pyshopify 0.9.0

Shopify Order API library with containeriezed MS SQL database

Shopify Orders Rest API Wrapper and Data Export

This is a python library that pulls and parses shopify rest orders api. Currently the only Shopify endpoint available is the Orders api.

This has the flexibility of exporting the data to a SQL Server ( along with other relational dbs), exporting to csv and returning a dictionary of dataframes.

The Structure of the SQL Database is in the Docs folder, an SQL script to build the database is in the scripts folder.

Script Configuration file

Configuration is done through an ini based file. Here is the template:

[shopify]
# Orders API Endpoint
url_base = https://**YOURSTORE**.myshopify.com
order_ep = /admin/api/2020-10/orders.json

# Shopify Access Token
access_token = ***ACCESS TOKEN FROM ADMIN***

# Earliest date
early_date = 20000101

# Items per Return - 250 Max
items_per_page = 250

# Uncomment to get data between two dates
# Overrides past days of history
# start = 20210610
# end = 20210617

# Get past days of history - 30 days is default
days = 30

[sql]
enable = False

# Driver for pyodbc to use
driver = ODBC Driver 17 for SQL Server

# Database server & port
server = ***DATABASE SERVER***
port = 1433
database = ***DATABASE***

# Database user & password
db_user = ***DB USER***
db_pass = ***DB PASSWORD***

[csv]
enable = True
# Relative filepath of csv folder output
filepath = csv_export

[custom]
#Output dictionary of dataframes
enable = False

The configuration file will default to config.ini in the current working directory. A custom path can be defined by passing to ShopifyApp('rel/path/config.ini') when instantiating or the cli_runner --config rel/path/config.ini

Installing Base Library

Install from PyPi through pip install. This will install all required dependencies for running to export to CSV and return a dictionary of dataframes.

$ python3 -m pip install pyshopify

Library with SQL Driver

In order to use the sql output feature, the database driver and python library must be installed.

On linux it takes several steps. pyodbc must be installed as root user.

$ apt-get install -y unixodbc-dev msodbcsql17
$ sudo -H python3 -m pip install pyodbc
$ python3 -m pip install sqlalchemy 

Ensure MS ODBC driver is installed on Windows. Can be found Microsoft SQL OBC Driver

Running the ShopifyApp()

The primary class is ShopifyApp() which contains all of the necessary execution methods.

Can be run two ways:

As a module:

from pyshopify.runner import ShopifyApp

# Get one day history of orders and return flattened dictionary
shop_class = ShopifyApp('rel/dir/to/config.ini')

run = ShopifyApp.app_runner()

# if custom is enabled -
# Dataframe columns are same as database columns 

# Order Details
# ['id' 'order_date' 'fulfillment_status' 'name' 'number' 'order_number', 'payment_gateway_names' 'processing_method' 'source_name', 'subtotal_price' 'total_discounts' 'total_line_items_price' 'total_price', 'total_price_usd' 'total_tax' 'total_weight']
orders_dataframe = run.get("Orders")

# Refunds Dataframe with Date of Refund and Order ID
# Columns    ['refund_date', 'order_id']
refunds_dataframe = run.get("Refunds")

# Dataframe of Refund Line Items Showing Units returned
# ['id', 'line_item_id', 'quantity', 'subtotal', 'total_tax', 'variant_id', 'refund_id', 'order_id']
refund_lineitems = run.get("RefundLineItems")

# Dataframe of Line Items sold
# ['id', 'order_id', 'order_date', 'variant_id', 'quantity', 'price']
line_items = run.get("LineItems")

# Dataframe of customer for each order and customer info
# ['order_id', 'order_date', 'email', 'customer_id', 'orders_count', 'total_spent', 'created_at']
customer_orders = run.get("OrderCustomers")

From command line:

# There are different command options
$ shopify_cli --help
Usage: shopify_cli [OPTIONS]

  Run Shopify App CLI.

Options:
  -d, --days INTEGER     get days of history
  -b, --between TEXT...  get between 2 dates - yyyy-MM-dd, ex -b 2020-01-01
                         2020-01-02
  --sql-out / --no-sql   write to database - Default False
  --csv-out / --no-csv   Write results to csv files - Default true
  --csv-location TEXT    Relative location of csv export folder defaults to
                         csv_export/
  --config TEXT          Relative location of config.ini - defaults to
                         config.ini in currect directory
  --help                 Show this message and exit.

# Default arguments are:
$ shopify_cli -d 30 --csv-out --no-sql --config config.ini

$ shopify_cli -d 30 # get last 30 days of orders and export to CSV in CWD/csv_export
$ shopify_cli -b 2020-01-01 2020-01-02 # get orders between dates and export csv
$ shopify_cli -d 30 --sql-out # update SQL db

Enabling the custom section of config.ini will return a dictionary of order data parsed into separate key-value pairs that allow easier processing and analysis. Using the sql option will update an SQL Database with the data from the dictionary.

The structure of the custom return dictionary reflects the SQL database structure that it will update:

from pyshopify import ShopifyApp

# Enable custom in config.ini
shop_app = ShopifyApp()

app_run = shop_app.app_runner()

app_run = {
      'Orders': OrdersDataframe,
      'Customers': CustomersDataframe,
      'LineItems': LineItemDataFrame
      'Refunds': RefundDataFrame,
      'RefundLineItem': RefLineItem.DataFrame,
      'Adjustments': RefundAdjustmentsDataFrame
}

Each dataframe in the return represents an SQL Table in the database. The dataframe column types match the database column types.

Database Structure

Exporting SQL from API response is two step process:

1. Send DataFrame to temporary SQL Table
2. Run stored procedure to merge temp table with the appropriate table

The full database documentation is located here

Click on each item for more details.

shop_rest is the default database name. Remember to change config.ini if using a different database name.

Tables

Name	Description
dbo.Adjustments	Order Refund Adjustments
dbo.DateDimension	Date Dimension Table for Analysis
dbo.LineItems	Line Items with Units Sold for Orders
dbo.OrderCustomers	Customer Info based on Order ID
dbo.Orders	Order Details
dbo.RefundLineItem	Refunded Units
dbo.Refunds	Order Refunds

Stored Procedures

Name	Description
dbo.adjustments_update	Update Adjustments
dbo.cust_update	Update Customer Orders Table
dbo.lineitems_update	Update Line Items
dbo.orders_update	Merge Orders
dbo.reflineitem_update	Merge Refunded Line Items
dbo.refunds_update	Merge Refunds

A DateDimension table is included for easier analysis

Database script

To build the dataabse, run the setup.sql script in the docker/scripts folder. This has only been tested on Microsoft SQL Server 2019 but can easily be adapted for other databases. It will set up all of the required tables and stored procedures.

Docker Container

There is a Dockerfile and docker-compose.yml in the docker folder. This is based on the Microsoft SQL Server 2019 container running on Ubuntu. It installs all of the necessary applications to run pyshopify and a database instance to write to.

NOTE: This is NOT production ready. Security is not hardened, container is run as root user.

Both containers automatically deploy setup.sql to build the required database structure.

Please make sure to set the password in the docker-compose.yml file.

Download entire docker folder or just clone repo

$ git clone https://github.com/webdjoe/pyshopify
$ cd docker

Use vim or nano to edit docker-compose.yml and config.ini in config folder

$ vim docker-compose.yml
$ vim config/config.ini

Build & Run container. Use -d for detached

$ docker-compose build
$ docker-compose run -d

Once started test if SQL server is running. A 0 return value indicates the server has started up.

$ docker exec -it shopsql /opt/mssql-tools/bin/sqlcmd -h -1 -t 1 -U sa -P "$SA_PASSWORD" -Q "SET NOCOUNT ON; Select SUM(state) from sys.databases")

shopify_cli can be called in container to update database. Or the server can be updated from an external application.

Get last 30 days of data and import into SQL Server running in container
$ docker exec -it shopsql shopify_cli -d 30 --no-csv --sql-out

Get data between dates and import into SQL Server running on container 
$ docker exec -it shopsql shopify_cli -b 20200101 20201231 --no-csv --sql-out