More pylint issues squashed

Author: gb119

Stoner/core/__init__.py

@@ -24,4 +24,4 @@
 from . import Typing, array, base, exceptions, utils
 from .array import DataArray
 from .base import RegexpDict, TypeHintedDict, metadataObject, string_to_type
-from .setas import setas as _setas
+from .setas import Setas as _setas

Stoner/core/array.py

@@ -9,12 +9,11 @@
 import copy
 
 import numpy as np
-import numpy.ma as ma
-
+from numpy import ma
 from ..compat import int_types
 from ..tools import AttributeStore, all_size, all_type, isiterable, isnone
 from .exceptions import StonerSetasError
-from .setas import setas as _setas
+from .setas import Setas as _setas
 
 
 class DataArray(ma.MaskedArray):

Stoner/core/data.py

@@ -55,6 +55,7 @@
 from ..analysis.fitting import functions as fitting
 from ..plot import PlotMixin
 from ..tools.decorators import class_modifier
+from ..tools.file import best_saver
 from . import methods
 
 
@@ -963,3 +964,52 @@ def load(cls, *args, **kargs):
             copy_into(ret, datafile)
             datafile.filetype = filetype
         return datafile
+
+    def save(self, filename=None, as_loaded=None, filetype=False, **kwargs):
+        """Save a string representation of the current self object into the file 'filename'.
+
+        Args:
+            self (Data):
+                Data object to work with if not being used as a bound method.
+
+        Keyword Arguments:
+            filename (string, bool or None):
+                Filename to save data as, if this is None then the current filename for the object is used. If this
+                is not set, then then a file dialog is used. If filename is False then a file dialog is forced.
+            as_loaded (bool,str):
+                If True, then the *Loaded as* key is inspected to see what the original class of the self was
+                and then this class' save method is used to save the data. If a str then
+                the keyword value is interpreted as the name of a subclass of the the current self.
+            filetype (bool):
+                Fallback is as_loaded is not provided.
+            **kwargs:
+                Other keyword arguments are ignored.
+
+        Returns:
+            self:
+                The current :py:class:`self` object
+        """
+        as_loaded = filetype if as_loaded is None else as_loaded
+        if filename is None:
+            filename = self.filename
+        if filename is None or (isinstance(filename, bool) and not filename):
+            # now go and ask for one
+            filename = file_dialog("w", self.filename, "Data")
+            if not filename:
+                raise RuntimeError("Cannot get filename to save")
+        match as_loaded:
+            case False:
+                saver = best_saver(filename, name=None, what="Data")
+                ret = saver(self, filename)
+                self.filename = ret.filename
+                return self
+            case True:
+                as_loaded = self.get("Loaded as", "self")
+            case str():
+                pass
+            case _:
+                raise TypeError("Unable to use loadtype to work out best saving routine.")
+        saver = best_saver(filename, name=as_loaded, what="Data")
+        ret = saver(self, filename)
+        self.filename = ret.filename
+        return self

Stoner/core/methods.py

@@ -13,7 +13,7 @@
 
 from ..compat import _pattern_type, int_types, str2bytes
 from ..tools import all_type, format_error, isiterable, operator, make_Class
-from ..tools.file import HDFFileManager, best_saver, file_dialog
+from ..tools.file import HDFFileManager, file_dialog
 from ..tools.widgets import RangeSelect
 from .array import DataArray
 
@@ -673,6 +673,59 @@ def unique(datafile, col, return_index=False, return_inverse=False):
     return np.unique(datafile.column(col), return_index, return_inverse)
 
 
+def _validate_index(datafile, index, replace):
+    match index:
+        case None | True:
+            index = datafile.shape[1]
+            replace = False
+        case int() if index == datafile.shape[1]:
+            replace = False
+        case _:
+            index = datafile.find_col(index)
+    return index, replace
+
+
+def _normalise_column_data(datafile, column_data, header, func_args):
+    """Sort out the data and get it into an array of values."""
+    if isinstance(column_data, list):
+        column_data = np.array(column_data)
+
+    if isinstance(column_data, DataArray) and header is None:
+        header = column_data.column_headers
+
+    match column_data:
+        case np.ndarray():
+            np_data = column_data
+        case _ if callable(column_data) and isinstance(func_args, dict):
+            new_data = [column_data(x, **func_args) for x in datafile]
+            np_data = np.array(new_data)
+        case _ if callable(column_data):
+            new_data = [column_data(x) for x in datafile]
+            np_data = np.array(new_data)
+        case _:
+            raise NotImplementedError
+
+    return np_data, header
+
+
+def _data_make_setas(setas, cw):
+    """Make setas based on the existing setas and the one supplied."""
+    setas = "." * cw if setas is None else setas
+
+    if isiterable(setas) and len(setas) == cw:
+        for s in setas:
+            if s not in ".-xyzuvwdefpqr":
+                raise TypeError(
+                    f"setas parameter should be a string or list of letter in the set xyzdefuvw.-, not {setas}"
+                )
+    else:
+        raise TypeError(
+            f"""setas parameter should be a string or list of letter the same length as the number of columns
+            being added in the set xyzdefuvw.-, not {setas}"""
+        )
+    return setas
+
+
 def add_column(datafile, column_data, header=None, index=None, func_args=None, replace=False, setas=None):
     """Append a column of data or inserts a column to a datafile instance.
 
@@ -704,50 +757,14 @@ def add_column(datafile, column_data, header=None, index=None, func_args=None, r
         Like most :py:class:`DataFile` methods, this method operates in-place in that it also modifies
         the original DataFile Instance as well as returning it.
     """
-    if index is None or isinstance(index, bool) and index:  # Enure index is set
-        index = datafile.shape[1]
-        replace = False
-    elif isinstance(index, int_types) and index == datafile.shape[1]:
-        replace = False
-    else:
-        index = datafile.find_col(index)
-
-    # Sort out the data and get it into an array of values.
-    if isinstance(column_data, list):
-        column_data = np.array(column_data)
-
-    if isinstance(column_data, DataArray) and header is None:
-        header = column_data.column_headers
 
-    if isinstance(column_data, np.ndarray):
-        np_data = column_data
-    elif callable(column_data):
-        if isinstance(func_args, dict):
-            new_data = [column_data(x, **func_args) for x in datafile]
-        else:
-            new_data = [column_data(x) for x in datafile]
-        np_data = np.array(new_data)
-    else:
-        return NotImplemented
+    index, replace = _validate_index(datafile, index, replace)
+    np_data, header = _normalise_column_data(datafile, column_data, header, func_args)
 
     # Sort out the sizes of the arrays
     np_data = np.atleast_2d(np_data).T
     cl, cw = np_data.shape
-
-    # Make setas
-    setas = "." * cw if setas is None else setas
-
-    if isiterable(setas) and len(setas) == cw:
-        for s in setas:
-            if s not in ".-xyzuvwdefpqr":
-                raise TypeError(
-                    f"setas parameter should be a string or list of letter in the set xyzdefuvw.-, not {setas}"
-                )
-    else:
-        raise TypeError(
-            f"""setas parameter should be a string or list of letter the same length as the number of columns
-            being added in the set xyzdefuvw.-, not {setas}"""
-        )
+    setas = _data_make_setas(setas, cw)
 
     # Make sure our current data is at least 2D and get its size
     match datafile.data.shape:
@@ -1161,52 +1178,6 @@ def rows(datafile, not_masked=False, reset=False):
         yield row
 
 
-def save(datafile, filename=None, as_loaded=None, filetype=False):
-    """Save a string representation of the current DataFile object into the file 'filename'.
-
-    Args:
-        datafile (Data):
-            Data object to work with if not being used as a bound method.
-        filename (string, bool or None):
-            Filename to save data as, if this is None then the current filename for the object is used. If this
-            is not set, then then a file dialog is used. If filename is False then a file dialog is forced.
-        as_loaded (bool,str):
-            If True, then the *Loaded as* key is inspected to see what the original class of the DataFile was
-            and then this class' save method is used to save the data. If a str then
-            the keyword value is interpreted as the name of a subclass of the the current DataFile.
-        filetype (bool):
-            Fallback is as_loaded is not provided.
-
-    Returns:
-        datafile:
-            The current :py:class:`DataFile` object
-    """
-    as_loaded = filetype if as_loaded is None else as_loaded
-    if filename is None:
-        filename = datafile.filename
-    if filename is None or (isinstance(filename, bool) and not filename):
-        # now go and ask for one
-        filename = file_dialog("w", datafile.filename, "Data")
-        if not filename:
-            raise RuntimeError("Cannot get filename to save")
-    match as_loaded:
-        case False:
-            saver = best_saver(filename, name=None, what="Data")
-            ret = saver(datafile, filename)
-            datafile.filename = ret.filename
-            return datafile
-        case True:
-            as_loaded = datafile.get("Loaded as", "DataFile")
-        case str():
-            pass
-        case _:
-            raise TypeError("Unable to use loadtype to work out best saving routine.")
-    saver = best_saver(filename, name=as_loaded, what="Data")
-    ret = saver(datafile, filename)
-    datafile.filename = ret.filename
-    return datafile
-
-
 def swap_column(datafile, *swp, headers_too=True, **kwargs):
     """Swap pairs of columns in the data.
 

Stoner/core/operators.py

@@ -257,7 +257,7 @@ def __read_iterable(self, reader):
             readline = reader.__next__
 
         else:
-            return NotImplemented
+            raise NotImplementedError
         row = readline().split("\t")
         if row[0].strip() == "TDI Format 1.5":
             fmt = 1.5

Stoner/core/property.py

@@ -123,8 +123,7 @@ def filename(self):
             self.filename = "Untitled"
         if isinstance(self._filename, path_types):
             return str(self._filename)
-        else:
-            return self._filename
+        return self._filename
 
     @filename.setter
     def filename(self, filename):

Stoner/core/setas.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 """setas module provides the setas class for DataFile and friends."""
-__all__ = ["setas"]
+__all__ = ["Setas"]
 import copy
 import re
 from collections.abc import Iterable, MutableMapping
@@ -13,7 +13,7 @@
 from .utils import decode_string
 
 
-class setas(MutableMapping):
+class Setas(MutableMapping):
     """A Class that provides a mechanism for managing the column assignments in a DataFile like object.
 
     Implements a MutableMapping bsed on the column_headers as the keys (with a few tweaks!).
@@ -163,9 +163,9 @@ def clone(self):
         """Create an exact copy of the current object."""
         cls = type(self)
         new = cls()
-        for attr in self.__dict__:
-            if not callable(self.__dict__[attr]):
-                new.__dict__[attr] = copy.deepcopy(self.__dict__[attr])
+        for attr, val in self.__dict__.items():
+            if not callable(val):
+                new.__dict__[attr] = copy.deepcopy(val)
         return new
 
     @property
@@ -281,10 +281,10 @@ def __call__(self, *args, **kargs):
         return_self = kargs.pop("_self", False)
         if not (args or kargs):  # New - bare call to setas will return the current value.
             return self.setas
-        if len(args) == 1 and isinstance(args[0], setas):
+        if len(args) == 1 and isinstance(args[0], Setas):
             args = list(args)
             args[0] = args[0].to_list()
-        if len(args) == 1 and not (isinstance(args[0], string_types + (setas,)) or isiterable(args[0])):
+        if len(args) == 1 and not (isinstance(args[0], string_types + (Setas,)) or isiterable(args[0])):
             raise SyntaxError(
                 f"setas should be called with eother a string, iterable object or setas object, not a {type(args[0])}"
             )
@@ -311,7 +311,7 @@ def __call__(self, *args, **kargs):
             if len(value) > self._size:
                 value = value[: self._size]
             elif len(value) < self._size:
-                value = [v for v in value]  # Ensure value is now a list
+                value = list(value)  # Ensure value is now a list
                 value.extend(list("." * (self._size - len(value))))
             value = value[: self._size]
             for i, v in enumerate(value):
@@ -347,8 +347,8 @@ def __eq__(self, other):
         """Check to see if this is the same object, or has the same headers and the same setas values."""
         ret = False
         if isinstance(other, string_types):  # Expand strings and convert to list
-            other = [c for c in decode_string(other)]
-        if not isinstance(other, setas):  # Ok, need to check whether items match
+            other = list(decode_string(other))
+        if not isinstance(other, Setas):  # Ok, need to check whether items match
             if isiterable(other) and len(other) <= self._size:
                 for m in self.setas[len(other) :]:  # Check that if other is short we don't have assignments there
                     if m != ".":
@@ -714,7 +714,7 @@ def unset(self, what=None):
 
     def update(self, other=(), **kwds):  # pylint:  disable=arguments-differ
         """Replace any assignments in self with assignments from other."""
-        if isinstance(other, setas):
+        if isinstance(other, Setas):
             other = other.to_dict()
         elif isinstance(other, tuple) and len(other) == 0:
             other = kwds