Move x Folder Into Tests Directory and Clean Up Test Structure

pytest.ini

@@ -3,3 +3,8 @@
 pythonpath = src
 filterwarnings =
     ignore::DeprecationWarning:jupyter_client.connect
+
+addopts = -ra
+python_files = test_*.py
+python_classes = Test*
+python_functions = test_*

src/plf/__init__.py

@@ -24,11 +24,5 @@
 
 
 """
-__all__ = [
-    "context",
-    "experiment",
-    "utils",
-    "lab",
-    "danger"
-]
 
+__all__ = ["context", "experiment", "utils", "lab", "danger"]

src/plf/_pipeline.py

@@ -9,16 +9,12 @@
 
 import traceback
 
-from .utils import (
-    load_component,
-    hash_args,
-    get_invalid_loc_queries,
-    Db,
-    Component)
+from .utils import load_component, hash_args, get_invalid_loc_queries, Db, Component
 
 from ._transfer_utils import TransferContext
 from .context import get_shared_data, set_shared_data
 
+
 class CompsDict(TypedDict):
     """
     fgfvv
@@ -41,12 +37,12 @@ def __init__(self, pplid=None):
         """
         Initialize the pipeline with default settings and empty components.
         """
-        self._paths = ['config']
+        self._paths = ["config"]
         self.settings = get_shared_data()
 
         self.pplid = None
         self.workflow = None
-        
+
         self.cnfg = None
         self._prepared = False
         self.__db = Db(db_path=f"{self.settings['data_path']}/ppls.db")
@@ -78,46 +74,43 @@ def _save_config(self) -> None:
             )
 
     def get_path(
-        self,
-        of: str,
-        pplid: Optional[str] = None,
-        args: Optional[Dict] = None
+        self, of: str, pplid: Optional[str] = None, args: Optional[Dict] = None
     ) -> str:
         """
-            Generate a standardized file path for various experiment artifacts.
-
-            Constructs and returns a file path based on the type of file (`of`), experiment ID,
-            epoch number, and batch index, where applicable. Automatically creates necessary
-            directories if they do not exist.
-
-            Parameters
-            ----------
-            of : str
-                The type of file to retrieve the path for. Supported values:
-                - "config": Configuration file path.
-                - "weight": Model weights file path.
-                - "gradient": Saved gradients file path.
-                - "history": Training history file path.
-                - "quick": Quick config file path.
-            pplid : str, optional
-                Experiment ID. If not provided, uses the currently set `self.pplid`.
-            epoch : int, optional
-                Epoch number. Required for weight and gradient file paths.
-                For weights, if not specified, the best epoch from config is used.
-            batch : int, optional
-                Batch index, required for gradient file paths.
-
-            Returns
-            -------
-            str
-                Full path to the specified artifact as a string with forward slashes.
-
-            Raises
-            ------
-            ValueError
-                If `pplid` is not set or invalid.
-                If required parameters (`epoch`, `batch`) are missing for gradient paths.
-                If the `of` argument is not one of the supported values.
+        Generate a standardized file path for various experiment artifacts.
+
+        Constructs and returns a file path based on the type of file (`of`), experiment ID,
+        epoch number, and batch index, where applicable. Automatically creates necessary
+        directories if they do not exist.
+
+        Parameters
+        ----------
+        of : str
+            The type of file to retrieve the path for. Supported values:
+            - "config": Configuration file path.
+            - "weight": Model weights file path.
+            - "gradient": Saved gradients file path.
+            - "history": Training history file path.
+            - "quick": Quick config file path.
+        pplid : str, optional
+            Experiment ID. If not provided, uses the currently set `self.pplid`.
+        epoch : int, optional
+            Epoch number. Required for weight and gradient file paths.
+            For weights, if not specified, the best epoch from config is used.
+        batch : int, optional
+            Batch index, required for gradient file paths.
+
+        Returns
+        -------
+        str
+            Full path to the specified artifact as a string with forward slashes.
+
+        Raises
+        ------
+        ValueError
+            If `pplid` is not set or invalid.
+            If required parameters (`epoch`, `batch`) are missing for gradient paths.
+            If the `of` argument is not one of the supported values.
         """
         pplid = pplid or self.pplid
         if not pplid:
@@ -130,10 +123,10 @@ def get_path(
 
         else:
             if self.workflow is None:
-                self.workflow = self.load_component(**self.cnfg['workflow'])
+                self.workflow = self.load_component(**self.cnfg["workflow"])
             path = self.workflow.get_path(of=of, pplid=pplid, args=args)
 
-        path = base_path / path 
+        path = base_path / path
         path = path.as_posix()
         os.makedirs(os.path.dirname(path), exist_ok=True)
         return path
@@ -149,36 +142,32 @@ def load(self, pplid: str, prepare: bool = False):
         with open(cfg_path, encoding="utf-8") as f:
             self.cnfg = json.load(f)
         self.pplid = pplid
-
 
         if prepare:
             self.prepare()
 
-
-
-
-
-
     def reset(self):
         """
         reset
         """
         self.pplid = None
-        
+
         self.settings = get_shared_data()
         self.cnfg = None
         self._prepared = False
         self.workflow = None
         self.__db = Db(db_path=f"{self.settings['data_path']}/ppls.db")
 
-    def load_component(self,loc: str, args: Optional[Dict[str, Any]] = None, setup: bool = True):
+    def load_component(
+        self, loc: str, args: Optional[Dict[str, Any]] = None, setup: bool = True
+    ):
         #  if lab_role nopt exists  then  add the key in   json file   at  self.settings['settings_path]
         if self.settings.get("lab_role") != "base":
             Tsx = TransferContext()
 
             loc = Tsx.map_loc(loc, pplid=self.pplid)
 
-        comp =  load_component(loc=loc, args=args, setup=setup)
+        comp = load_component(loc=loc, args=args, setup=setup)
         comp.P = self
         return comp
 
@@ -214,10 +203,7 @@ def verify(self, *, pplid: str = None, cnfg: Dict = None) -> Union[str, bool]:
             if len(result) > 0:
                 return pplid
         elif cnfg:
-            args = {
-                'workflow':cnfg['workflow'],
-                'args': cnfg['args']
-            }
+            args = {"workflow": cnfg["workflow"], "args": cnfg["args"]}
             args_hash = hash_args(args)
             rows = self.__db.query(
                 "SELECT pplid FROM ppls WHERE args_hash =? LIMIT 1", (args_hash,)
@@ -236,7 +222,7 @@ def _check_args(self, cnfg):
         t = self.verify(cnfg=cnfg)
         if t:
             raise ValueError(f"same configuration is already exists in: {t}")
-    
+
     def new(
         self,
         pplid: Optional[str] = None,
@@ -279,31 +265,28 @@ def new(
         if self.verify(pplid=pplid):
             raise ValueError(f"{pplid} is already exists  try  different id")
         self._check_args(args)
-        t = {
-            "pplid": pplid,
-            **args
-        }
+        t = {"pplid": pplid, **args}
 
         self.pplid = pplid
         self.cnfg = t
 
         try:
-            self.workflow = self.load_component(**args['workflow'])
-            self.workflow.new(args['args'])
+            self.workflow = self.load_component(**args["workflow"])
+            self.workflow.new(args["args"])
         except:
             traceback.print_exc()
-            
+
             raise
-        
+
         self.__db.execute(
             "INSERT INTO ppls (pplid, args_hash) VALUES (?, ?)",
             (pplid, hash_args(args)),
         )
 
-        self._save_config()        
+        self._save_config()
         if prepare:
             self.prepare()
-    
+
     def prepare(self) -> None:
         """
         Prepare the experiment by loading model, optimizer, metrics, loss, and data loaders.
@@ -333,15 +316,12 @@ def prepare(self) -> None:
 
                 self.cnfg = Tsx.map_cnfg(self.cnfg)
 
-
-            self.workflow = self.load_component(**self.cnfg['workflow'])
+            self.workflow = self.load_component(**self.cnfg["workflow"])
             self._prepared = self.workflow.prepare()
 
-
-
         except:
             traceback.print_exc()
-   
+
     def run(self) -> None:
 
         if not self._prepared:
@@ -380,56 +360,58 @@ def is_running(self):
         if rows:
             return rows[0][0]
         return False
-    
-    @property    
+
+    @property
     def should_running(self):
         rows = self.__db.query(
             "SELECT parity FROM runnings WHERE pplid = ?", (self.pplid,)
         )
-        if rows and rows[0][0]=='stop':
+        if rows and rows[0][0] == "stop":
             return False
         return True
 
     def stop_running(self):
         logid = self.is_running()
         if logid:
             self.__db.execute(
-                "UPDATE runnings SET parity = ? WHERE logid = ?", ('stop', logid)
+                "UPDATE runnings SET parity = ? WHERE logid = ?", ("stop", logid)
+            )
+            print(
+                f"ppid:{self.pplid} will be stopped at logid:{logid} after current iteration"
             )
-            print(f"ppid:{self.pplid} will be stopped at logid:{logid} after current iteration")
         else:
             print("it is not running anywhere")
-    
+
     @property
     def paths(self):
         artifs = self._paths
         if self.workflow is None and self.pplid:
-            self.workflow = self.load_component(**self.cnfg['workflow'])
+            self.workflow = self.load_component(**self.cnfg["workflow"])
         if self.workflow:
             artifs += self.workflow.paths
         return artifs
-   
+
     def clean(self):
-        if self.cnfg==None:
+        if self.cnfg == None:
             print("Empty Pipeline")
             return
         try:
             if self.workflow is None:
-                self.workflow = self.load_component(**self.cnfg['workflow'])
+                self.workflow = self.load_component(**self.cnfg["workflow"])
             self.workflow.clean()
         except:
             traceback.print_exc()
 
     def status(self):
-        if self.cnfg==None:
+        if self.cnfg == None:
             print("Empty Pipeline")
             return
         try:
             if self.workflow is None:
-                self.workflow = self.load_component(**self.cnfg['workflow'])
+                self.workflow = self.load_component(**self.cnfg["workflow"])
             return self.workflow.status()
         except:
             traceback.print_exc()
 
-from copy import deepcopy
 
+from copy import deepcopy