Google

Google Cloud services allow you to upload and manipulate Tables as spreadsheets (via GoogleSheets) or query them as SQL database tables (via GoogleBigQuery). You can also upload/store/download them as binary objects (via GoogleCloudStorage). Finally, Google offers an API for civic information using GoogleCivic.

For all of these services you will need to enable the APIs for your Google Cloud account and obtain authentication tokens to access them from your scripts. If you are the administrator of your Google Cloud account, you can do both of these at Google Cloud Console APIs and Services.

BigQuery

Overview

Google BigQuery is a cloud data warehouse solution. Data is stored in tables, and users can query using SQL. BigQuery uses datasets as top level containers for tables, and datasets are themselves contained within Google Cloud projects.

Quickstart

To instantiate the GoogleBigQuery class, you can pass the constructor a string containing either the name of the Google service account credentials file or a JSON string encoding those credentials. Alternatively, you can set the environment variable GOOGLE_APPLICATION_CREDENTIALS to be either of those strings and call the constructor without that argument.

from parsons import GoogleBigQuery

# Set as environment variable so we don't have to pass it in. May either
# be the file name or a JSON encoding of the credentials.
os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = 'google_credentials_file.json'

big_query = GoogleBigQuery()

Alternatively, you can pass the credentials in as an argument. In the example below, we also specify the project.

# Project in which we're working
project = 'parsons-test'
big_query = GoogleBigQuery(app_creds='google_credentials_file.json',
                           project=project)

We can now upload/query data.

dataset = 'parsons_dataset'
table = 'parsons_table'

# Table name should be project.dataset.table, or dataset.table, if
# working with the default project
table_name = project + '.' + dataset + '.' + table

# Must be pre-existing bucket. Create via GoogleCloudStorage() or
# at https://console.cloud.google.com/storage/create-bucket. May be
# omitted if the name of the bucket is specified in environment
# variable GCS_TEMP_BUCKET.
gcs_temp_bucket = 'parsons_bucket'

# Create dataset if it doesn't already exist
big_query.client.create_dataset(dataset=dataset, exists_ok=True)

parsons_table = Table([{'name':'Bob', 'party':'D'},
                       {'name':'Jane', 'party':'D'},
                       {'name':'Sue', 'party':'R'},
                       {'name':'Bill', 'party':'I'}])

# Copy table in to create new BigQuery table
big_query.copy(table_obj=parsons_table,
               table_name=table_name,
               tmp_gcs_bucket=gcs_temp_bucket)

# Select from project.dataset.table
big_query.query(f'select name from {table_name} where party = "D"')

# Delete the table when we're done
big_query.client.delete_table(table=table_name)

API

class parsons.google.google_bigquery.GoogleBigQuery(app_creds=None, project=None, location=None)

Class for querying BigQuery table and returning the data as Parsons tables.

This class requires application credentials in the form of a json. It can be passed in the following ways:

• Set an environmental variable named GOOGLE_APPLICATION_CREDENTIALS with the local path to the credentials json.

  Example: GOOGLE_APPLICATION_CREDENTALS='path/to/creds.json'

• Pass in the path to the credentials using the app_creds argument.

• Pass in a json string using the app_creds argument.

Args:

app_creds: str

A credentials json string or a path to a json file. Not required if GOOGLE_APPLICATION_CREDENTIALS env variable set.

project: str

The project which the client is acting on behalf of. If not passed then will use the default inferred environment.

location: str

Default geographic location for tables

copy(table_obj, table_name, if_exists='fail', tmp_gcs_bucket=None, gcs_client=None, job_config=None, **load_kwargs)

Copy a Parsons Table into Google BigQuery via Google Cloud Storage.

Args:

table_obj: obj

The Parsons Table to copy into BigQuery.

table_name: str

The table name to load the data into.

if_exists: str

If the table already exists, either fail, append, drop or truncate the table.

tmp_gcs_bucket: str

The name of the Google Cloud Storage bucket to use to stage the data to load into BigQuery. Required if GCS_TEMP_BUCKET is not specified.

gcs_client: object

The GoogleCloudStorage Connector to use for loading data into Google Cloud Storage.

job_config: object

A LoadJobConfig object to provide to the underlying call to load_table_from_uri on the BigQuery client. The function will create its own if not provided.

**load_kwargs: kwargs

Arguments to pass to the underlying load_table_from_uri call on the BigQuery client.

delete_table(table_name)

Delete a BigQuery table.

Args:

table_name: str

The name of the table to delete.

query(sql, parameters=None)

Run a BigQuery query and return the results as a Parsons table.

To include python variables in your query, it is recommended to pass them as parameters, following the BigQuery style where parameters are prefixed with @`s. Using the ``parameters` argument ensures that values are escaped properly, and avoids SQL injection attacks.

Parameter Examples

name = "Beatrice O'Brady"
sql = 'SELECT * FROM my_table WHERE name = %s'
rs.query(sql, parameters=[name])

name = "Beatrice O'Brady"
sql = "SELECT * FROM my_table WHERE name = %(name)s"
rs.query(sql, parameters={'name': name})

Args:

sql: str

A valid BigTable statement

parameters: dict

A dictionary of query parameters for BigQuery.

Returns:

Parsons Table

See Parsons Table for output options.

table_exists(table_name)

Check whether or not the Google BigQuery table exists in the specified dataset.

Args:

table_name: str

The name of the BigQuery table to check for

Returns:

bool

True if the table exists in the specified dataset, false otherwise

property client

Get the Google BigQuery client to use for making queries.

Returns:

google.cloud.bigquery.client.Client

Cloud Storage

Overview

Google Cloud Storage is a cloud file storage system. It uses buckets in which to store arbitrary files referred to as blobs. You may use this connector to upload Parsons tables as blobs, download them to files, and list available blobs.

To use the GoogleCloudStorage class, you will need Google service account credentials. If you are the administrator of your Google Cloud account, you can generate them in the Google Cloud Console APIs and Services.

Quickstart

To instantiate the GoogleBigQuery class, you can pass the constructor a string containing either the name of your Google service account credentials file or a JSON string encoding those credentials. Alternatively, you can set the environment variable GOOGLE_APPLICATION_CREDENTIALS to be either of those strings and call the constructor without that argument.

from parsons import GoogleCloudStorage

# Set as environment variable so we don't have to pass it in. May either
# be the file name or a JSON encoding of the credentials.
os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = 'google_credentials_file.json'

gcs = GoogleCloudStorage()

Alternatively, you can pass the credentials in as an argument. In the example below, we also specify the project.

credentials_filename = 'google_credentials_file.json'
project = 'parsons-test'    # Project in which we're working
gcs = GoogleCloudStorage(app_creds=credentials_filename, project=project)

Now we can create buckets, upload blobs to them and and list/retrieve the available blobs.

gcs.create_bucket('parsons_bucket')
gcs.list_buckets()

gcs.upload_table(bucket='parsons_bucket', table=parsons_table, blob_name='parsons_blob')
gcs.get_blob(bucket_name='parsons_bucket', blob_name='parsons_blob')

API

class parsons.google.google_cloud_storage.GoogleCloudStorage(app_creds=None, project=None)

This class requires application credentials in the form of a json. It can be passed in the following ways:

• Set an environmental variable named GOOGLE_APPLICATION_CREDENTIALS with the local path to the credentials json.

  Example: GOOGLE_APPLICATION_CREDENTALS='path/to/creds.json'

• Pass in the path to the credentials using the app_creds argument.

• Pass in a json string using the app_creds argument.

Args:

app_creds: str

A credentials json string or a path to a json file. Not required if GOOGLE_APPLICATION_CREDENTIALS env variable set.

project: str

The project which the client is acting on behalf of. If not passed then will use the default inferred environment.

Returns:

GoogleCloudStorage Class

client

Access all methods of google.cloud package

list_buckets()

Returns a list of buckets

Returns:

List of buckets

bucket_exists(bucket_name)

Verify that a bucket exists

Args:

bucket_name: str

The name of the bucket

Returns:

boolean

get_bucket(bucket_name)

Returns a bucket object

Args:

bucket_name: str

The name of bucket

Returns:

GoogleCloud Storage bucket

create_bucket(bucket_name)

Create a bucket.

Args:

bucket_name: str

A globally unique name for the bucket.

Returns:

None

delete_bucket(bucket_name, delete_blobs=False)

Delete a bucket. Will fail if not empty unless delete_blobs argument is set to True.

Args:

bucket_name: str

The name of the bucket

delete_blobs: boolean

Delete blobs in the bucket, if it is not empty

Returns:

None

list_blobs(bucket_name, max_results=None, prefix=None)

List all of the blobs in a bucket

Args:

bucket_name: str

The name of the bucket

max_results: int

TBD

prefix_filter: str

A prefix to filter files

Returns:

A list of blob names

blob_exists(bucket_name, blob_name)

Verify that a blob exists in the specified bucket

Args:

bucket_name: str

The bucket name

blob_name: str

The name of the blob

Returns:

boolean

get_blob(bucket_name, blob_name)

Get a blob object

Args:

bucket_name: str

A bucket name

blob_name: str

A blob name

Returns:

A Google Storage blob object

put_blob(bucket_name, blob_name, local_path)

Puts a blob (aka file) in a bucket

Args:

blob_name:

The name of blob to be stored in the bucket

bucket_name:

The name of the bucket to store the blob

local_path: str

The local path of the file to upload

Returns:

None

download_blob(bucket_name, blob_name, local_path=None)

Gets a blob from a bucket

Args:

bucket_name: str

The name of the bucket

blob_name: str

The name of the blob

local_path: str

The local path where the file will be downloaded. If not specified, a temporary file will be created and returned, and that file will be removed automatically when the script is done running.

Returns:

str

The path of the downloaded file

delete_blob(bucket_name, blob_name)

Delete a blob

Args:

bucket_name: str

The bucket name

blob_name: str

The blob name

Returns:

None

upload_table(table, bucket_name, blob_name, data_type='csv', default_acl=None)

Load the data from a Parsons table into a blob.

Args:

table: obj

A Parsons Table

bucket_name: str

The name of the bucket to upload the data into.

blob_name: str

The name of the blob to upload the data into.

data_type: str

The file format to use when writing the data. One of: csv or json

Civic

Overview

Google Civic is an API which provides helpful information about elections. In order to access Google Civic you must create a Google Developer Key in their API console. In order to use Google Civic, you must enable this specific end point.

The Google Civic API utilizes the Voting Information Project to collect key civic information such as personalized ballots and polling location information.

Quickstart

To instantiate the GoogleCivic class, you can pass the constructor a string containing the Google Civic API key you’ve generated for your project, or set the environment variable GOOGLE_CIVIC_API_KEY to that value.

from parsons import GoogleCivic

# Set as environment variable so we don't have to pass it in. May either
# be the file name or a JSON encoding of the credentials.
os.environ['GOOGLE_CIVIC_API_KEY'] = 'AIzaSyAOVZVeL-snv3vNDUdw6QSiCvZRXk1xM'

google_civic = GoogleCivic()

Alternatively, you can pass the credentials in as an argument. In the example below, we also specify the project.

google_civic = GoogleCivic(api_key='AIzaSyAOVZVeL-snv3vNDUdw6QSiCvZRXk1xM')

Now you can retrieve election information

elections = google_civic.get_elections()

address = '1600 Pennsylvania Avenue, Washington DC'
election_id = '7000'  # General Election
google_civic.get_polling_location(election_id=election_id, address=address)

API

class parsons.google.google_civic.GoogleCivic(api_key=None)

Args:

api_keystr

A valid Google api key. Not required if GOOGLE_CIVIC_API_KEY env variable set.

Returns:

class

get_elections()

Get a collection of information about elections and voter information.

Returns:

Parsons Table

See Parsons Table for output options.

get_polling_location(election_id, address)

Get polling location information for a given address.

Args:

election_id: int

A valid election id. Election ids can be found by running the get_elections() method.

address: str

A valid US address in a single string.

Returns:

Parsons Table

See Parsons Table for output options.

get_polling_locations(election_id, table, address_field='address')

Get polling location information for a table of addresses.

Args:

election_id: int

A valid election id. Election ids can be found by running the get_elections() method.

address: str

A valid US address in a single string.

address_field: str

The name of the column where the address is stored.

Returns:

Parsons Table

See Parsons Table for output options.

Google Sheets

Overview

The GoogleSheets class allows you to interact with Google service account spreadsheets, called “Google Sheets.” You can create, modify, read, format, share and delete sheets with this connector.

In order to instantiate the class, you must pass Google service account credentials as a dictionary, or store the credentials as a JSON string in the GOOGLE_DRIVE_CREDENTIALS environment variable. Typically you’ll get the credentials from the Google Developer Console (look for the “Google Drive API”).

Quickstart

To instantiate the GoogleSheets class, you can either pass the constructor a dict containing your Google service account credentials or define the environment variable GOOGLE_DRIVE_CREDENTIALS to contain a JSON encoding of the dict.

from parsons import GoogleSheets

# First approach: Use API credentials via environmental variables
sheets = GoogleSheets()

# Second approach: Pass API credentials as argument
credential_filename = 'google_drive_service_credentials.json'
credentials = json.load(open(credential_filename))
sheets = GoogleSheets(google_keyfile_dict=credentials)

You can then create/modify/retrieve documents using instance methods:

sheet_id = sheets.create_spreadsheet('Voter Cell Phones')
sheets.append_to_sheet(sheet_id, people_with_cell_phones)
parsons_table = sheets.get_worksheet(sheet_id)

API

class parsons.google.google_sheets.GoogleSheets(google_keyfile_dict=None)

A connector for Google Sheets, handling data import and export.

Args:

google_keyfile_dict: dict

A dictionary of Google Drive API credentials, parsed from JSON provided by the Google Developer Console. Required if env variable GOOGLE_DRIVE_CREDENTIALS is not populated.

list_worksheets(spreadsheet_id)

Return a list of worksheets in the spreadsheet.

Args:

spreadsheet_id: str

The ID of the spreadsheet (Tip: Get this from the spreadsheet URL)

Returns:

list

A List of worksheets order by their index

get_worksheet_index(spreadsheet_id, title)

Get the first sheet in a Google spreadsheet with the given title. The title is case sensitive and the index begins with 0.

Args:

spreadsheet_id: str

The ID of the spreadsheet (Tip: Get this from the spreadsheet URL)

title: str

The sheet title

Returns:

str

The sheet index

get_worksheet(spreadsheet_id, worksheet=0)

Create a parsons table from a sheet in a Google spreadsheet, given the sheet index.

Args:

spreadsheet_id: str

The ID of the spreadsheet (Tip: Get this from the spreadsheet URL)

worksheet: str or int

The index or the title of the worksheet. The index begins with 0.

Returns:

Parsons Table

See Parsons Table for output options.

share_spreadsheet(spreadsheet_id, sharee, share_type='user', role='reader', notify=True, notify_message=None, with_link=False)

Share a spreadsheet with a user, group of users, domain and/or the public.

Args:

spreadsheet_id: str

The ID of the spreadsheet (Tip: Get this from the spreadsheet URL)

sharee: str

User or group e-mail address, domain name to share the spreadsheet with. To share publicly, set sharee value to None.

share_type: str

The sharee type. Allowed values are: user, group, domain, anyone.

role: str

The primary role for this user. Allowed values are: owner, writer, reader.

notify: boolean

Whether to send an email to the target user/domain.

email_message: str

The email to be sent if notify kwarg set to True.

with_link: boolean

Whether a link is required for this permission.

get_spreadsheet_permissions(spreadsheet_id)

List the permissioned users and groups for a spreadsheet.

Args:

spreadsheet_id: str

The ID of the spreadsheet (Tip: Get this from the spreadsheet URL)

Returns:

Parsons Table

See Parsons Table for output options.

create_spreadsheet(title, editor_email=None)

Create a Google spreadsheet from a Parsons table. Optionally shares the new doc with the given email address.

Args:

title: str

The human-readable title of the new spreadsheet

editor_email: str (optional)

Email address which should be given permissions on this spreadsheet

Returns:

str

The spreadsheet ID

delete_spreadsheet(spreadsheet_id)

Deletes a Google spreadsheet.

Args:

spreadsheet_id: str

The ID of the spreadsheet (Tip: Get this from the spreadsheet URL)

add_sheet(spreadsheet_id, title=None, rows=100, cols=25)

Adds a sheet to a Google spreadsheet.

Args:

spreadsheet_id: str

The ID of the spreadsheet (Tip: Get this from the spreadsheet URL)

rows: int

Number of rows

cols

Number of cols

Returns:

str

The sheet index

append_to_sheet(spreadsheet_id, table, worksheet=0, user_entered_value=False, **kwargs)

Append data from a Parsons table to a Google sheet. Note that the table’s columns are ignored, as we’ll be keeping whatever header row already exists in the Google sheet.

Args:

spreadsheet_id: str

The ID of the spreadsheet (Tip: Get this from the spreadsheet URL)

table: obj

Parsons table

worksheet: str or int

The index or the title of the worksheet. The index begins with 0.

user_entered_value: bool (optional)

If True, will submit cell values as entered (required for entering formulas). Otherwise, values will be entered as strings or numbers only.

overwrite_sheet(spreadsheet_id, table, worksheet=0, user_entered_value=False, **kwargs)

Replace the data in a Google sheet with a Parsons table, using the table’s columns as the first row.

Args:

spreadsheet_id: str

The ID of the spreadsheet (Tip: Get this from the spreadsheet URL)

table: obj

Parsons table

worksheet: str or int

The index or the title of the worksheet. The index begins with 0.

user_entered_value: bool (optional)

If True, will submit cell values as entered (required for entering formulas). Otherwise, values will be entered as strings or numbers only.

format_cells(spreadsheet_id, range, cell_format, worksheet=0)

Format the cells of a worksheet.

Args:

spreadsheet_id: str

The ID of the spreadsheet (Tip: Get this from the spreadsheet URL)

range: str

The cell range to format. E.g. "A2" or "A2:B100"

cell_format: dict

The formatting to apply to the range. Full options are specified in the GoogleSheets API documentation.

worksheet: str or int

The index or the title of the worksheet. The index begins with 0.

Examples

# Set 'A4' cell's text format to bold
gs.format_cells(sheet_id, "A4", {"textFormat": {"bold": True}}, worksheet=0)

# Color the background of 'A2:B2' cell range yellow,
# change horizontal alignment, text color and font size
gs.format_cells.format(sheet_id, "A2:B2", {
    "backgroundColor": {
        "red": 0.0,
        "green": 0.0,
        "blue": 0.0
        },
    "horizontalAlignment": "CENTER",
    "textFormat": {
        "foregroundColor": {
            "red": 1.0,
            "green": 1.0,
            "blue": 0.0
            },
            "fontSize": 12,
            "bold": True
            }
        }, worksheet=0)