Project Setup Instructions

Project%20Setup%20Instructions

User Manual:

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Page Count: 5

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Follow the instructions below to set up ​your local development environment. ​You can
also use your Google Cloud Instance for running this project. In both the cases, you will
need to obtain the credentials file and create a dataset on BigQuery where you will save
your tables.

1) Install the google cloud SDK library :
Run the following command in your terminal to install the required library:
pip install --upgrade google-cloud-storage click
pip install google-cloud-bigquery

2) Open the URL below:
https://cloud.google.com/bigquery/docs/quickstarts/quickstart-client-libraries#bigquery-si
mple-app-local-dev-python
(Make sure you are signed in using your cloud.cs account)

3) Create a Project by clicking on the button:
If you already created a project before, you can use the same project and skip to
step 5. Otherwise, you can follow step 3 and 4 to create a new project.
Click on the “GO TO THE MANAGE RESOURCES PAGE” button.

4) Create a new project
Click on create a project button on the top and fill in details about your project as shown
below. Click on the create button to finish creating your project. Make sure you select
the Billing Account as ​COMS 4111 Introduction to Databases​.

5) Click on the “Enable API” button
Once the project has been created, click on the “ENABLE API” button in the URL which
has been mentioned above.

6) Select the project which you created in step 5.

Once, you have selected the project, the BigQuery API will get enabled.

7) Select “Go to the Create Service Account Key Page” button.
Follow the instructions, as provided in the image below.

Click on the “Create” button.
A .json file containing the required credentials will be downloaded automatically.

8)​​ ​Open BigQuery console:

Click on the URL ​https://cloud.google.com/bigquery/​ and choose the “Go To Console”
button.
You can also follow the instructions at ​https://cloud.google.com/bigquery/docs/datasets
to create your own dataset using the Python API.

9) Create a new dataset:
To create a new dataset click on the button below. Fill in the details and click on the
create button.

10) Run graph.py
Now you can run the graph.py script by providing the path to the downloaded
credentials file as a system argument.
If you’re using the GCP instance to run your project, make sure you upload the
credentials file on the instance, install the required libraries and use the graph.py as the
starter code for your submission.
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