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Merged
merged 12 commits into from
Dec 4, 2018
Merged

Moved the imports and region tags inside the functions #1891

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b0285c8
Moved the imports and region tags inside the functions
happyhuman Dec 3, 2018
1008e05
Removed the unnecessary imports
happyhuman Dec 3, 2018
677c3d4
Added the missing import (six) to the functions
happyhuman Dec 3, 2018
d818474
Removed the extra whitespaces
happyhuman Dec 3, 2018
bc600a5
Merge branch 'master' into master
happyhuman Dec 4, 2018
3c8e76b
Changes based on Alix's comments.
happyhuman Dec 4, 2018
9539226
Remove extra whitespace
happyhuman Dec 4, 2018
3ec1471
Merge branch 'master' into master
happyhuman Dec 4, 2018
ed84c48
Removed extra whitespaces
happyhuman Dec 4, 2018
a13340d
Merge branch 'master' of github.com:happyhuman/python-docs-samples
happyhuman Dec 4, 2018
1224bad
Removed unused import
happyhuman Dec 4, 2018
7e76df7
Removed the extra + signs
happyhuman Dec 4, 2018
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113 changes: 87 additions & 26 deletions language/cloud-client/v1/snippets.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
#!/usr/bin/env python

# Copyright 2016 Google, Inc.
# Copyright 2018 Google, LLC.
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For the future, I've been told we only need to update this for new files.
It's just LLC no .

#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
Expand All @@ -24,17 +24,20 @@
import argparse
import sys

from google.cloud import language
from google.cloud.language import enums
from google.cloud.language import types
import six


# [START language_sentiment_text]
def sentiment_text(text):
# [START language_sentiment_text]
import six
from google.cloud import language
from google.cloud.language import enums
from google.cloud.language import types

"""Detects sentiment in the text."""
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Please remove. It doesn't make sense to have a docstring if the user doesn't know it's a function.

client = language.LanguageServiceClient()

# TODO(developer): Uncomment the following line to run this code.
# text = 'Your text to analyze, e.g. Hello, world!'
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It would be better to remove the parameter and have the actual text defined here. This will reduce confusion for the user. Only have commented out variables when absolutely necessary (ex. a project ID).

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So, the function takes no input parameters as text, and we uncomment text to something like this:
text = 'Hello World'

Yeah?

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Yes, you are correct on the 'Hello World' example. For the gcs_uri parameter, upload the sample file to the cloud-samples-data storage bucket, and then update to where you uploaded it. For example: gcs_uri = 'gs://cloud-samples-data/language/your-sample-file.txt'

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Did we finalize that new sample rubric yet?

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This page the example page alix? https://cloud.google.com/natural-language/docs/quickstart-client-libraries

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It's not officially finalized because we're still waiting on UX testing for the script vs. function formatting. I believe eliminating the use of commented out variables when possible was non-controversial, though.

I don't think that link is the "official" example page, though those look like good samples to me.


if isinstance(text, six.binary_type):
text = text.decode('utf-8')

Expand All @@ -51,14 +54,20 @@ def sentiment_text(text):
print('Score: {}'.format(sentiment.score))
print('Magnitude: {}'.format(sentiment.magnitude))
# [END language_python_migration_sentiment_text]
# [END language_sentiment_text]
# [END language_sentiment_text]


# [START language_sentiment_gcs]
def sentiment_file(gcs_uri):
# [START language_sentiment_gcs]
from google.cloud import language
from google.cloud.language import enums
from google.cloud.language import types
"""Detects sentiment in the file located in Google Cloud Storage."""
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Please remove.

client = language.LanguageServiceClient()

# TODO(developer): Uncomment the following line to run this code.
# gcs_uri = 'The gcs uri to your file, e.g. gs://my_bucket/my_file'
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This URI could be defined here if you put the file in our sample data GCS bucket - gs://cloud-samples-data. This way the user has an easily accessible test file and the snippet tests don't have to upload a file every time. Let me know if you don't have permissions to that project and I'll add you.


# Instantiates a plain text document.
# [START language_python_migration_document_gcs]
document = types.Document(
Expand All @@ -72,14 +81,21 @@ def sentiment_file(gcs_uri):

print('Score: {}'.format(sentiment.score))
print('Magnitude: {}'.format(sentiment.magnitude))
# [END language_sentiment_gcs]
# [END language_sentiment_gcs]


# [START language_entities_text]
def entities_text(text):
# [START language_entities_text]
import six
from google.cloud import language
from google.cloud.language import enums
from google.cloud.language import types
"""Detects entities in the text."""
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Please remove.

client = language.LanguageServiceClient()

# TODO(developer): Uncomment the following line to run this code.
# text = 'Your text to analyze, e.g. Hello, world!'
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Same as above. Please replace with the actual text.


if isinstance(text, six.binary_type):
text = text.decode('utf-8')

Expand All @@ -105,14 +121,20 @@ def entities_text(text):
print(u'{:<16}: {}'.format('wikipedia_url',
entity.metadata.get('wikipedia_url', '-')))
# [END language_python_migration_entities_text]
# [END language_entities_text]
# [END language_entities_text]


# [START language_entities_gcs]
def entities_file(gcs_uri):
# [START language_entities_gcs]
from google.cloud import language
from google.cloud.language import enums
from google.cloud.language import types
"""Detects entities in the file located in Google Cloud Storage."""
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Please remove.

client = language.LanguageServiceClient()

# TODO(developer): Uncomment the following line to run this code.
# gcs_uri = 'The gcs uri to your file, e.g. gs://my_bucket/my_file'
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Same as above. Please load the file to the sample storage bucket.


# Instantiates a plain text document.
document = types.Document(
gcs_content_uri=gcs_uri,
Expand All @@ -131,14 +153,21 @@ def entities_file(gcs_uri):
print(u'{:<16}: {}'.format('salience', entity.salience))
print(u'{:<16}: {}'.format('wikipedia_url',
entity.metadata.get('wikipedia_url', '-')))
# [END language_entities_gcs]
# [END language_entities_gcs]


# [START language_syntax_text]
def syntax_text(text):
# [START language_syntax_text]
import six
from google.cloud import language
from google.cloud.language import enums
from google.cloud.language import types
"""Detects syntax in the text."""
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Please remove.

client = language.LanguageServiceClient()

# TODO(developer): Uncomment the following line to run this code.
# text = 'Your text to analyze, e.g. Hello, world!'
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Same as above. Please hardcode the text.


if isinstance(text, six.binary_type):
text = text.decode('utf-8')

Expand All @@ -157,14 +186,20 @@ def syntax_text(text):
print(u'{}: {}'.format(part_of_speech_tag.name,
token.text.content))
# [END language_python_migration_syntax_text]
# [END language_syntax_text]
# [END language_syntax_text]


# [START language_syntax_gcs]
def syntax_file(gcs_uri):
# [START language_syntax_gcs]
from google.cloud import language
from google.cloud.language import enums
from google.cloud.language import types
"""Detects syntax in the file located in Google Cloud Storage."""
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Please remove.

client = language.LanguageServiceClient()

# TODO(developer): Uncomment the following line to run this code.
# gcs_uri = 'The gcs uri to your file, e.g. gs://my_bucket/my_file'
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Same as above. Please upload the file to the sample file bucket.


# Instantiates a plain text document.
document = types.Document(
gcs_content_uri=gcs_uri,
Expand All @@ -178,14 +213,21 @@ def syntax_file(gcs_uri):
part_of_speech_tag = enums.PartOfSpeech.Tag(token.part_of_speech.tag)
print(u'{}: {}'.format(part_of_speech_tag.name,
token.text.content))
# [END language_syntax_gcs]
# [END language_syntax_gcs]


# [START language_entity_sentiment_text]
def entity_sentiment_text(text):
# [START language_entity_sentiment_text]
import six
from google.cloud import language
from google.cloud.language import enums
from google.cloud.language import types
"""Detects entity sentiment in the provided text."""
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Please remove.

client = language.LanguageServiceClient()

# TODO(developer): Uncomment the following line to run this code.
# text = 'Your text to analyze, e.g. Hello, world!'
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Same as above. Please hardcode the text.


if isinstance(text, six.binary_type):
text = text.decode('utf-8')

Expand All @@ -211,14 +253,20 @@ def entity_sentiment_text(text):
print(u' Type : {}'.format(mention.type))
print(u'Salience: {}'.format(entity.salience))
print(u'Sentiment: {}\n'.format(entity.sentiment))
# [END language_entity_sentiment_text]
# [END language_entity_sentiment_text]


# [START language_entity_sentiment_gcs]
def entity_sentiment_file(gcs_uri):
# [START language_entity_sentiment_gcs]
from google.cloud import language
from google.cloud.language import enums
from google.cloud.language import types
"""Detects entity sentiment in a Google Cloud Storage file."""
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Please remove.

client = language.LanguageServiceClient()

# TODO(developer): Uncomment the following line to run this code.
# gcs_uri = 'The gcs uri to your file, e.g. gs://my_bucket/my_file'
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Same as above. Please upload the file to the sample bucket.


document = types.Document(
gcs_content_uri=gcs_uri,
type=enums.Document.Type.PLAIN_TEXT)
Expand All @@ -240,14 +288,21 @@ def entity_sentiment_file(gcs_uri):
print(u' Type : {}'.format(mention.type))
print(u'Salience: {}'.format(entity.salience))
print(u'Sentiment: {}\n'.format(entity.sentiment))
# [END language_entity_sentiment_gcs]
# [END language_entity_sentiment_gcs]


# [START language_classify_text]
def classify_text(text):
# [START language_classify_text]
import six
from google.cloud import language
from google.cloud.language import enums
from google.cloud.language import types
"""Classifies content categories of the provided text."""
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Please remove.

client = language.LanguageServiceClient()

# TODO(developer): Uncomment the following line to run this code.
# text = 'Your text to analyze, e.g. Hello, world!'
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Same as above. Please hardcode the text.

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This will need to be longer than 20 tokens or the api call will fail.


if isinstance(text, six.binary_type):
text = text.decode('utf-8')

Expand All @@ -261,16 +316,22 @@ def classify_text(text):
print(u'=' * 20)
print(u'{:<16}: {}'.format('name', category.name))
print(u'{:<16}: {}'.format('confidence', category.confidence))
# [END language_classify_text]
# [END language_classify_text]


# [START language_classify_gcs]
def classify_file(gcs_uri):
# [START language_classify_gcs]
from google.cloud import language
from google.cloud.language import enums
from google.cloud.language import types
"""Classifies content categories of the text in a Google Cloud Storage
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Please remove.

file.
"""
client = language.LanguageServiceClient()

# TODO(developer): Uncomment the following line to run this code.
# gcs_uri = 'The gcs uri to your file, e.g. gs://my_bucket/my_file'
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Same as above. Please upload the file to the sample bucket.


document = types.Document(
gcs_content_uri=gcs_uri,
type=enums.Document.Type.PLAIN_TEXT)
Expand All @@ -281,7 +342,7 @@ def classify_file(gcs_uri):
print(u'=' * 20)
print(u'{:<16}: {}'.format('name', category.name))
print(u'{:<16}: {}'.format('confidence', category.confidence))
# [END language_classify_gcs]
# [END language_classify_gcs]


if __name__ == '__main__':
Expand Down