refactor: remove unused imports and optimize network module by importing networkx locally

Author: dwr-psandhu

pydsm/analysis/dsm2study.py

@@ -9,26 +9,10 @@
 
 # our imports
 import pyhecdss
-import pydsm
 from pydsm.input import parser, network
 from pydsm.output import hydroh5
 from vtools.functions.filter import godin
 
-# viz imports
-import geoviews as gv
-import hvplot.pandas
-import holoviews as hv
-from holoviews import opts
-
-hv.extension("bokeh")
-import colorcet as cc
-
-#
-import param
-import panel as pn
-
-pn.extension()
-
 import logging
 
 logger = logging.getLogger(__name__)

pydsm/analysis/postpro.py

@@ -614,7 +614,19 @@ def build_processors(dssfile, locationfile, vartype, units, study_name, observed
     return processors
 
 
-def run_processor(processor, store=True, clear=True):
+def run_processor(processor, store=True, clear=True, skip_if_cached=False):
+    if skip_if_cached:
+        key = processor.cache.get_cache_key(
+            processor.location.name,
+            processor.vartype.name,
+            PostProcessor.TIME_INTERVAL,
+        )
+        if key in processor.cache.cache:
+            logging.info(
+                "Skipping %s/%s (already cached)"
+                % (processor.location.name, processor.vartype.name)
+            )
+            return
     logging.info("Running %s/%s" % (processor.location.name, processor.vartype.name))
     processed = False
     try:

pydsm/input/network.py

@@ -1,11 +1,11 @@
 # Creates a network containing channel and reservoir connections as nodes and channels and reservoirs as arcs.
-import networkx as nx
 
 
 def build_network_channels(tables):
     '''
     Builds network with channel upnodes -> downnodes. Stores the columns as attributes of each node
     '''
+    import networkx as nx
     c = tables['CHANNEL']
     gc = nx.from_pandas_edgelist(c, source='UPNODE', target='DOWNNODE', edge_attr=list(
         c.columns), create_using=nx.MultiDiGraph)
@@ -18,6 +18,7 @@ def build_network_reservoirs(tables):
     each resevoir connection, one from reservoir to node and from node to the reservoir.
     In this way, each reservoir is treated as a node in the graph
     '''
+    import networkx as nx
     rc = tables['RESERVOIR_CONNECTION']
     grc1 = nx.from_pandas_edgelist(rc, source='RES_NAME', target='NODE', edge_attr=list(
         rc.columns), create_using=nx.MultiDiGraph)
@@ -34,5 +35,6 @@ def build_network(tables):
     '''
     gc = build_network_channels(tables)
     grc = build_network_reservoirs(tables)
+    import networkx as nx
     g = nx.compose(gc, grc)
     return g