calcpy

Implementations of basic calculations in Python.

Installation

pip install --upgrade calcpy

Set-Alike APIs

Set-alike APIs operate objects with original order reserved and optional customized comparison function.

>>> from calcpy import unique
>>> unique([4, 3, 7, 3, 4])
[4, 3, 7]

List of APIs:

• calcpy.unique(values, matcher=None) Remove duplicated entries.
• calcpy.concat(*args, matcher=None) Concatenate.
• calcpy.union(*args, matcher=None) Union.
• calcpy.intersect(*args, matcher=None) Intersection.
• calcpy.exclude(arg, *args, matcher=None) Remove follow-up arguments from the first.
• calcpy.xor(*args, matcher=None) Exclusive-or of follow-up parameters from the first parameter.
• calcpy.eq(*args, matcher=None) Check whether parameters are all equal.
• calcpy.ne(*args, matcher=None) Check whether parameters are all distinct.

Supported object types

• list
• tuple
• set
• np.ndarray
• pd.Series
• pd.DataFrame
• others

On keyword parameter matcher: The keyword parameter matcher is for customized comparison function. By default, it is None, which uses the default way to compare two objects, i.e. compare them as a whole. We can write customized binary functions to compare two objects. For example, we can compare the equality of two np.ndarrays using np.array_equal, or use the following customized function lower_matcher to compare two strs according to their lowercases:

>>> def lower_matcher(loper, roper):
...     return loper.lower() == roper.lower()
...
>>> from calcpy import eq
>>> eq("Hello", "hello", "HELLO", matcher=lower_matcher)
True

calcpy also provide a class calcpy.matcher.PandasFrameMatcher for comparing pd.Seriess and pd.DataFrames.

• calcpy.matcher.PandasFrameMatcher() Compare whether pandas objects as a whole. The same as loper.equals(roper).

• calcpy.matcher.PandasFrameMatcher("index") Compare index values of pandas objects.

• calcpy.matcher.PandasFrameMatcher("values") Compare values of pandas objects, ignoring the index values.

• calcpy.matcher.PandasFrameMatcher("series") Compare pd.DataFrame in a pd.Series way. By default, it is left_series.equals(right_series).

For pd.DataFrame, it also provides a keyword parameter axis. It compares each row when it is set to 0 (the default value) or 'index', and compares each column if axis is set to 1 or 'column'.

Sequence APIs

Repetend Analysis

• calcpy.sequence.min_repetend_len(): Get the mimimum length of repetends.

Usage Example:

>>> from calcpy.sequence import min_repetend_len
>>> min_repetend_len([1, 2, 3, 1, 2, 3, 1, 2])
3

Sequence Generator

• calcpy.sequence.A276128(): Generator for the sequence OEIS A276128.

Usage Example:

>>> from calcpy.sequence import A276128
>>> print(list(A276128(14)))
[0, 0, 1, 2, 4, 6, 8, 10, 12, 14, 16, 18, 21, 24]