Connection rework, now prefers using get_connection and set_connection functions to connect to data sources. Has helper functions to set up connection to eimerdb and postgres.

demo/control/control_app.py

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+# ---
+# jupyter:
+#   jupytext:
+#     text_representation:
+#       extension: .py
+#       format_name: light
+#       format_version: '1.5'
+#   kernelspec:
+#     display_name: demo-ssb-dash
+#     language: python
+#     name: demo-ssb-dash
+# ---
+
+# +
+import os  # Nødvendig for oppsett
+
+from control_code import DemoControls  # For å kunne bruke kontroll-modulen
+
+# Moduler importert fra biblioteket
+# from ssb_dash_framework import HBMethod
+from ssb_dash_framework import AggDistPlotterWindow
+from ssb_dash_framework import AltinnControlViewWindow
+from ssb_dash_framework import AltinnSkjemadataEditor
+from ssb_dash_framework import FreeSearchTab
+from ssb_dash_framework import app_setup
+from ssb_dash_framework import main_layout
+from ssb_dash_framework import set_eimerdb_connection
+from ssb_dash_framework import set_variables
+
+# from egentilpassing.hb_method import hb_get_data
+
+
+# Kobling til EimerDB som ligger i fellesbøtta.
+set_eimerdb_connection(
+    "ssb-dapla-felles-data-produkt-prod",
+    "produksjonstilskudd_altinn3",
+)
+selected_time_units = ["aar"]  # Tidsenheten(e) til dataene
+
+# Basic app-oppsett
+port = 8070
+service_prefix = os.getenv("JUPYTERHUB_SERVICE_PREFIX", "/")
+domain = os.getenv("JUPYTERHUB_HTTP_REFERER", None)
+app = app_setup(port, service_prefix, "lumen", logging_level="debug", log_to_file=True)
+
+# VARIABLER: Velg hvilke variabler appen skal bruke. Default values er valgfritt, men anbefalt.
+set_variables(
+    [
+        "aar",
+        "ident",
+        "statistikkvariabel",
+        "altinnskjema",
+        "valgt_tabell",
+        "refnr",
+    ]
+)
+default_values = {
+    "aar": "2023",
+    "statistikkvariabel": "fulldyrket",
+    "valgt_tabell": "skjemadata_hoved",
+    "altinnskjema": "RA-7357",
+}
+
+# Uncomment this if you have access to the VoF shared bucket.
+# bof_module = BofInformationTab(
+#     variableselector_foretak_name="ident"
+# )
+
+# Legg in alle tabene i denne lista
+tab_list = [
+    AltinnSkjemadataEditor(time_units=selected_time_units, variable_connection={}),
+    FreeSearchTab(),
+    #    bof_module # Uncomment this if you have access to the VoF shared bucket.
+]
+
+# MODALENE: Lag en liste med alle modalene
+# hb = HBMethod(
+#     database=conn,
+#     hb_get_data_func=hb_get_data,
+#     selected_state_keys=["aar", "statistikkvariabel"],
+#     selected_ident="ident",
+#     variable="verdi",
+# )
+
+# visualiseringsbyggermodul = VisualizationBuilder(conn)
+# datafangstmodalen = AltinnDataCaptureWindow(
+#     time_units=selected_time_units
+# )
+aggdistplotter = AggDistPlotterWindow(selected_time_units)
+
+controls = AltinnControlViewWindow(
+    time_units=["aar"], control_dict={"RA-7357": DemoControls}
+)
+
+# MODALENE: Lag en liste med alle modalene
+modal_list = [
+    # datafangstmodalen,
+    aggdistplotter,
+    controls,
+    # hb,
+    # visualiseringsbyggermodul,
+]
+
+# Denne linja genererer layouten til hele appen. Her legges listene med valgt innhold for modalene, fanene og variablene.
+app.layout = main_layout(modal_list, tab_list, default_values=default_values)
+
+if __name__ == "__main__":
+    app.run(debug=True, port=port, jupyter_server_url=domain, jupyter_mode="tab")

demo/control/control_code.py

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+# ---
+# jupyter:
+#   jupytext:
+#     cell_metadata_filter: -papermill,tags
+#     custom_cell_magics: kql
+#     text_representation:
+#       extension: .py
+#       format_name: percent
+#       format_version: '1.3'
+#       jupytext_version: 1.16.2
+#   kernelspec:
+#     display_name: .venv
+#     language: python
+#     name: python3
+# ---
+
+
+import eimerdb as db
+import pandas as pd
+
+# %% metadata={}
+from ssb_dash_framework import ControlFrameworkBase
+from ssb_dash_framework import register_control
+
+conn = db.EimerDBInstance(
+    "ssb-dapla-felles-data-produkt-prod",
+    "produksjonstilskudd_altinn3",
+)
+
+
+class DemoControls(ControlFrameworkBase):
+    def __init__(
+        self,
+        time_units: list[int | str],
+        applies_to_subset: dict[str, int | str],
+    ) -> None:
+        super().__init__(time_units, applies_to_subset)
+
+    @register_control(
+        kontrollid="nye",
+        kontrolltype="I",
+        beskrivelse="Nye enheter for året",
+        kontrollerte_variabler=["ident"],
+        sorteringsvariabel="fulldyrket",
+        sortering="ASC",
+    )
+    def control_nye(self):
+        aar = int(self.applies_to_subset["aar"][0])
+
+        df = conn.query("SELECT * FROM skjemamottak")
+
+        enheter_fjoraar = list(df.loc[df["aar"] == aar - 1]["ident"].unique())
+
+        nye_enheter = df.loc[(df["aar"] == aar) & (~df["ident"].isin(enheter_fjoraar))]
+        ikke_nye_enheter = df.loc[
+            (df["aar"] == aar) & (df["ident"].isin(enheter_fjoraar))
+        ]
+
+        nye_enheter["utslag"] = True
+        ikke_nye_enheter["utslag"] = False
+
+        df = pd.concat([nye_enheter, ikke_nye_enheter])
+        df["verdi"] = 0
+
+        return df[["aar", "skjema", "ident", "refnr", "utslag", "verdi"]]
+
+    @register_control(
+        kontrollid="diff",
+        kontrolltype="S",
+        beskrivelse="Stor differanse mot fjoråret",
+        kontrollerte_variabler=["fulldyrket"],
+        sorteringsvariabel="fulldyrket",
+        sortering="ASC",
+    )
+    def control_diff(self):
+        aar = int(self.applies_to_subset["aar"][0])
+        df = conn.query("SELECT * FROM skjemadata_hoved")
+        df = df.loc[df["variabel"] == "fulldyrket"]
+        diff_df = df.loc[(df["aar"].isin([aar, aar - 1]))]
+        diff_df = diff_df.pivot(
+            index=["ident", "variabel"], columns="aar", values="verdi"
+        ).reset_index()
+        diff_df[aar - 1] = diff_df[aar - 1].astype(float)
+        diff_df[aar] = diff_df[aar].astype(float)
+        diff_df = diff_df.loc[(diff_df[aar - 1] > 0) & (diff_df[aar] > 0)]
+
+        diff_df["differanse"] = diff_df[aar] - diff_df[aar - 1]
+        diff_df["prosent_endring"] = (diff_df["differanse"] / diff_df[aar - 1]) * 100
+
+        diff_df["utslag"] = False
+        diff_df.loc[(abs(diff_df["prosent_endring"]) > 100), "utslag"] = True
+
+        diff_df["aar"] = aar
+        diff_df["skjema"] = "RA-7357"
+        diff_df["kontrollid"] = "diff"
+        diff_df["verdi"] = diff_df["prosent_endring"].astype(int)
+
+        diff_df = diff_df.merge(
+            df.loc[df["aar"] == aar][["ident", "refnr"]], on="ident"
+        )
+        return diff_df[
+            ["aar", "skjema", "ident", "refnr", "kontrollid", "utslag", "verdi"]
+        ]
+
+
+if __name__ == "__main__":
+
+    test = DemoControls(
+        time_units=["aar"],
+        applies_to_subset={"aar": 2024, "skjema": "RA-7357"},
+        conn=conn,
+    )
+
+    test.register_all_controls()
+    test.execute_controls()
+
+    print(conn.query("SELECT * FROM kontroller"))
+
+    print(conn.query("SELECT * FROM kontrollutslag"))