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SeqTools-1.2.0


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توضیحات

A library for transparent transformation of indexable containers (lists, etc.)
ویژگی مقدار
سیستم عامل OS Independent
نام فایل SeqTools-1.2.0
نام SeqTools
نسخه کتابخانه 1.2.0
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Nicolas Granger
ایمیل نویسنده nicolas.granger.m@gmail.com
آدرس صفحه اصلی https://github.com/nlgranger/SeqTools
آدرس اینترنتی https://pypi.org/project/SeqTools/
مجوز Mozilla Public License 2.0 (MPL 2.0)
.. image:: https://badge.fury.io/py/SeqTools.svg :target: https://github.com/nlgranger/SeqTools :alt: PyPi package .. image:: https://circleci.com/gh/nlgranger/SeqTools.svg?style=shield :target: https://circleci.com/gh/nlgranger/SeqTools :alt: CircleCI Continuous integration .. image:: https://readthedocs.org/projects/seqtools-doc/badge :target: http://seqtools-doc.readthedocs.io :alt: Documentation .. image:: https://api.codacy.com/project/badge/Grade/f5324dc1e36d46f7ae1cabaaf6bce263 :target: https://www.codacy.com/app/nlgranger/SeqTools?utm_source=github.com&utm_medium=referral&utm_content=nlgranger/SeqTools&utm_campaign=Badge_Grade :alt: Code quality analysis .. image:: https://codecov.io/gh/nlgranger/SeqTools/branch/master/graph/badge.svg :target: https://codecov.io/gh/nlgranger/SeqTools :alt: Tests coverage .. image:: http://joss.theoj.org/papers/527a3c6e78ef0b31f93bbd29235d5a0b/status.svg :target: http://joss.theoj.org/papers/527a3c6e78ef0b31f93bbd29235d5a0b :alt: Citable paper SeqTools ======== SeqTools extends the functionalities of itertools to indexable (list-like) objects. Some of the provided functionalities include: element-wise function mapping, reordering, reindexing, concatenation, joining, slicing, minibatching, `etc <https://seqtools-doc.readthedocs.io/en/stable/reference.html>`_. SeqTools functions implement **on-demand evaluation** under the hood: operations and transformations are only applied to individual items when they are actually accessed. A simple but powerful prefetch function is also provided to quickly evaluate elements. SeqTools originally targets data science, more precisely the data preprocessing stages. Being aware of the experimental nature of this usage, on-demand execution is made as transparent as possible by providing **fault-tolerant functions and insightful error message**. Example ------- Example ------- >>> def f1(x): ... return x + 1 ... >>> def f2(x): # slow and memory heavy transformation ... time.sleep(.01) ... return [x for _ in range(500)] ... >>> def f3(x): ... return sum(x) / len(x) ... >>> data = list(range(1000)) Without seqtools, defining the pipeline and reading values looks like so: >>> tmp1 = [f1(x) for x in data] >>> tmp2 = [f2(x) for x in tmp1] # takes 10 seconds and a lot of memory >>> res = [f3(x) for x in tmp2] >>> print(res[2]) 3.0 >>> print(max(tmp2[2])) # requires to store 499 500 useless values along 3 With seqtools: >>> tmp1 = seqtools.smap(f1, data) >>> tmp2 = seqtools.smap(f2, tmp1) >>> res = seqtools.smap(f3, tmp2) # no computations so far >>> print(res[2]) # takes 0.01 seconds 3.0 >>> print(max(tmp2[2])) # easy access to intermediate results 3 Batteries included! ------------------- The library comes with a set of functions to manipulate sequences: .. |concatenate| image:: docs/_static/concatenate.png .. _concatenation: https://seqtools-doc.readthedocs.io/en/latest/reference.html#seqtools.concatenate .. |batch| image:: docs/_static/batch.png .. _batching: https://seqtools-doc.readthedocs.io/en/latest/reference.html#seqtools.batch .. |gather| image:: docs/_static/gather.png .. _reindexing: https://seqtools-doc.readthedocs.io/en/latest/reference.html#seqtools.gather .. |prefetch| image:: docs/_static/prefetch.png .. _prefetching: https://seqtools-doc.readthedocs.io/en/latest/reference.html#seqtools.prefetch .. |interleaving| image:: docs/_static/interleaving.png .. _interleaving: https://seqtools-doc.readthedocs.io/en/latest/reference.html#seqtools.interleave .. |uniter| image:: docs/_static/uniter.png .. _uniter: https://seqtools-doc.readthedocs.io/en/latest/reference.html#seqtools.uniter ==================== ================= =============== | `concatenation`_ | `batching`_ | `reindexing`_ | |concatenate| | |batch| | |gather| | `prefetching`_ | `interleaving`_ | `uniter`_ | |prefetch| | |interleaving| | |uniter| ==================== ================= =============== and others (suggestions are also welcome). Installation ------------ .. code-block:: bash pip install seqtools Documentation ------------- The documentation is hosted at `https://seqtools-doc.readthedocs.io <https://seqtools-doc.readthedocs.io>`_. Contributing and Support ------------------------ Use the `issue tracker <https://github.com/nlgranger/SeqTools/issues>`_ to request features, propose improvements or report issues. For questions regarding usage, please send an `email <mailto:3764009+nlgranger@users.noreply.github.com>`_. Related libraries ----------------- `Joblib <https://joblib.readthedocs.io>`_, proposes low-level functions with many optimization settings to optimize pipelined transformations. This library notably provides advanced caching mechanisms which are not the primary concern of SeqTool. SeqTool uses a simpler container-oriented interface with multiple utility functions in order to assist fast prototyping. On-demand evaluation is its default behaviour and applies at all layers of a transformation pipeline. In particular, parallel evaluation can be inserted in the middle of the transformation pipeline and won't block the execution to wait for the computation of all elements from the dataset. SeqTools is conceived to connect nicely to the data loading pipeline of Machine Learning libraries such as PyTorch's `torch.utils.data <http://pytorch.org/docs/master/data.html>`_ and `torchvision.transforms <http://pytorch.org/docs/master/torchvision/transforms.html>`_ or Tensorflow's `tf.data <https://www.tensorflow.org/guide/datasets>`_. The interface of these libraries focuses on `iterators <https://docs.python.org/3/library/stdtypes.html#iterator-types>`_ to access transformed elements, contrary to SeqTools which also provides arbitrary reads via indexing.


نیازمندی

مقدار نام
- tblib
- sphinx
- ipython
- ipykernel
- nbconvert
- nbsphinx
- Pillow
- numpy
- scikit-learn
- numpy
- pytorch
- pytest
- pytest-timeout
- numpy
- coverage
- nose


نحوه نصب


نصب پکیج whl SeqTools-1.2.0:

    pip install SeqTools-1.2.0.whl


نصب پکیج tar.gz SeqTools-1.2.0:

    pip install SeqTools-1.2.0.tar.gz