dealstat 0.1.5

=================
DealStat Utilities
=================


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DealStat Utilities


* Free software: MIT license

Dealstat
--------
Generic functions that may be moved to specific modules at some point:::

from dealstat.dealstat import *

# generate random letter based ID of given length
my_id = unique_id(30)


Boto
--------
Simplifies some of AWS' Boto3 functionality (at the moment, just S3)

* First save `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY` as environment variables::

from dealstat.boto import Boto
s3 = Boto('s3')

location1 = {'bucket':'<some-bucket>', 'key': '<some-key'>}
location2 = {'bucket':'<some-other-bucket>', 'key': '<some-other-key'>}

# Get temporary pre-signed url
url = s3.get_temp_url(location1)

# Move object from one bucket/key to another
s3.move_object(location1, location2)

# Upload file
file_path = '/some/file/path.txt'
s3.upload_file(file_path, location1)

# Download file
destination_file_path = 'local/file/path2.txt'
s3.download_file(destination_file_path, location2)

# List contents of bucket
# Use prefix='some-prefix' to search for specific key prefixes
# Use exclude_dirs=True to not return directories in result
s3.list_bucket('<some-bucket'>, prefix=None, exclude_dirs=True)

Machine Learning
--------
Random utilities useful in ML prototyping

* Download and use Standform NLP Glove Embedings ::

from dealstat.ml import Embeddings

Embed = Embeddings()

# Download embeddings
Embed.download_embeddings()

# Unzip embeddings
Embed.extract_embeddings()

# Generate embeddings look up dict for given dimension
dim = 200
embedding_dict = Embed.generate(loc='.', dim=dim)





Credits
-------

This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage


=======
History
=======

0.1.0 (2018-08-23)
------------------

* First release on PyPI.