From a952f235551148946ad5b3698cb307ba29801c4e Mon Sep 17 00:00:00 2001 From: "gcf-owl-bot[bot]" <78513119+gcf-owl-bot[bot]@users.noreply.github.com> Date: Wed, 10 Nov 2021 20:37:03 -0500 Subject: [PATCH] chore(python): run blacken session for all directories with a noxfile (#220) Source-Link: https://github.com/googleapis/synthtool/commit/bc0de6ee2489da6fb8eafd021a8c58b5cc30c947 Post-Processor: gcr.io/cloud-devrel-public-resources/owlbot-python:latest@sha256:39ad8c0570e4f5d2d3124a509de4fe975e799e2b97e0f58aed88f8880d5a8b60 Co-authored-by: Owl Bot --- language/snippets/classify_text/classify_text_tutorial.py | 2 +- language/snippets/cloud-client/v1/quickstart.py | 8 ++++++-- language/snippets/cloud-client/v1/set_endpoint.py | 4 +++- .../generated-samples/v1/language_sentiment_text.py | 2 +- language/snippets/sentiment/sentiment_analysis.py | 6 ++++-- 5 files changed, 15 insertions(+), 7 deletions(-) diff --git a/language/snippets/classify_text/classify_text_tutorial.py b/language/snippets/classify_text/classify_text_tutorial.py index 9c05b83f589c..675f8499efc0 100644 --- a/language/snippets/classify_text/classify_text_tutorial.py +++ b/language/snippets/classify_text/classify_text_tutorial.py @@ -42,7 +42,7 @@ def classify(text, verbose=True): document = language_v1.Document( content=text, type_=language_v1.Document.Type.PLAIN_TEXT ) - response = language_client.classify_text(request={'document': document}) + response = language_client.classify_text(request={"document": document}) categories = response.categories result = {} diff --git a/language/snippets/cloud-client/v1/quickstart.py b/language/snippets/cloud-client/v1/quickstart.py index 4c4b06b52a14..b9b0e96c1781 100644 --- a/language/snippets/cloud-client/v1/quickstart.py +++ b/language/snippets/cloud-client/v1/quickstart.py @@ -30,10 +30,14 @@ def run_quickstart(): # The text to analyze text = u"Hello, world!" - document = language_v1.Document(content=text, type_=language_v1.Document.Type.PLAIN_TEXT) + document = language_v1.Document( + content=text, type_=language_v1.Document.Type.PLAIN_TEXT + ) # Detects the sentiment of the text - sentiment = client.analyze_sentiment(request={'document': document}).document_sentiment + sentiment = client.analyze_sentiment( + request={"document": document} + ).document_sentiment print("Text: {}".format(text)) print("Sentiment: {}, {}".format(sentiment.score, sentiment.magnitude)) diff --git a/language/snippets/cloud-client/v1/set_endpoint.py b/language/snippets/cloud-client/v1/set_endpoint.py index e9ad97d3e4b1..c49537a58b81 100644 --- a/language/snippets/cloud-client/v1/set_endpoint.py +++ b/language/snippets/cloud-client/v1/set_endpoint.py @@ -31,7 +31,9 @@ def set_endpoint(): ) # Detects the sentiment of the text - sentiment = client.analyze_sentiment(request={'document': document}).document_sentiment + sentiment = client.analyze_sentiment( + request={"document": document} + ).document_sentiment print("Sentiment: {}, {}".format(sentiment.score, sentiment.magnitude)) diff --git a/language/snippets/generated-samples/v1/language_sentiment_text.py b/language/snippets/generated-samples/v1/language_sentiment_text.py index 9f975023114f..4170ddbc4cd0 100644 --- a/language/snippets/generated-samples/v1/language_sentiment_text.py +++ b/language/snippets/generated-samples/v1/language_sentiment_text.py @@ -39,7 +39,7 @@ def sample_analyze_sentiment(content): type_ = language_v1.Document.Type.PLAIN_TEXT document = {"type_": type_, "content": content} - response = client.analyze_sentiment(request={'document': document}) + response = client.analyze_sentiment(request={"document": document}) sentiment = response.document_sentiment print("Score: {}".format(sentiment.score)) print("Magnitude: {}".format(sentiment.magnitude)) diff --git a/language/snippets/sentiment/sentiment_analysis.py b/language/snippets/sentiment/sentiment_analysis.py index 2333bf8238ab..e82c3a68ae86 100644 --- a/language/snippets/sentiment/sentiment_analysis.py +++ b/language/snippets/sentiment/sentiment_analysis.py @@ -51,8 +51,10 @@ def analyze(movie_review_filename): # Instantiates a plain text document. content = review_file.read() - document = language_v1.Document(content=content, type_=language_v1.Document.Type.PLAIN_TEXT) - annotations = client.analyze_sentiment(request={'document': document}) + document = language_v1.Document( + content=content, type_=language_v1.Document.Type.PLAIN_TEXT + ) + annotations = client.analyze_sentiment(request={"document": document}) # Print the results print_result(annotations)