorer,
+            ),
+        )
     )

analyzers/ngram_web/__init__.py

@@ -4,5 +4,5 @@
 from .interface import interface
 
 ngrams_web = WebPresenterDeclaration(
-    interface=interface, factory=factory, name=__name__
+    interface=interface, factory=factory, name=__name__, shiny=False
 )

analyzers/temporal_barplot/__init__.py

@@ -4,5 +4,5 @@
 from .interface import interface
 
 temporal_barplot = WebPresenterDeclaration(
-    interface=interface, factory=factory, name=__name__
+    interface=interface, factory=factory, name=__name__, shiny=False
 )