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‎.gitattributes

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# Auto detect text files and perform LF normalization
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* text=auto

‎README.md

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# AWS-Rekognition
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AWS Rekognition Chalice
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## Supported File Extensions
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* Image: JPEG, JPG, PNG
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* Video: MOV, MPEG-4, FLV (Based on H264)
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## Supported Function
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* Labels(identify thousands of objects)
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* Face detection and analysis(emotion, gender, smiling etc)

‎app.py

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import json
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import os
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import boto3
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from chalice import Chalice
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from chalice import NotFoundError
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from chalicelib import db
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from chalicelib import rekognition
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app = Chalice(app_name='media-query')
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_MEDIA_DB = None
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_REKOGNITION_CLIENT = None
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_SUPPORTED_IMAGE_EXTENSIONS = (
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'.jpg',
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'.jpeg',
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'.png',
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)
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_SUPPORTED_VIDEO_EXTENSIONS = (
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'.mp4',
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'.flv',
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'.mov',
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)
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def get_media_db():
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global _MEDIA_DB
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if _MEDIA_DB is None:
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_MEDIA_DB = db.DynamoMediaDB(
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boto3.resource('dynamodb').Table(
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os.environ['MEDIA_TABLE_NAME']))
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return _MEDIA_DB
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def get_rekognition_client():
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global _REKOGNITION_CLIENT
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if _REKOGNITION_CLIENT is None:
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_REKOGNITION_CLIENT = rekognition.RekognitonClient(
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boto3.client('rekognition'))
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return _REKOGNITION_CLIENT
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# Start of Event Handlers.
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@app.on_s3_event(bucket=os.environ['MEDIA_BUCKET_NAME'],
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events=['s3:ObjectCreated:*'])
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def handle_object_created(event):
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if _is_image(event.key):
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_handle_created_image(bucket=event.bucket, key=event.key)
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elif _is_video(event.key):
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_handle_created_video(bucket=event.bucket, key=event.key)
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@app.on_s3_event(bucket=os.environ['MEDIA_BUCKET_NAME'],
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events=['s3:ObjectRemoved:*'])
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def handle_object_removed(event):
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if _is_image(event.key) or _is_video(event.key):
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get_media_db().delete_media_file(event.key)
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@app.on_sns_message(topic=os.environ['VIDEO_TOPIC_NAME'])
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def add_video_file(event):
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message = json.loads(event.message)
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labels = get_rekognition_client().get_video_job_labels(message['JobId'])
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get_media_db().add_media_file(
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name=message['Video']['S3ObjectName'],
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media_type=db.VIDEO_TYPE,
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labels=labels)
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@app.on_sns_message(topic=os.environ['VIDEO_TOPIC_FACE_NAME'])
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def add_video_file_face(event):
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message = json.loads(event.message)
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emotions = get_rekognition_client().get_video_job_faces(message['JobId'])
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get_media_db().add_media_file_face(
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name=message['Video']['S3ObjectName'],
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media_type=db.VIDEO_TYPE,
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emotions=emotions)
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@app.route('/',cors=True)
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def list_media_files():
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params = {}
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if app.current_request.query_params:
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params = _extract_db_list_params(app.current_request.query_params)
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return get_media_db().list_media_files(**params)
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@app.route('/{name}',cors=True)
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def get_media_file(name):
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item = get_media_db().get_media_file(name)
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if item is None:
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raise NotFoundError('Media file (%s) not found' % name)
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return item
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# End of Event Handlers.
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def _extract_db_list_params(query_params):
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valid_query_params = [
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'startswith',
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'media-type',
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'label'
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]
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return {
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k.replace('-', '_'): v
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for k, v in query_params.items() if k in valid_query_params
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}
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def _is_image(key):
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return key.endswith(_SUPPORTED_IMAGE_EXTENSIONS)
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def _handle_created_image(bucket, key):
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labels = get_rekognition_client().get_image_labels(bucket=bucket, key=key)
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emotions = get_rekognition_client().get_image_emotions(bucket=bucket, key=key)
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if 'public/' in key:
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index = key.find('public/')
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key = key[index+len('public/'):]
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get_media_db().add_media_file(key, media_type=db.IMAGE_TYPE, labels=labels)
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get_media_db().add_media_file_face(key, media_type=db.IMAGE_TYPE, emotions=emotions)
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def _is_video(key):
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return key.endswith(_SUPPORTED_VIDEO_EXTENSIONS)
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def _handle_created_video(bucket, key):
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get_rekognition_client().start_video_label_job(
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bucket=bucket, key=key, topic_arn=os.environ['VIDEO_TOPIC_ARN'],
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role_arn=os.environ['VIDEO_ROLE_ARN']
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)
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get_rekognition_client().start_video_face_job(
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bucket=bucket, key=key,
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topic_arn=os.environ['VIDEO_TOPIC_FACE_ARN'],
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role_arn=os.environ['VIDEO_ROLE_ARN']
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)

‎boto3-1.14.63.dist-info/DESCRIPTION.rst

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===============================
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Boto3 - The AWS SDK for Python
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===============================
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|Build Status| |Version| |Gitter|
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Boto3 is the Amazon Web Services (AWS) Software Development Kit (SDK) for
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Python, which allows Python developers to write software that makes use
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of services like Amazon S3 and Amazon EC2. You can find the latest, most
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up to date, documentation at our `doc site`_, including a list of
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services that are supported.
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.. _boto: https://docs.pythonboto.org/
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.. _`doc site`: https://boto3.amazonaws.com/v1/documentation/api/latest/index.html
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.. |Build Status| image:: http://img.shields.io/travis/boto/boto3/develop.svg?style=flat
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:target: https://travis-ci.org/boto/boto3
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:alt: Build Status
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.. |Gitter| image:: https://badges.gitter.im/boto/boto3.svg
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:target: https://gitter.im/boto/boto3
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:alt: Gitter
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.. |Downloads| image:: http://img.shields.io/pypi/dm/boto3.svg?style=flat
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:target: https://pypi.python.org/pypi/boto3/
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:alt: Downloads
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.. |Version| image:: http://img.shields.io/pypi/v/boto3.svg?style=flat
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:target: https://pypi.python.org/pypi/boto3/
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:alt: Version
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.. |License| image:: http://img.shields.io/pypi/l/boto3.svg?style=flat
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:target: https://github.com/boto/boto3/blob/develop/LICENSE
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:alt: License
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Getting Started
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---------------
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Assuming that you have Python and ``virtualenv`` installed, set up your environment and install the required dependencies like this or you can install the library using ``pip``:
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.. code-block:: sh
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$ git clone https://github.com/boto/boto3.git
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$ cd boto3
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$ virtualenv venv
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...
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$ . venv/bin/activate
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$ python -m pip install -r requirements.txt
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$ python -m pip install -e .
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.. code-block:: sh
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$ python -m pip install boto3
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Using Boto3
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~~~~~~~~~~~~~~
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After installing boto3
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Next, set up credentials (in e.g. ``~/.aws/credentials``):
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.. code-block:: ini
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[default]
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aws_access_key_id = YOUR_KEY
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aws_secret_access_key = YOUR_SECRET
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Then, set up a default region (in e.g. ``~/.aws/config``):
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.. code-block:: ini
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[default]
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region=us-east-1
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Other credentials configuration method can be found `here <https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html>`__
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Then, from a Python interpreter:
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.. code-block:: python
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>>> import boto3
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>>> s3 = boto3.resource('s3')
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>>> for bucket in s3.buckets.all():
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print(bucket.name)
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Running Tests
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~~~~~~~~~~~~~
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You can run tests in all supported Python versions using ``tox``. By default,
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it will run all of the unit and functional tests, but you can also specify your own
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``nosetests`` options. Note that this requires that you have all supported
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versions of Python installed, otherwise you must pass ``-e`` or run the
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``nosetests`` command directly:
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.. code-block:: sh
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$ tox
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$ tox -- unit/test_session.py
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$ tox -e py26,py33 -- integration/
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You can also run individual tests with your default Python version:
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.. code-block:: sh
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$ nosetests tests/unit
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Getting Help
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------------
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We use GitHub issues for tracking bugs and feature requests and have limited
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bandwidth to address them. Please use these community resources for getting
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help:
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* Ask a question on `Stack Overflow <https://stackoverflow.com/>`__ and tag it with `boto3 <https://stackoverflow.com/questions/tagged/boto3>`__
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* Come join the AWS Python community chat on `gitter <https://gitter.im/boto/boto3>`__
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* Open a support ticket with `AWS Support <https://console.aws.amazon.com/support/home#/>`__
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* If it turns out that you may have found a bug, please `open an issue <https://github.com/boto/boto3/issues/new>`__
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Contributing
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------------
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We value feedback and contributions from our community. Whether it's a bug report, new feature, correction, or additional documentation, we welcome your issues and pull requests. Please read through this `CONTRIBUTING <https://github.com/boto/boto3/blob/develop/CONTRIBUTING.rst>`__ document before submitting any issues or pull requests to ensure we have all the necessary information to effectively respond to your contribution.
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More Resources
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--------------
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* `NOTICE <https://github.com/boto/boto3/blob/develop/NOTICE>`__
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* `Changelog <https://github.com/boto/boto3/blob/develop/CHANGELOG.rst>`__
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* `License <https://github.com/boto/boto3/blob/develop/LICENSE.txt>`__
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