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fix(docs): corrects typos in project documentation (#5741) · smooth80/python-docs-samples@ea1a3a7 · GitHub

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fix(docs): corrects typos in project documentation (GoogleCloudPlatform#5741)
* fix(docs): corrects typos in project documentation * Update notebooks/rendered/bigquery-basics.md Co-authored-by: Leah E. Cole <6719667+leahecole@users.noreply.github.com>
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‎appengine/standard/i18n/README.md‎

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$ pybabel update -l ja -d locales -i locales/messages.pot
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Note: If you run `pybabel init` against an existant translations file,
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Note: If you run `pybabel init` against an existent translations file,
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you will lose your translations.
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For strings in Jinja2 templates, there is the `i18n_utils.BaseHandler`
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class from which you can extend in order to have a handy property
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named `jinja2_env` that lazily initializes Jinja2 environment for you
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with the `jinja2.ext.i18n` extention, and similar to the
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with the `jinja2.ext.i18n` extension, and similar to the
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`I18nMiddleware`, installs `gettext` and `ngettext` functions to the
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global namespace of the Jinja2 environment.
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‎cloud-sql/mysql/client-side-encryption/README.md‎

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### Install requirements
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Next, setup install the requirements into a virtual enviroment:
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Next, setup install the requirements into a virtual environment:
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```bash
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virtualenv --python python3 env
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source env/bin/activate

‎cloud-sql/mysql/sqlalchemy/README.md‎

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### Testing the application
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Next, setup install the requirements into a virtual enviroment:
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Next, setup install the requirements into a virtual environment:
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```bash
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virtualenv --python python3 env
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source env/bin/activate

‎cloud-sql/postgres/client-side-encryption/README.md‎

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### Install requirements
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Next, setup install the requirements into a virtual enviroment:
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Next, setup install the requirements into a virtual environment:
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```bash
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virtualenv --python python3 env
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source env/bin/activate

‎cloud-sql/postgres/sqlalchemy/README.md‎

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```
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### Testing the application
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Next, setup install the requirements into a virtual enviroment:
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Next, setup install the requirements into a virtual environment:
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```bash
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virtualenv --python python3 env
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source env/bin/activate

‎notebooks/rendered/bigquery-basics.md‎

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load_job.result() # Waits for table load to complete.
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print('Job finished.')
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# Retreive the destination table
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# Retrieve the destination table
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destination_table = client.get_table(table_ref)
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print('Loaded {} rows.'.format(destination_table.num_rows))
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```

‎run/image-processing/README.md‎

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Cloud Run services can be [configured with Environment Variables](https://cloud.google.com/run/docs/configuring/environment-variables).
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Required variables for this sample include:
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* `INPUT_BUCKET_NAME`: The Cloud Run service will be notified of images uploaded to this Cloud Storage bucket. The service will then retreive and process the image.
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* `INPUT_BUCKET_NAME`: The Cloud Run service will be notified of images uploaded to this Cloud Storage bucket. The service will then retrieve and process the image.
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* `BLURRED_BUCKET_NAME`: The Cloud Run service will write blurred images to this Cloud Storage bucket.
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## Maintenance Note

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