Type "help", "copyright", "credits" or "license" for more information. If IPython isn't your preference, use of a standard Python interactive interpreter (either the Cloud Shell or your local development environment) is perfectly acceptable (also exit with ^D): $ python IPython 7.13.0 - An enhanced Interactive Python. Type 'copyright', 'credits' or 'license' for more information Example output of starting ipython will look like this: $ ipython Exit with ^D (Ctrl-d) and accept the offer to exit. IPython can be accessed from the Cloud Shell but can also be installed in a local development environment. IPython favors a Python 3 interpreter first but falls back to Python 2 if 3.x isn't available. If you are, IPython is the default interpreter for Jupyter Notebooks as well as Colab, Jupyter Notebooks hosted by Google Research. it is a higher-level interactive Python interpreter which we recommend, especially if you are part of the data science or machine learning community. The Cloud Shell also has IPython installed. More specifically for this codelab, the Cloud Shell has already pre-installed both versions of Python. The Cloud Shell is especially useful if you're developing or plan to continue developing with GCP products & APIs. The Cloud Shell is a convenience available for users directly from the Cloud Console and doesn't require a local development environment, so this tutorial can be done completely in the cloud with a web browser. You can find out more about support for Python here. If setting up your own, follow these guidelines to bring it in line with what's available from the Cloud Shell (more below). Google provides a cloud-based development environment for user convenience, but developers are welcome to using their own local dev environment as well. In particular, this codelab supports Python 2 and 3, but we recommend moving to 3.x as soon as possible. This codelab requires you to use the Python language (although many languages are supported by the Google APIs client libraries, so feel free to build something equivalent in your favorite development tool and simply use the Python as pseudocode). If you prefer not to use Python, you're welcome to implement the codelab in your favorite development tool (supported languages' client libraries are available here) and simply refer to the Python examples as (executable) pseudocode.
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