Merge pull request #767 from hackingmaterials/dict-keys

Remove unneeded `dict.keys()`

README.md

@@ -2,14 +2,14 @@
 
 [![Tests](https://github.com/hackingmaterials/atomate/actions/workflows/test.yml/badge.svg)](https://github.com/hackingmaterials/atomate/actions/workflows/test.yml)
 [![PyPI Downloads](https://img.shields.io/pypi/dm/atomate?label=PyPI%20Downloads)](https://pypi.org/project/atomate)
-[![PyPI](https://img.shields.io/pypi/v/atomate?label=PyPI%20Release)](https://pypi.org/project/atomate)
-[![Requires Python 3.8+](https://img.shields.io/badge/Python-3.8+-blue.svg?label=Requires%20Python)](https://python.org/downloads)
+[![PyPI](https://img.shields.io/pypi/v/atomate?logo=pypi&logoColor=white)](https://pypi.org/project/atomate)
+[![Requires Python 3.8+](https://img.shields.io/badge/Python-3.8+-blue.svg?logo=python&logoColor=white)](https://python.org/downloads)
 
 atomate is a software for computational materials science that contains pre-built workflows to compute and analyze the properties of materials.
 
-- **Website (including documentation):** https://hackingmaterials.github.io/atomate/
-- **Help/Support:** https://discuss.matsci.org/c/atomate
-- **Source:** https://github.com/hackingmaterials/atomate
+- **Website (including documentation):** <https://hackingmaterials.github.io/atomate/>
+- **Help/Support:** <https://discuss.matsci.org/c/atomate>
+- **Source:** <https://github.com/hackingmaterials/atomate>
 
 If you find atomate useful, please encourage its development by citing the following paper in your research output:
 

atomate/qchem/powerups.py

@@ -25,7 +25,7 @@ def use_fake_qchem(original_wf, ref_dirs, input_file="mol.qin"):
         Workflow
     """
     for idx_fw, fw in enumerate(original_wf.fws):
-        for job_type in ref_dirs.keys():
+        for job_type in ref_dirs:
             if job_type == fw.name:
                 for idx_t, t in enumerate(fw.tasks):
                     if "RunQChemCustodian" in str(t) or "RunQChemDirect" in str(t):

atomate/qchem/tests/test_drones.py

@@ -213,12 +213,8 @@ def test_assimilate_FF(self):
         self.assertIn("last_updated", doc)
         self.assertIn("dir_name", doc)
         self.assertEqual(len(doc["calcs_reversed"]), 4)
-        self.assertEqual(
-            list(doc["calcs_reversed"][0].keys()), list(doc["calcs_reversed"][2].keys())
-        )
-        self.assertEqual(
-            list(doc["calcs_reversed"][1].keys()), list(doc["calcs_reversed"][3].keys())
-        )
+        self.assertEqual(list(doc["calcs_reversed"][0]), list(doc["calcs_reversed"][2]))
+        self.assertEqual(list(doc["calcs_reversed"][1]), list(doc["calcs_reversed"][3]))
 
     def test_assimilate_bad_FF(self):
         drone = QChemDrone(
@@ -327,9 +323,7 @@ def test_assimilate_ffts(self):
         self.assertIn("last_updated", doc)
         self.assertIn("dir_name", doc)
         self.assertEqual(len(doc["calcs_reversed"]), 3)
-        self.assertEqual(
-            list(doc["calcs_reversed"][0].keys()), list(doc["calcs_reversed"][2].keys())
-        )
+        self.assertEqual(list(doc["calcs_reversed"][0]), list(doc["calcs_reversed"][2]))
 
     def test_assimilate_bad_ffts(self):
         drone = QChemDrone(

atomate/vasp/builders/tasks_materials.py

@@ -83,7 +83,7 @@ def run(self):
         q = {"state": "successful", "task_label": {"$in": self.supported_task_labels}}
 
         if self.query:
-            common_keys = [k for k in q.keys() if k in self.query.keys()]
+            common_keys = [k for k in q if k in self.query]
             if common_keys:
                 raise ValueError(
                     f"User query parameter cannot contain key(s): {common_keys}"

atomate/vasp/firetasks/approx_neb_dynamic_tasks.py

@@ -125,19 +125,19 @@ def run_task(self, fw_spec):
         elif isinstance(structure_paths, (dict)):
             relax_image_fws = []
             if launch_mode == "all":
-                for key in structure_paths.keys():
+                for key in structure_paths:
                     for path in structure_paths[key]:
                         relax_image_fws.append(self.get_fw(structure_path=path))
             elif launch_mode == "screening":
-                for key in structure_paths.keys():
+                for key in structure_paths:
                     sorted_paths = structure_paths[key]
                     relax_image_fws.extend(
                         self.get_screening_fws(sorted_paths=sorted_paths)
                     )
 
         # place fws in temporary wf in order to use powerup_by_kwargs
         # to apply powerups to image fireworks
-        if "vasp_powerups" in fw_spec.keys():
+        if "vasp_powerups" in fw_spec:
             temp_wf = Workflow(relax_image_fws)
             powerup_dicts = fw_spec["vasp_powerups"]
             temp_wf = powerup_by_kwargs(temp_wf, powerup_dicts)
@@ -177,7 +177,7 @@ def get_fw(self, structure_path, parents=None):
             add_tags=add_tags,
         )
         if isinstance(add_tags, list):
-            if "tags" in fw.spec.keys():
+            if "tags" in fw.spec:
                 fw.spec["tags"].extend(add_tags)
             else:
                 fw.spec["tags"] = add_tags

atomate/vasp/firetasks/approx_neb_tasks.py

@@ -90,7 +90,7 @@ def run_task(self, fw_spec):
         additional_fields = self.get("additional_fields", {})
         if isinstance(additional_fields, dict):
             for key, value in additional_fields.items():
-                if key not in approx_neb_doc.keys():
+                if key not in approx_neb_doc:
                     approx_neb_doc[key] = value
 
         tags = self.get("tags")
@@ -156,7 +156,7 @@ def run_task(self, fw_spec):
         # pulls desired fields from approx_neb collection and stores in pulled_fields
         pulled_doc = mmdb.collection.find_one({"wf_uuid": wf_uuid})
         pulled_fields = dict()
-        for key in fields_to_pull.keys():
+        for key in fields_to_pull:
             pulled_fields[key] = get(pulled_doc, fields_to_pull[key])
 
         # update fw_spec with pulled fields (labeled according to fields_to_pass)
@@ -230,7 +230,7 @@ def run_task(self, fw_spec):
         structure = Structure.from_dict(structure_doc["output"]["structure"])
         # removes site properties to avoid error
         if structure.site_properties != {}:
-            for p in structure.site_properties.keys():
+            for p in structure.site_properties:
                 structure.remove_site_property(p)
 
         # insert site(s) in structure and stores corresponding site index in inserted_site_indexes
@@ -559,7 +559,7 @@ def run_task(self, fw_spec):
         pf_subdoc = mmdb.collection.find_one(
             {"wf_uuid": wf_uuid}, {"pathfinder": 1, "_id": 0}
         )
-        if "pathfinder" not in pf_subdoc.keys():
+        if "pathfinder" not in pf_subdoc:
             pf_subdoc = {}
         else:
             pf_subdoc = pf_subdoc["pathfinder"]
@@ -655,7 +655,7 @@ def run_task(self, fw_spec):
             )
 
         # store images output in approx_neb collection
-        if "images" not in approx_neb_doc.keys():
+        if "images" not in approx_neb_doc:
             images_subdoc = {}
         else:
             images_subdoc = approx_neb_doc["images"]
@@ -738,7 +738,7 @@ def add_fix_two_atom_selective_dynamics(self, structure, fixed_index, fixed_spec
 
         # removes site properties to avoid error
         if structure.site_properties != {}:
-            for p in structure.site_properties.keys():
+            for p in structure.site_properties:
                 structure.remove_site_property(p)
 
         sd_structure = structure.copy()

atomate/vasp/firetasks/parse_outputs.py

@@ -495,7 +495,7 @@ def run_task(self, fw_spec):
         }
 
         # store the displacement & epsilon for each mode in a dictionary
-        mode_disps = fw_spec["raman_epsilon"].keys()
+        mode_disps = fw_spec["raman_epsilon"]
         modes_eps_dict = defaultdict(list)
         for md in mode_disps:
             modes_eps_dict[fw_spec["raman_epsilon"][md]["mode"]].append(

atomate/vasp/powerups.py

@@ -114,7 +114,7 @@ def use_no_vasp(original_wf, ref_dirs):
         Workflow
     """
     for idx_fw, fw in enumerate(original_wf.fws):
-        for job_type in ref_dirs.keys():
+        for job_type in ref_dirs:
             if job_type in fw.name:
                 for idx_t, t in enumerate(fw.tasks):
                     if "RunVasp" in str(t):
@@ -171,7 +171,7 @@ def use_fake_vasp(
         ]
 
     for idx_fw, fw in enumerate(original_wf.fws):
-        for job_type in ref_dirs.keys():
+        for job_type in ref_dirs:
             if job_type in fw.name:
                 for idx_t, t in enumerate(fw.tasks):
                     t_str = str(t)
@@ -384,7 +384,7 @@ def modify_to_soc(
         fw_name_constraint=fw_name_constraint,
         task_name_constraint="RunBoltztrap",
     )
-    for idx_fw, idx_t in run_boltztrap_list:
+    for idx_fw, _idx_t in run_boltztrap_list:
         original_wf.fws[idx_fw].name += " soc"
 
     return original_wf
@@ -457,7 +457,7 @@ def set_queue_options(
         task_name_constraint=task_name_constraint,
     )
 
-    for idx_fw, idx_t in idx_list:
+    for idx_fw, _idx_t in idx_list:
         original_wf.fws[idx_fw].spec.update({"_queueadapter": qsettings})
 
     return original_wf
@@ -525,7 +525,7 @@ def add_stability_check(
         fw_name_constraint=fw_name_constraint,
         task_name_constraint="VaspToDb",
     )
-    for idx_fw, idx_t in idx_list:
+    for idx_fw, _idx_t in idx_list:
         original_wf.fws[idx_fw].tasks.append(CheckStability(**check_stability_params))
     return original_wf
 
@@ -551,7 +551,7 @@ def add_bandgap_check(original_wf, check_bandgap_params=None, fw_name_constraint
         fw_name_constraint=fw_name_constraint,
         task_name_constraint="VaspToDb",
     )
-    for idx_fw, idx_t in idx_list:
+    for idx_fw, _idx_t in idx_list:
         original_wf.fws[idx_fw].tasks.append(CheckBandgap(**check_bandgap_params))
     return original_wf
 
@@ -812,7 +812,7 @@ def use_fake_lobster(original_wf, ref_dirs, params_to_check=None):
     if not params_to_check:
         params_to_check = ["basisSet", "cohpGenerator", "basisfunctions"]
     for idx_fw, fw in enumerate(original_wf.fws):
-        for job_type in ref_dirs.keys():
+        for job_type in ref_dirs:
             if job_type in fw.name:
                 for idx_t, t in enumerate(fw.tasks):
                     if "RunLobster" in str(t):

atomate/vasp/tests/test_drones.py

@@ -67,12 +67,12 @@ def test_runs_assimilate(self):
         self.assertEqual(doc["formula_pretty"], "Si")
         self.assertEqual(doc["formula_anonymous"], "A")
         self.assertEqual(
-            list(doc["calcs_reversed"][0]["input"].keys()),
-            list(doc["calcs_reversed"][1]["input"].keys()),
+            list(doc["calcs_reversed"][0]["input"]),
+            list(doc["calcs_reversed"][1]["input"]),
         )
         self.assertEqual(
-            list(doc["calcs_reversed"][0]["output"].keys()),
-            list(doc["calcs_reversed"][1]["output"].keys()),
+            list(doc["calcs_reversed"][0]["output"]),
+            list(doc["calcs_reversed"][1]["output"]),
         )
         self.assertEqual(
             doc["calcs_reversed"][0]["output"]["energy"], doc["output"]["energy"]

atomate/vasp/workflows/base/approx_neb.py

@@ -161,7 +161,7 @@ def get_aneb_wf(
     )
 
     # modifies incar settings needed for end point and image structure relaxations
-    if "user_incar_settings" not in approx_neb_params.keys():
+    if "user_incar_settings" not in approx_neb_params:
         approx_neb_params = {"user_incar_settings": {}}
     approx_neb_params["user_incar_settings"]["ISIF"] = 2
     approx_neb_params["user_incar_settings"]["ISYM"] = 0

atomate/vasp/workflows/base/hubbard_hund_linresp.py

@@ -184,7 +184,7 @@ def get_wf_hubbard_hund_linresp(
 
     # generate list of applied on-site potentials in linear response
     applied_potential_value_list = []
-    for counter_perturb in range(num_perturb):
+    for _ in range(num_perturb):
         applied_potential_values = np.linspace(
             applied_potential_range[0], applied_potential_range[1], num_evals
         )
@@ -264,11 +264,11 @@ def find_closest_sites(struct, species_perturb):
     n_species = {}
     for site in struct:
         k = str(site.specie)
-        if k not in n_species.keys():
+        if k not in n_species:
             n_species.update({k: 0})
         n_species[k] += 1
 
-    n_s = len(n_species.keys())
+    n_s = len(n_species)
     n_config = 1
     for k in n_species:
         n_config *= n_species[k]
@@ -278,10 +278,10 @@ def find_closest_sites(struct, species_perturb):
     for k in range(n_config):
         denom = 1
         for j in range(n_s):
-            n = n_species[list(n_species.keys())[j]]
+            n = n_species[list(n_species)[j]]
             indices[j] = np.mod(k // denom, n)
             denom *= n
-        nn_s = [n_species[list(n_species.keys())[j]] for j in range(n_s)]
+        nn_s = [n_species[list(n_species)[j]] for j in range(n_s)]
         iindxs = [indices[j] + int(np.sum(nn_s[0:j])) for j in range(n_s)]
         indxs = []
         for j, jk in enumerate(n_species):
@@ -309,7 +309,7 @@ def init_linresp_input_sets(
     """
 
     # set LMAXMIX in user_incar_settings
-    if "LMAXMIX" not in user_incar_settings.keys():
+    if "LMAXMIX" not in user_incar_settings:
         lmaxmix_dict = {"p": 2, "d": 4, "f": 6}
         lmm = "p"
         for site in structure:
@@ -679,9 +679,9 @@ def incar(self):
             incar.update({"LDAUU": self.kwargs.get("user_incar_settings")["LDAUU"]})
             incar.update({"LDAUJ": self.kwargs.get("user_incar_settings")["LDAUJ"]})
 
-            incar["LDAUL"] = [incar["LDAUL"][key] for key in incar["LDAUL"].keys()]
-            incar["LDAUU"] = [incar["LDAUU"][key] for key in incar["LDAUU"].keys()]
-            incar["LDAUJ"] = [incar["LDAUJ"][key] for key in incar["LDAUJ"].keys()]
+            incar["LDAUL"] = [incar["LDAUL"][key] for key in incar["LDAUL"]]
+            incar["LDAUU"] = [incar["LDAUU"][key] for key in incar["LDAUU"]]
+            incar["LDAUJ"] = [incar["LDAUJ"][key] for key in incar["LDAUJ"]]
 
             incar["LDAU"] = self.kwargs.get("user_incar_settings")["LDAU"]
             incar["LDAUTYPE"] = self.kwargs.get("user_incar_settings")["LDAUTYPE"]

atomate/vasp/workflows/tests/test_approx_neb_workflow.py

@@ -110,7 +110,7 @@ def test_wf(self):
         self.assertEqual(len(aneb_doc["end_points"]), 2)
         for e in aneb_doc["end_points"]:
             self.assertIn("output", e)
-        self.assertEqual(len(aneb_doc["pathfinder"].keys()), 1)
+        self.assertEqual(len(aneb_doc["pathfinder"]), 1)
         self.assertIn("0+1", aneb_doc["pathfinder"])
         self.assertIn("0+1", aneb_doc["images"])
         self.assertEqual(len(aneb_doc["images"]["0+1"]), 3)