ReviewPro is a cloud-based platform that helps hospitality businesses manage their online reputation and improve guest experiences. It aggregates reviews from a wide range of online travel agents and review sites, including Google and TripAdvisor. It provides a dashboard to track, measure, and respond to reviews in real time.

This article provides an overview to get started with the Shiji ReviewPro connector in Peliqan. Please contact support if you have any additional questions or remarks.

Contents
ReviewPro Data Pipeline
Fetching API key and API Secret
Connect Shiji Reviewpro
Shiji ReviewPro data sync to a data warehouse
Shiji ReviewPro Data Activation
Custom ETL Pipeline to sync Average Ratings and Review Ratings based on Date Intervals
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ReviewPro Data Pipeline

Fetching API key and API Secret

Connecting to Shiji ReviewPro APIs requires API key and API Secret. API Keys are on Application level. Hence, it is required to create an Application and corresponding API key and API Secret.

Connect Shiji Reviewpro

Connect Shiji ReviewPro through the Peliqan Connectivity module:

Configuration options:

API Key
API Secret
Start Date in YYYY-MM-DD format.
(Optional) table selection via ‘Advanced’

Click save to initiate the connection and allowing ReviewPro data to get synced to Peliqan DataWarehouse.

API Key and API secret are combined to form a signature for Authentication purpose.

Shiji ReviewPro data sync to a data warehouse

Peliqan offers an out of the box data warehouse. Optionally the user can choose to sync ReviewPro data to their own data warehouse such as Snowflake, Google BigQuery, MS SQL etc.

“Lodging” related data is retrieved in Peliqan for ReviewPro based on Date Intervals. Date intervals can be daily, weekly, monthly or yearly. For more details, refer Shiji ReviewPro Data Activation below.

Data will be synced to the chosen data warehouse and made available through the Peliqan UI for exploration.

Data gets synced every 6 hours.

With the Peliqan federated query engine, queries on the Shiji ReviewPro data can be written and data can be transformed and combined with other sources.

Shiji ReviewPro Data Activation

Custom ETL Pipeline to sync Average Ratings and Review Ratings based on Date Intervals

Peliqan offers Shiji ReviewPro data activation functions for generating review ratings or average index ratings based on date intervals. This is achieved through Custom Pipeline in Peliqan. Related data is generated, accumulated and stored in Peliqan DataWareHouse. Writing to DataWarehouse is done using write() method in Peliqan.

Below is the custom Pipeline Script to get Weekly Average Indexed Ratings, Monthly Average Indexed Ratings, Monthly Average Rating Reviews.

# Required Imports

from datetime import date, datetime
from dateutil.relativedelta import relativedelta
import time
import calendar


# Required helper functions
def get_month_end_date(date):
    month_end_date = calendar.monthrange(date.year, date.month)[1]
    return f"{date.year}-{date.month}-{month_end_date}"

def get_start_date(connection_name):
    connections = pq.list_connections()
    for connection in connections:
        if connection['name'] == connection_name:
            return connection['param1']



# Required Inputs
connection_name = 'Shiji ReviewPro' 
source_schema_name = 'shiji reviewpro'
source_tables = 'available_hotels'
END_DATE = date.today()

# setting start date
START_DATE = get_start_date(connection_name)  # fetching from connect-form

# required data objects
monthly_avg_indexed_ratings, weekly_avg_indexed_ratings, monthly_avg_rating_reviews  = [], [], []


# Required Connections
source_conn = pq.connect(connection_name)
dbconn = pq.dbconnect(pq.DW_NAME)

# fetching all the available Hotels
st.text('Fetching Hotels....')
hotels_list = dbconn.fetch(pq.DW_NAME, source_schema_name, source_tables)


# Fecthing monthly data: 
st.text(f"Syncing Streams from {START_DATE} ....")

for hotel in hotels_list:

    # monthly_avg_indexed_ratings - monthly_avg_rating_reviews 
    date_iter = datetime.strptime(START_DATE, '%Y-%m-%d').date()
    while date_iter <= date.today():   # '=' considering same start_date and current_date | YYYY-MM-DD
 
        body = {
            'pid': hotel['id'],
            'start_date': str(date_iter),
            'end_date': get_month_end_date(date_iter)    
        }
        # Monthly average index rating : 
        index_rating_result = source_conn.get('average_index_rating', body)
        index_rating_result['year'] = date_iter.year
        index_rating_result['month'] = date_iter.strftime("%B").lower()
        index_rating_result[ 'external_id'] = str( index_rating_result['pid'] ) + "_" + str(date_iter.year) + "_" + date_iter.strftime("%B").lower() 
        monthly_avg_indexed_ratings.append(index_rating_result)

        time.sleep(0.5)    # to avoid rate limiting

        # Monthly average review rating
        review_rating_result = source_conn.get('average_review_rating_distribution', body)
        review_rating_result['year'] = date_iter.year
        review_rating_result['month'] = date_iter.strftime("%B").lower() 
        review_rating_result[ 'external_id'] = str(review_rating_result['pid']) + "_" + str(date_iter.year) + "_" +  date_iter.strftime("%B").lower() 
        monthly_avg_rating_reviews.append(review_rating_result)

        date_iter += relativedelta(months=1)          # moving interation cursor
        time.sleep(0.5)

    # weekly_avg_indexed_ratings
    date_iter = datetime.strptime(START_DATE, '%Y-%m-%d').date()
    while date_iter <= date.today():  
        
        body = {
            'pid': hotel['id'],
            'start_date': str(date_iter),
            'end_date': date_iter + relativedelta(weeks=1)   
        }
        weekly_index_result = source_conn.get('average_index_rating', body)
        weekly_index_result['year'] = date_iter.year
        weekly_index_result['week'] = date_iter.strftime("%U")
        weekly_index_result[ 'external_id'] =  str(weekly_index_result['pid']) + "_" + str(date_iter.year) + "_" + date_iter.strftime("%U")
        weekly_avg_indexed_ratings.append(weekly_index_result)

        # moving interation cursor
        date_iter += relativedelta(weeks=1)
        time.sleep(0.5)


# writing data to our datawarehouse

for stream_name, data in {'monthly_avg_indexed_ratings': monthly_avg_indexed_ratings, 'weekly_avg_indexed_ratings': weekly_avg_indexed_ratings, 'monthly_avg_rating_reviews': monthly_avg_rating_reviews}.items():

    write_result = dbconn.write(source_schema_name, stream_name, records = data , pk='external_id')
    if write_result['status'] == 'success' :
        st.text(f"Data Synced for stream {stream_name}! ")
    else:
        st.text(f"Error while syncing stream {stream_name}! ")
        st.json(write_result)


exit(0)

Need further help

Please contact our support for any further assistance via support@peliqan.io.

Shiji ReviewPro - Getting Started in Peliqan