'site_name': '<YOUR_SITE_NAME>',
'site_url': '<YOUR_SITE_URL>'
}
}
conn = TableauServerConnection(config, env='tableau_staging')
#Logging into Tableau server
conn.sign_in()
# get a dataframe which has all the sites present, we can access contentUrl from this dataframe to loop over.
sites = get_sites_dataframe(conn)
print(f'Avaiable sites are {sites}')
for i in sites['contentUrl']:
conn.switch_site(i) # switching to the site for each site in a list
print(f'Current site is {i}')
# getting a dataframe of all users in that current site
all_users_data = get_users_dataframe(conn)
# converting last-login columns to a datetime column as currently it is Object type
all_users_data['lastLogin'] = pd.to_datetime(all_users_data['lastLogin'])
# creating a new column with just now() time, converting to same timezone as lastLogin Column else it will throw TypeError: DatetimeArray subtraction must have the same timezones or no timezones
all_users_data['later_time'] = datetime.now(tz=timezone.utc)
all_users_data['duration in days'] = (all_users_data['later_time'] -
all_users_data['lastLogin']).dt.days
# Filtering out all users email address and their names so that we can contact them , where days not logegd is greater than n days
users_not_logged_in = all_users_data[
# signing in to the Tableau server
conn.sign_in()
# get all the sites on Server in a dataframe
sites_data = get_sites_dataframe(conn)
site_choose = input('Under which site do you want to publish the data source ')
project_choose = input(
'Under which Project do you want to publish the data source ')
x = str(sites_data[sites_data['name'] == site_choose]['contentUrl'])
##print(type(x))
#print(x.split()[1])
# Switching to the site which user entered, and where he want to publish data source
conn.switch_site(x.split()[1])
res = conn.query_projects()
# gettign the project site where we want to publish our data sources
project_id = [
i['id'] for i in res.json()['projects']['project']
if i['name'] == project_choose
]
project_id = str(project_id[0])
print(project_id)
# changing to the directory where all our data sources are saved
# looping over all data sources and publsihing them on server
for i in glob.glob('/Users/surbhiagrawal/Downloads/sample/*.hyper'):
print(i.split('/')[-1])