Handle pathlib.Path in Attrdict.from_yaml

src/calliope/cli.py

@@ -182,7 +182,7 @@ def new(path, template, debug):
     with format_exceptions(debug):
         if template is None:
             template = "national_scale"
-        source_path = examples._PATHS[template]
+        source_path = examples.EXAMPLE_MODEL_DIR / template
         click.echo("Copying {} template to target directory: {}".format(template, path))
         shutil.copytree(source_path, path)
 

src/calliope/core/attrdict.py

@@ -177,7 +177,7 @@ def from_yaml(cls, f, resolve_imports=True):
             overrides definitions in the imported file.
 
         """
-        if isinstance(f, str) or isinstance(f, Path):
+        if isinstance(f, (str, Path)):
             with open(
                 f,
                 "r",

src/calliope/core/model.py

@@ -58,7 +58,7 @@ class Model(object):
 
     def __init__(
         self,
-        model_definition: Optional[Union[str, dict]] = None,
+        model_definition: Optional[Union[str, Path, dict]] = None,
         model_data: Optional[xarray.Dataset] = None,
         debug: bool = False,
         scenario: Optional[str] = None,
@@ -71,7 +71,7 @@ def __init__(
         configuration file or a dict fully specifying the model.
 
         Args:
-            config (Optional[Union[str, dict]]):
+            config (Optional[Union[str, Path, dict]]):
                 If str, must be the path to a model configuration file.
                 If dict or AttrDict, must fully specify the model.
             model_data (Optional[xarray.Dataset], optional):
@@ -104,8 +104,8 @@ def __init__(
         # try to set logging output format assuming python interactive. Will
         # use CLI logging format if model called from CLI
         log_time(LOGGER, self._timings, "model_creation", comment="Model: initialising")
-        if isinstance(model_definition, str):
-            self._model_def_path = model_definition
+        if isinstance(model_definition, (str, Path)):
+            self._model_def_path = Path(model_definition).as_posix()
             model_run, debug_data = model_run_from_yaml(
                 model_definition,
                 scenario,

src/calliope/core/util/tools.py

@@ -6,6 +6,7 @@
 import importlib
 import os
 import sys
+from pathlib import Path
 from typing import TypeVar
 
 import jsonschema
@@ -67,7 +68,7 @@ def relative_path(base_path_file, path):
 
     """
     # Check if base_path_file is a string because it might be an AttrDict
-    if not os.path.isabs(path) and isinstance(base_path_file, str):
+    if not os.path.isabs(path) and isinstance(base_path_file, (str, Path)):
         path = os.path.join(os.path.dirname(base_path_file), path)
     return path
 

src/calliope/preprocess/model_run.py

@@ -13,6 +13,7 @@
 import itertools
 import logging
 import os
+from pathlib import Path
 from typing import Optional
 
 import pandas as pd
@@ -64,7 +65,7 @@ def model_run_from_yaml(
 
     """
     config = AttrDict.from_yaml(model_file)
-    config._model_def_path = model_file
+    config._model_def_path = Path(model_file).as_posix()
 
     config_with_overrides, debug_comments, overrides, scenario = apply_overrides(
         config, scenario=scenario, override_dict=override_dict

tests/test_core_preprocess.py

@@ -1479,18 +1479,20 @@ def model_national(self, load_timeseries_from_dataframes):
         """
         if load_timeseries_from_dataframes:
             # Create dictionary with dataframes
-            timeseries_data_path = os.path.join(
-                calliope.examples._PATHS["national_scale"], "timeseries_data/"
+            timeseries_data_path = (
+                calliope.examples.EXAMPLE_MODEL_DIR
+                / "national_scale"
+                / "timeseries_data"
             )
             timeseries_dataframes = {}
             timeseries_dataframes["csp_resource"] = pd.read_csv(
-                os.path.join(timeseries_data_path, "csp_resource.csv"), index_col=0
+                timeseries_data_path / "csp_resource.csv", index_col=0
             )
             timeseries_dataframes["demand_1"] = pd.read_csv(
-                os.path.join(timeseries_data_path, "demand-1.csv"), index_col=0
+                timeseries_data_path / "demand-1.csv", index_col=0
             )
             timeseries_dataframes["demand_2"] = pd.read_csv(
-                os.path.join(timeseries_data_path, "demand-2.csv"), index_col=0
+                timeseries_data_path / "demand-2.csv", index_col=0
             )
             # Create override dict telling calliope to load timeseries from df
             override_dict = {