Clean type annotation

marisco/__init__.py

@@ -1 +1 @@
-__version__ = "0.2.0"
+__version__ = "0.3.0"

marisco/callbacks.py

@@ -15,7 +15,7 @@
 import pandas as pd
 from .configs import cfg, cdl_cfg, grp_names
 from functools import partial 
-from typing import List, Dict, Callable, Tuple
+from typing import List, Dict, Callable, Tuple, Any, Optional
 from pathlib import Path 
 
 from .configs import get_lut, nuc_lut_path
@@ -28,7 +28,10 @@ class Callback():
     order = 0
 
 # %% ../nbs/api/callbacks.ipynb 7
-def run_cbs(cbs, obj=None):
+def run_cbs(
+    cbs: List[Callback], # List of callbacks to run
+    obj: Any # Object to pass to the callbacks
+    ):
     "Run the callbacks in the order they are specified."
     for cb in sorted(cbs, key=attrgetter('order')):
         if cb.__doc__: obj.logs.append(cb.__doc__)
@@ -37,16 +40,16 @@ def run_cbs(cbs, obj=None):
 # %% ../nbs/api/callbacks.ipynb 8
 class Transformer():
     def __init__(self, 
-                 dfs:pd.DataFrame, # Dictionary of DataFrames to transform
-                 cbs:list=None, # List of callbacks to run
-                 inplace:bool=False # Whether to modify the dataframes in place
+                 dfs: Dict[str, pd.DataFrame], # Dictionary of DataFrames to transform
+                 cbs: Optional[List[Callback]]=None, # List of callbacks to run
+                 inplace: bool=False # Whether to modify the dataframes in place
                  ): 
         "Transform the dataframes according to the specified callbacks."
         fc.store_attr()
         self.dfs = dfs if inplace else {k: v.copy() for k, v in dfs.items()}
         self.logs = []
 
-    def unique(self, col_name):
+    def unique(self, col_name: str) -> np.ndarray:
         "Distinct values of a specific column present in all groups."
         columns = [df.get(col_name) for df in self.dfs.values() if df.get(col_name) is not None]
         values = np.concatenate(columns) if columns else []
@@ -60,8 +63,8 @@ def __call__(self):
 # %% ../nbs/api/callbacks.ipynb 15
 class SanitizeLonLatCB(Callback):
     "Drop row when both longitude & latitude equal 0. Drop unrealistic longitude & latitude values. Convert longitude & latitude `,` separator to `.` separator."
-    def __init__(self, verbose=False): fc.store_attr()
-    def __call__(self, tfm):
+    def __init__(self, verbose: bool=False): fc.store_attr()
+    def __call__(self, tfm: Transformer):
         for grp, df in tfm.dfs.items():
             " Convert `,` separator to `.` separator"
             df['lon'] = [float(str(x).replace(',', '.')) for x in df['lon']]
@@ -84,8 +87,8 @@ def __call__(self, tfm):
 # %% ../nbs/api/callbacks.ipynb 20
 class AddSampleTypeIdColumnCB(Callback):
     def __init__(self, 
-                 cdl_cfg:Callable=cdl_cfg, # Callable to get the CDL config dictionary
-                 col_name:str='samptype_id'
+                 cdl_cfg: Callable=cdl_cfg, # Callable to get the CDL config dictionary
+                 col_name: str='samptype_id' # Column name to store the sample type id
                  ): 
         "Add a column with the sample type id as defined in the CDL."
         fc.store_attr()
@@ -97,16 +100,16 @@ def __call__(self, tfm):
 # %% ../nbs/api/callbacks.ipynb 23
 class AddNuclideIdColumnCB(Callback):
     def __init__(self, 
-                 col_value:str, # Column name containing the nuclide name
-                 lut_fname_fn:callable=nuc_lut_path, # Function returning the lut path
-                 col_name:str='nuclide_id' # Column name to store the nuclide id
+                 col_value: str, # Column name containing the nuclide name
+                 lut_fname_fn: Callable=nuc_lut_path, # Function returning the lut path
+                 col_name: str='nuclide_id' # Column name to store the nuclide id
                  ): 
         "Add a column with the nuclide id."
         fc.store_attr()
         self.lut = get_lut(lut_fname_fn().parent, lut_fname_fn().name, 
                            key='nc_name', value='nuclide_id', reverse=False)
 
-    def __call__(self, tfm):
+    def __call__(self, tfm: Transformer):
         for grp, df in tfm.dfs.items(): 
             df[self.col_name] = df[self.col_value].map(self.lut)
 
@@ -148,9 +151,9 @@ def _remap_value(self, value: str) -> Any:
 class LowerStripNameCB(Callback):
     "Convert values to lowercase and strip any trailing spaces."
     def __init__(self, 
-                 col_src:str, # Source column name e.g. 'Nuclide'
-                 col_dst:str=None, # Destination column name
-                 fn_transform:Callable=lambda x: x.lower().strip() # Transformation function
+                 col_src: str, # Source column name e.g. 'Nuclide'
+                 col_dst: str=None, # Destination column name
+                 fn_transform: Callable=lambda x: x.lower().strip() # Transformation function
                  ):
         fc.store_attr()
         self.__doc__ = f"Convert values from '{col_src}' to lowercase, strip spaces, and store in '{col_dst}'."
@@ -168,7 +171,7 @@ def __call__(self, tfm):
 class RemoveAllNAValuesCB(Callback):
     "Remove rows with all NA values."
     def __init__(self, 
-                 cols_to_check:dict # A dictionary with the sample type as key and the column name to check as value
+                 cols_to_check: Dict[str, str] # A dictionary with the sample type as key and the column name to check as value
                 ):
         fc.store_attr()
 
@@ -180,9 +183,13 @@ def __call__(self, tfm):
 
 # %% ../nbs/api/callbacks.ipynb 34
 class ReshapeLongToWide(Callback):
-    def __init__(self, columns=['nuclide'], values=['value'], 
-                 num_fill_value=-999, str_fill_value='STR FILL VALUE'):
-        "Convert data from long to wide with renamed columns."
+    "Convert data from long to wide with renamed columns."
+    def __init__(self, 
+                 columns: List[str]=['nuclide'], # Columns to use as index
+                 values: List[str]=['value'], # Columns to use as values
+                 num_fill_value: int=-999, # Fill value for numeric columns
+                 str_fill_value='STR FILL VALUE'
+                 ):
         fc.store_attr()
         self.derived_cols = self._get_derived_cols()
 
@@ -234,8 +241,10 @@ def __call__(self, tfm):
 
 # %% ../nbs/api/callbacks.ipynb 36
 class CompareDfsAndTfmCB(Callback):
-    def __init__(self, dfs: Dict[str, pd.DataFrame]): 
-        "Create a dataframe of dropped data. Data included in the `dfs` not in the `tfm`."
+    "Create a dataframe of dropped data. Data included in the `dfs` not in the `tfm`."
+    def __init__(self, 
+                 dfs: Dict[str, pd.DataFrame] # Original dataframes
+                 ): 
         fc.store_attr()
 
     def __call__(self, tfm: Transformer) -> None:
@@ -271,8 +280,13 @@ def _compute_stats(self,
 
 # %% ../nbs/api/callbacks.ipynb 41
 class EncodeTimeCB(Callback):
-    "Encode time as `int` representing seconds since xxx"    
-    def __init__(self, cfg , verbose=False): fc.store_attr()
+    "Encode time as `int` representing seconds since xxx."    
+    def __init__(self, 
+                 cfg: dict, # Configuration dictionary
+                 verbose: bool=False # Whether to print the number of invalid time entries
+                 ): 
+        fc.store_attr()
+
     def __call__(self, tfm): 
         def format_time(x): 
             return date2num(x, units=self.cfg['units']['time'])

nbs/api/callbacks.ipynb

@@ -37,7 +37,7 @@
     "import pandas as pd\n",
     "from marisco.configs import cfg, cdl_cfg, grp_names\n",
     "from functools import partial \n",
-    "from typing import List, Dict, Callable, Tuple\n",
+    "from typing import List, Dict, Callable, Tuple, Any, Optional\n",
     "from pathlib import Path \n",
     "\n",
     "from marisco.configs import get_lut, nuc_lut_path\n",
@@ -50,7 +50,16 @@
    "execution_count": null,
    "id": "91324c91",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The autoreload extension is already loaded. To reload it, use:\n",
+      "  %reload_ext autoreload\n"
+     ]
+    }
+   ],
    "source": [
     "#| hide\n",
     "from marisco.configs import cdl_cfg, CONFIGS_CDL\n",
@@ -97,7 +106,10 @@
    "outputs": [],
    "source": [
     "#| exports\n",
-    "def run_cbs(cbs, obj=None):\n",
+    "def run_cbs(\n",
+    "    cbs: List[Callback], # List of callbacks to run\n",
+    "    obj: Any # Object to pass to the callbacks\n",
+    "    ):\n",
     "    \"Run the callbacks in the order they are specified.\"\n",
     "    for cb in sorted(cbs, key=attrgetter('order')):\n",
     "        if cb.__doc__: obj.logs.append(cb.__doc__)\n",
@@ -114,16 +126,16 @@
     "#| exports\n",
     "class Transformer():\n",
     "    def __init__(self, \n",
-    "                 dfs:pd.DataFrame, # Dictionary of DataFrames to transform\n",
-    "                 cbs:list=None, # List of callbacks to run\n",
-    "                 inplace:bool=False # Whether to modify the dataframes in place\n",
+    "                 dfs: Dict[str, pd.DataFrame], # Dictionary of DataFrames to transform\n",
+    "                 cbs: Optional[List[Callback]]=None, # List of callbacks to run\n",
+    "                 inplace: bool=False # Whether to modify the dataframes in place\n",
     "                 ): \n",
     "        \"Transform the dataframes according to the specified callbacks.\"\n",
     "        fc.store_attr()\n",
     "        self.dfs = dfs if inplace else {k: v.copy() for k, v in dfs.items()}\n",
     "        self.logs = []\n",
     "            \n",
-    "    def unique(self, col_name):\n",
+    "    def unique(self, col_name: str) -> np.ndarray:\n",
     "        \"Distinct values of a specific column present in all groups.\"\n",
     "        columns = [df.get(col_name) for df in self.dfs.values() if df.get(col_name) is not None]\n",
     "        values = np.concatenate(columns) if columns else []\n",
@@ -153,7 +165,7 @@
    "source": [
     "class TestCB(Callback):\n",
     "    \"A test callback to add 1 to the depth.\"\n",
-    "    def __call__(self, tfm):\n",
+    "    def __call__(self, tfm: Transformer):\n",
     "        for grp, df in tfm.dfs.items(): \n",
     "            df['depth'] = df['depth'].apply(lambda x: x+1)"
    ]
@@ -209,8 +221,8 @@
     "#| exports\n",
     "class SanitizeLonLatCB(Callback):\n",
     "    \"Drop row when both longitude & latitude equal 0. Drop unrealistic longitude & latitude values. Convert longitude & latitude `,` separator to `.` separator.\"\n",
-    "    def __init__(self, verbose=False): fc.store_attr()\n",
-    "    def __call__(self, tfm):\n",
+    "    def __init__(self, verbose: bool=False): fc.store_attr()\n",
+    "    def __call__(self, tfm: Transformer):\n",
     "        for grp, df in tfm.dfs.items():\n",
     "            \" Convert `,` separator to `.` separator\"\n",
     "            df['lon'] = [float(str(x).replace(',', '.')) for x in df['lon']]\n",
@@ -298,8 +310,8 @@
     "#| exports\n",
     "class AddSampleTypeIdColumnCB(Callback):\n",
     "    def __init__(self, \n",
-    "                 cdl_cfg:Callable=cdl_cfg, # Callable to get the CDL config dictionary\n",
-    "                 col_name:str='samptype_id'\n",
+    "                 cdl_cfg: Callable=cdl_cfg, # Callable to get the CDL config dictionary\n",
+    "                 col_name: str='samptype_id' # Column name to store the sample type id\n",
     "                 ): \n",
     "        \"Add a column with the sample type id as defined in the CDL.\"\n",
     "        fc.store_attr()\n",
@@ -343,16 +355,16 @@
     "#| exports\n",
     "class AddNuclideIdColumnCB(Callback):\n",
     "    def __init__(self, \n",
-    "                 col_value:str, # Column name containing the nuclide name\n",
-    "                 lut_fname_fn:callable=nuc_lut_path, # Function returning the lut path\n",
-    "                 col_name:str='nuclide_id' # Column name to store the nuclide id\n",
+    "                 col_value: str, # Column name containing the nuclide name\n",
+    "                 lut_fname_fn: Callable=nuc_lut_path, # Function returning the lut path\n",
+    "                 col_name: str='nuclide_id' # Column name to store the nuclide id\n",
     "                 ): \n",
     "        \"Add a column with the nuclide id.\"\n",
     "        fc.store_attr()\n",
     "        self.lut = get_lut(lut_fname_fn().parent, lut_fname_fn().name, \n",
     "                           key='nc_name', value='nuclide_id', reverse=False)\n",
     "        \n",
-    "    def __call__(self, tfm):\n",
+    "    def __call__(self, tfm: Transformer):\n",
     "        for grp, df in tfm.dfs.items(): \n",
     "            df[self.col_name] = df[self.col_value].map(self.lut)"
    ]
@@ -437,9 +449,9 @@
     "class LowerStripNameCB(Callback):\n",
     "    \"Convert values to lowercase and strip any trailing spaces.\"\n",
     "    def __init__(self, \n",
-    "                 col_src:str, # Source column name e.g. 'Nuclide'\n",
-    "                 col_dst:str=None, # Destination column name\n",
-    "                 fn_transform:Callable=lambda x: x.lower().strip() # Transformation function\n",
+    "                 col_src: str, # Source column name e.g. 'Nuclide'\n",
+    "                 col_dst: str=None, # Destination column name\n",
+    "                 fn_transform: Callable=lambda x: x.lower().strip() # Transformation function\n",
     "                 ):\n",
     "        fc.store_attr()\n",
     "        self.__doc__ = f\"Convert values from '{col_src}' to lowercase, strip spaces, and store in '{col_dst}'.\"\n",
@@ -510,7 +522,7 @@
     "class RemoveAllNAValuesCB(Callback):\n",
     "    \"Remove rows with all NA values.\"\n",
     "    def __init__(self, \n",
-    "                 cols_to_check:dict # A dictionary with the sample type as key and the column name to check as value\n",
+    "                 cols_to_check: Dict[str, str] # A dictionary with the sample type as key and the column name to check as value\n",
     "                ):\n",
     "        fc.store_attr()\n",
     "\n",
@@ -538,9 +550,13 @@
    "source": [
     "#| exports\n",
     "class ReshapeLongToWide(Callback):\n",
-    "    def __init__(self, columns=['nuclide'], values=['value'], \n",
-    "                 num_fill_value=-999, str_fill_value='STR FILL VALUE'):\n",
-    "        \"Convert data from long to wide with renamed columns.\"\n",
+    "    \"Convert data from long to wide with renamed columns.\"\n",
+    "    def __init__(self, \n",
+    "                 columns: List[str]=['nuclide'], # Columns to use as index\n",
+    "                 values: List[str]=['value'], # Columns to use as values\n",
+    "                 num_fill_value: int=-999, # Fill value for numeric columns\n",
+    "                 str_fill_value='STR FILL VALUE'\n",
+    "                 ):\n",
     "        fc.store_attr()\n",
     "        self.derived_cols = self._get_derived_cols()\n",
     "    \n",
@@ -616,8 +632,10 @@
    "source": [
     "#| exports\n",
     "class CompareDfsAndTfmCB(Callback):\n",
-    "    def __init__(self, dfs: Dict[str, pd.DataFrame]): \n",
-    "        \"Create a dataframe of dropped data. Data included in the `dfs` not in the `tfm`.\"\n",
+    "    \"Create a dataframe of dropped data. Data included in the `dfs` not in the `tfm`.\"\n",
+    "    def __init__(self, \n",
+    "                 dfs: Dict[str, pd.DataFrame] # Original dataframes\n",
+    "                 ): \n",
     "        fc.store_attr()\n",
     "        \n",
     "    def __call__(self, tfm: Transformer) -> None:\n",
@@ -727,8 +745,13 @@
    "source": [
     "#| exports\n",
     "class EncodeTimeCB(Callback):\n",
-    "    \"Encode time as `int` representing seconds since xxx\"    \n",
-    "    def __init__(self, cfg , verbose=False): fc.store_attr()\n",
+    "    \"Encode time as `int` representing seconds since xxx.\"    \n",
+    "    def __init__(self, \n",
+    "                 cfg: dict, # Configuration dictionary\n",
+    "                 verbose: bool=False # Whether to print the number of invalid time entries\n",
+    "                 ): \n",
+    "        fc.store_attr()\n",
+    "        \n",
     "    def __call__(self, tfm): \n",
     "        def format_time(x): \n",
     "            return date2num(x, units=self.cfg['units']['time'])\n",

settings.ini

@@ -1,7 +1,7 @@
 [DEFAULT]
 repo = marisco
 lib_name = marisco
-version = 0.2.0
+version = 0.3.0
 min_python = 3.7
 license = apache2
 doc_path = _docs