Metadata-Version: 1.1
Name: infseq
Version: 0.2
Summary: Lazy infinite cached sequences
Home-page: https://github.com/mitya57/infseq
Author: Dmitry Shachnev
Author-email: mitya57@gmail.com
License: BSD
Description: 
        .. image:: https://api.travis-ci.org/mitya57/infseq.svg
           :target: https://travis-ci.org/mitya57/infseq
           :alt: Travis CI status
        
        Infinite sequences for Python
        =============================
        
        The ``infseq`` module implements cached lazy infinite sequences for Python 3.
        
        Here, the word “lazy” means that values of the sequence will never be calculated
        unless they are really used, and the word “cached” means that every value will
        be calculated no more than once.
        
        Sequences can contain items of any type — such as numbers, strings or even
        other sequences.
        
        Using this module is pretty straightforward — everything just works. Here are
        some usage examples:
        
        Creating sequences
        ------------------
        
        .. code:: python
        
          >>> from infseq import InfSequence
          >>> InfSequence(5)
          <InfSequence: 5 5 5 5 5 5 ...>
          >>> InfSequence(5, 6, ...)
          <InfSequence: 5 6 7 8 9 10 ...>
          >>> InfSequence(lambda index: index * 2 + 1)
          <InfSequence: 1 3 5 7 9 11 ...>
          >>> InfSequence.geometric_progression(3)
          <InfSequence: 1 3 9 27 81 243 ...>
          >>> InfSequence.cycle('a', 'b', 'c')
          <InfSequence: 'a' 'b' 'c' 'a' 'b' 'c' ...>
          >>> InfSequence.fibonacci()
          <InfSequence: 0 1 1 2 3 5 ...>
        
        **Note**: for the ease of debugging the first six values are calculated when
        ``repr()`` is called on the sequence. If you just create the sequence without
        printing it, the values are not calculated. The number of items can be adjusted
        by modifying the ``infseq.REPR_VALUES`` number (it is set to 6 by default).
        
        Retrieving the values
        ---------------------
        
        .. code:: python
        
          >>> a = InfSequence.geometric_progression(2)
          >>> a
          <InfSequence: 1 2 4 8 16 32 ...>
          >>> a[10]
          1024
          >>> a.partial_sum(10)  # a[0] + ... + a[9]
          1023
          >>> a.partial_sum(4, 10)  # sum(a[i] for i in range(4, 10))
          1008
          >>> a.partial_product(5)  # a[0] * ... * a[4]
          1024
        
        Slicing and prepending elements
        -------------------------------
        
        .. code:: python
        
          >>> a[5:]
          <InfSequence: 32 64 128 256 512 1024 ...>
          >>> a[::2]
          <InfSequence: 1 4 16 64 256 1024 ...>
          >>> list(a[5:10])  # a[5:10] returns a map object, because of laziness
          [32, 64, 128, 256, 512]
          >>> list(a[4::-1])  # reverse slices also work
          [16, 8, 4, 2, 1]
          >>> (5, 7) + a
          <InfSequence: 5 7 1 2 4 8 ...>
        
        Arithmetic operations
        ---------------------
        
        .. code:: python
        
          >>> b = InfSequence(1, 2, ...)
          >>> b
          <InfSequence: 1 2 3 4 5 6 ...>
          >>> b * 2
          <InfSequence: 2 4 6 8 10 12 ...>
          >>> b ** 2
          <InfSequence: 1 4 9 16 25 36 ...>
          >>> a + b
          <InfSequence: 2 4 7 12 21 38 ...>
        
        Applying any functions
        ----------------------
        
        .. code:: python
        
          >>> c = InfSequence.geometric_progression(9)
          >>> c
          <InfSequence: 1 9 81 729 6561 59049 ...>
          >>> import math
          >>> c.apply_function(math.sqrt)
          <InfSequence: 1.0 3.0 9.0 27.0 81.0 243.0 ...>
        
        Using the ``accumulate`` method
        -------------------------------
        
        The ``accumulate`` method returns a sequence of partial sums of the original
        sequence (similar to itertools.accumulate_)::
        
          result[0] = a[0]
          result[1] = a[0] + a[1]
          result[2] = a[0] + a[1] + a[2]
          ...
        
        .. _itertools.accumulate: https://docs.python.org/3/library/itertools.html#itertools.accumulate
        
        If a custom function is passed as an argument, it is used to do
        the reducing instead of the sum function.
        
        In the examples below we can get the sequence of *n(n+1)/2* and the sequence of
        *n!* using this method:
        
        .. code:: python
        
          >>> from operator import mul
          >>> b
          <InfSequence: 1 2 3 4 5 6 ...>
          >>> b.accumulate()
          <InfSequence: 1 3 6 10 15 21 ...>
          >>> b.accumulate(mul)
          <InfSequence: 1 2 6 24 120 720 ...>
        
        Using the matrix multiplication operator
        ----------------------------------------
        
        If you are using Python 3.5+, you can use the new “matrix multiplication”
        operator that was introduced in that version.
        
        The expression ``a @ b`` will produce the following result::
        
          result[0] = a[0] * b[0]
          result[1] = a[0] * b[1] + a[1] * b[0]
          result[2] = a[0] * b[2] + a[1] * b[1] + a[2] * b[0]
          ...
        
        Example:
        
        .. code:: python
        
          >>> InfSequence(0, 2, ...) @ InfSequence(1)
          <InfSequence: 1 4 9 16 25 36 ...>
        
        Installing the module and running the tests
        -------------------------------------------
        
        The module is available on PyPI_. To install the module, simply use::
        
          pip3 install infseq
        
        The source code is hosted on GitHub_.
        
        To run the doctests in this module, use::
        
          python3 -m doctest ./README.rst
        
        .. _PyPI: https://pypi.python.org/pypi/infseq
        .. _GitHub: https://github.com/mitya57/infseq
        
Platform: any
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3 :: Only
