Fix/allow db via ssh

doc/conf.py

@@ -127,7 +127,7 @@ def setup(sphinx):
     ),
     "ding0": ("https://dingo.readthedocs.io/en/dev/api/ding0.html#%s", "ding0.%s"),
     "pypsa": (
-        "https://pypsa.readthedocs.io/en/latest/user-guide/components.html#%s",
+        "https://docs.pypsa.org/v0.35.1/user-guide/components.html#%s",
         "pypsa.%s",
     ),
     "plotly": (

doc/features_in_detail.rst

@@ -422,7 +422,7 @@ References
     *dena-Verteilnetzstudie: Ausbau- und Innovationsbedarf der Stromverteilnetze in Deutschland bis 2030*. 2012.
 
 .. [PyPSA] `PyPSA - Spatial Clustering Documentation
-            <https://pypsa.readthedocs.io/en/latest/examples/spatial-clustering.html>`_
+            <https://docs.pypsa.org/v0.35.1/examples/spatial-clustering.html>`_
 
 .. [SCR]    `Master Thesis - Malte Jahn - Analysis of the effects of spatial complexity reduction on Distribution
             network expansion planning with flexibilities (written in German)

doc/whatsnew/v0-1-0.rst

@@ -6,7 +6,7 @@ Release date: July 26, 2021
 This release comes with some major refactoring. The internal data structure
 of the network topologies was changed from a networkx graph structure to
 a pandas dataframe structure based on the
-`PyPSA <https://pypsa.readthedocs.io/en/latest/>`_ data structure. This comes
+`PyPSA <https://docs.pypsa.org/v0.35.1/>`_ data structure. This comes
 along with major API changes.
 Not all functionality of the previous eDisGo release 0.0.10 is yet refactored
 (e.g. the heuristics for grid supportive storage integration and generator

edisgo/edisgo.py

@@ -31,7 +31,7 @@
     pypsa_io,
     timeseries_import,
 )
-from edisgo.io.db import engine as toep_engine
+from edisgo.io.db import engine as egon_engine
 from edisgo.io.ding0_import import import_ding0_grid
 from edisgo.io.electromobility_import import (
     distribute_charging_demand,
@@ -556,6 +556,7 @@ def set_time_series_active_power_predefined(
             is indexed using a default year and set for the whole year.
 
         """
+        engine = kwargs["engine"] if "engine" in kwargs else egon_engine()
         if self.timeseries.timeindex.empty:
             logger.warning(
                 "When setting time series using predefined profiles it is better to "
@@ -569,7 +570,7 @@ def set_time_series_active_power_predefined(
                 self,
                 fluctuating_generators_ts,
                 fluctuating_generators_names,
-                engine=kwargs.get("engine", toep_engine()),
+                engine=engine,
                 timeindex=kwargs.get("timeindex", None),
             )
         if dispatchable_generators_ts is not None:
@@ -584,7 +585,7 @@ def set_time_series_active_power_predefined(
                 loads_ts_df = timeseries_import.electricity_demand_oedb(
                     edisgo_obj=self,
                     scenario=kwargs.get("scenario"),
-                    engine=kwargs.get("engine", toep_engine()),
+                    engine=engine,
                     timeindex=kwargs.get("timeindex", None),
                     load_names=conventional_loads_names,
                 )
@@ -978,14 +979,15 @@ def import_generators(self, generator_scenario=None, **kwargs):
             keyword arguments.
 
         """
+        engine = kwargs["engine"] if "engine" in kwargs else egon_engine()
         if self.legacy_grids is True:
             generators_import.oedb_legacy(
                 edisgo_object=self, generator_scenario=generator_scenario, **kwargs
             )
         else:
             generators_import.oedb(
                 edisgo_object=self,
-                engine=kwargs.get("engine", toep_engine()),
+                engine=engine,
                 scenario=generator_scenario,
             )
 
@@ -1004,7 +1006,7 @@ def analyze(
         Conducts a static, non-linear power flow analysis.
 
         Conducts a static, non-linear power flow analysis using
-        `PyPSA <https://pypsa.readthedocs.io/en/latest/user-guide/power-flow.html#\
+        `PyPSA <https://docs.pypsa.org/v0.35.1/user-guide/power-flow.html#\
         non-linear-power-flow>`_
         and writes results (active, reactive and apparent power as well as
         current on lines and voltages at buses) to :class:`~.network.results.Results`
@@ -1109,7 +1111,7 @@ def analyze(
 
         References
         --------
-        [1] https://pypsa.readthedocs.io/en/latest/troubleshooting.html
+        [1] https://docs.pypsa.org/v0.35.1/troubleshooting.html
 
         """
 
@@ -1846,9 +1848,11 @@ def _aggregate_time_series(attribute, groups, naming):
                 [
                     pd.DataFrame(
                         {
-                            naming.format("_".join(k))
-                            if isinstance(k, tuple)
-                            else naming.format(k): getattr(self.timeseries, attribute)
+                            (
+                                naming.format("_".join(k))
+                                if isinstance(k, tuple)
+                                else naming.format(k)
+                            ): getattr(self.timeseries, attribute)
                             .loc[:, v]
                             .sum(axis=1)
                         }

edisgo/io/pypsa_io.py

@@ -362,7 +362,7 @@ def set_seed(edisgo_obj, pypsa_network):
     """
     Set initial guess for the Newton-Raphson algorithm.
 
-    In `PyPSA <https://pypsa.readthedocs.io/en/latest/>`_ an
+    In `PyPSA <https://docs.pypsa.org/v0.35.1/>`_ an
     initial guess for the Newton-Raphson algorithm used in the power flow
     analysis can be provided to speed up calculations.
     For PQ buses, which besides the slack bus, is the only bus type in
@@ -613,9 +613,9 @@ def _append_lv_components(
                         ),
                     ]
                 )
-                aggregated_elements[
-                    lv_grid_name + "_fluctuating"
-                ] = comps_fluct.index.values
+                aggregated_elements[lv_grid_name + "_fluctuating"] = (
+                    comps_fluct.index.values
+                )
 
             if len(comps_disp) > 0:
                 comps_aggr = pd.concat(
@@ -632,21 +632,21 @@ def _append_lv_components(
                         ),
                     ]
                 )
-                aggregated_elements[
-                    lv_grid_name + "_dispatchable"
-                ] = comps_disp.index.values
+                aggregated_elements[lv_grid_name + "_dispatchable"] = (
+                    comps_disp.index.values
+                )
         elif aggregate_generators == "all":
             comps_aggr = pd.DataFrame(
                 {
                     "bus": [bus],
                     "control": ["PQ"],
                     "p_nom": [sum(comps.p_nom)],
                     "fluctuating": [
-                        True
-                        if (comps.type.isin(flucts)).all()
-                        else False
-                        if ~comps.type.isin(flucts).any()
-                        else "Mixed"
+                        (
+                            True
+                            if (comps.type.isin(flucts)).all()
+                            else False if ~comps.type.isin(flucts).any() else "Mixed"
+                        )
                     ],
                 },
                 index=[lv_grid_name + "_generators"],