Test Automation Scope - ja-guzzle/guzzle_docs GitHub Wiki

guzzle_regression_test_suite_v0.4.xlsx

https://medium.com/@briananderson2209/best-automation-testing-tools-for-2018-top-10-reviews-8a4a19f664d2

Guzzle test suit supported syntax:

Given: Used to setup source files and database tables for a test case.

• Database:
  • Supported configuration format:
    • JDBC (MySQL, hive, phoenix). Hive DB is accessed via JDBC (as this step is done by Cucumber directly and not via Spark)
  • Source table structure format:
    • Table format
    • SQL query format as "CREATE TALE xxx"
  • Table data ingestion format:
    • Table format
    • SQL query format as " INSERT INTO... xxx"
• File Source:
  • Supported file system and format:
    • file system: LFS, HDFS, DBFS, Adls Gen2, S3
    • file format: delimited, json, xml, control file, fixed file format, simple text file, excel, parquet
  • Create a source file with data:
    • Table structure
    • raw file content given as JSON, XML, Log files etc (Yet to be built)
    • Other supported options, like file path, format, delimiter, file system, header etc.
    • path to an existing file which points (yet to be built) - this can be any format including excel

When: Used to executed guzzle job with specified parameters.

• Run job:
  • job name
  • job parameters (key value format)
• Run job group:
  • job group name
  • job parameters (key value format)
• Initialize batch:
  • batch parameters (key value format)
• Execute batch:
  • batch parameters (key value format)

Then: Used to compare job result and expected result.

• Fetch actual data:
  • Database:
    • Supported configuration format:
      • jdbc (hive, phoenix, MySQL, SQL Server, delta)
    • Fetch table data options:
      • database and table name
      • database and table name and filter condition
      • database and select SQL query
  • File:
    • Supported file system and format:
      • file system: LFS, HDFS, DBFS, Adls Gen2, S3
      • file format: delimited, json, xml, control file, excel, parquet
    • Fetch file data options:
      • file system, file format and file path
• Expected data:
  • Table format
  • Existing table in JDBC
• compare data:
  • compare actual and expected records by specified primary key(multiple column by comma(,) separated)
  • compare only specified columns