Merge pull request #1227 from akaviaLab/refactor/flake8-flux_analysis

flake8 of flux_analysis directory

src/cobra/flux_analysis/__init__.py

@@ -1,3 +1,5 @@
+"""Provide functions related to Flux Analysis."""
+
 from .deletion import (
     double_gene_deletion,
     double_reaction_deletion,

src/cobra/flux_analysis/deletion.py

@@ -205,7 +205,7 @@ def _multi_deletion(
         elif "room" in method:
             add_room(model, solution=solution, linear="linear" in method, **kwargs)
 
-        args = set([frozenset(comb) for comb in product(*element_lists)])
+        args = {frozenset(comb) for comb in product(*element_lists)}
         processes = min(processes, len(args))
 
         def extract_knockout_results(result_iter):
@@ -223,9 +223,10 @@ def extract_knockout_results(result_iter):
             return result
 
         if processes > 1:
-            worker = dict(
-                gene=_gene_deletion_worker, reaction=_reaction_deletion_worker
-            )[entity]
+            worker = {
+                "gene": _gene_deletion_worker,
+                "reaction": _reaction_deletion_worker,
+            }[entity]
             chunk_size = len(args) // processes
 
             with ProcessPool(
@@ -235,7 +236,7 @@ def extract_knockout_results(result_iter):
                     pool.imap_unordered(worker, args, chunksize=chunk_size)
                 )
         else:
-            worker = dict(gene=_gene_deletion, reaction=_reaction_deletion)[entity]
+            worker = {"gene": _gene_deletion, "reaction": _reaction_deletion}[entity]
             results = extract_knockout_results(map(partial(worker, model), args))
         return results
 
@@ -634,7 +635,7 @@ def __getitem__(
                 args = [{obj} for obj in args]
         elif isinstance(args[0], set):
             try:
-                args = [set(elem.id for elem in obj) for obj in args]
+                args = [{elem.id for elem in obj} for obj in args]
             except AttributeError:
                 args = [set(obj) for obj in args]
         else:

src/cobra/flux_analysis/gapfilling.py

@@ -2,7 +2,7 @@
 
 
 import logging
-from typing import TYPE_CHECKING, Dict, List, Optional
+from typing import TYPE_CHECKING, Dict, List, Optional, Union
 
 from optlang.interface import OPTIMAL
 from optlang.symbolics import Zero
@@ -107,7 +107,7 @@ def __init__(
         model: Model,
         universal: Optional[Model] = None,
         lower_bound: float = 0.05,
-        penalties: Optional[Dict[str, "Reaction"]] = None,
+        penalties: Optional[Union[Dict[str, int], Dict["Reaction", int]]] = None,
         exchange_reactions: bool = False,
         demand_reactions: bool = True,
         integer_threshold: float = 1e-6,
@@ -136,7 +136,7 @@ def __init__(
         #  threshold when it is not supported by the chosen solver.
         self.integer_threshold = integer_threshold
         self.universal = universal.copy() if universal else Model("universal")
-        self.penalties = dict(universal=1, exchange=100, demand=1)
+        self.penalties = {"universal": 1, "exchange": 100, "demand": 1}
         if penalties is not None:
             self.penalties.update(penalties)
         self.indicators = []

src/cobra/flux_analysis/phenotype_phase_plane.py

@@ -103,7 +103,7 @@ def production_envelope(
     """
     reactions = model.reactions.get_by_any(reactions)
     objective = model.solver.objective if objective is None else objective
-    data = dict()
+    data = {}
 
     if carbon_sources is None:
         c_input = _find_carbon_sources(model)

src/cobra/flux_analysis/reaction.py

@@ -58,7 +58,7 @@ def assess(
         if m.slim_optimize(error_value=0.0) >= flux_coefficient_cutoff:
             return True
         else:
-            results = dict()
+            results = {}
             results["precursors"] = assess_component(
                 model, reaction, "reactants", flux_coefficient_cutoff
             )
@@ -113,7 +113,7 @@ def assess_component(
 
     """
     reaction = model.reactions.get_by_any(reaction)[0]
-    result_key = dict(reactants="produced", products="capacity")[side]
+    result_key = {"reactants": "produced", "products": "capacity"}[side]
     get_components = attrgetter(side)
     with model as m:
         m.objective = reaction