Datastore Testibility
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tester_test_discovery_expect_users.json refactoring Feb 22, 2018
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README.md

Datastore Testibility (dsunit)

Datastore testibility library for Go. GoDoc

This library is compatible with Go 1.5+

Please refer to CHANGELOG.md if you encounter breaking changes.

Introduction

Data focused testing belongs to blackbox group, where the main interest goes down to the initial and final state of the datastore.

To set the initial state of ta datastore, this framework provies utilities to either create empty datastore, or to prepare it with dataset data to test that application works correctly.

The final state testing focuses on checking that a dataset data matches an expected set of values after application logic run. In this case this library has ability to verify either complete or snapshot state of a datastore. While the first approach will be comparing all tables data with expected set of values, the latter will reduced verification to the range provided by expected dataset.

Motivation

This library has been design to provide easy and unified way of testing any datastore (SQL, NoSSQL,file logs) on any platform, language and on the cloud. It simplifies test organization by dataset auto discovery used for datastore preparation and verification. Dataset data can be loaded from various sources like: memory, local or remote csv, json files. All dataset support macro expression to dynamically evaluate value of data i.e <ds:sql ["SELECT CURRENT_DATE()"]> On top of that expected data, can also use predicate expressions to delegate verification of the data values i.e. <ds:between [11301, 11303]>. Finally a dataset like a view can be used to store data for many datastore sources in in just one dataset file.

Datastore initialization and dataset data verification can by managed locally or remotely on remote data store unit test server.

##Usage

import (
	"testing"
	"github.com/viant/dsunit"
	_ "github.com/go-sql-driver/mysql"
)


func TestSetup(t *testing.T) {

    var verticaRequest = dsunit.NewScriptRequest(...)

    dsunit.InitFromURL(t, "test/init.json")
	dsunit.RunScript(t, verticaRequest)
	dsunit.PrepareFromURL(t, "mytestdb")
	
	
	... business test logic comes here
	
	dsunit.ExpectFromURL(t, "mytestdb", dsunit.SnapshotDatasetCheckPolicy)
	
	
	
}

Tester methods

Service Methods Description Request Response
Register(t *testing.T, request *RegisterRequest) bool register database connection RegisterRequest RegisterResponse
RegisterFromURL(t *testing.T, URL string) bool as above, where JSON request is fetched from URL/relative path RegisterRequest RegisterResponse
Recreate(t *testing.T, request *RecreateRequest) bool recreate database/datastore RecreateRequest RecreateResponse
RecreateFromURL(t *testing.T, URL string) bool as above, where JSON request is fetched from URL/relative path RecreateRequest RecreateResponse
RunSQL(t *testing.T, request *RunSQLRequest) bool run SQL commands RunSQLRequest RunSQLResponse
RunSQLFromURL(t *testing.T, URL string) bool as above, where JSON request is fetched from URL/relative path RunSQLRequest RunSQLResponse
RunScript(t *testing.T, request *RunScriptRequest) bool run SQL script RunScriptRequest RunSQLResponse
RunScriptFromURL(t *testing.T, URL string) bool as above, where JSON request is fetched from URL/relative path RunScriptRequest RunSQLResponse
AddTableMapping(t *testing.T, request *MappingRequest) bool register database table mapping (view), MappingRequest MappingResponse
AddTableMappingFromURL(t *testing.T, URL string) bool as above, where JSON request is fetched from URL/relative path MappingRequest MappingResponse
Init(t *testing.T, request *InitRequest) bool initialize datastore (register, recreate, run sql, add mapping) InitRequest MappingResponse
InitFromURL(t *testing.T, URL string) bool as above, where JSON request is fetched from URL/relative path InitRequest MappingResponse
Prepare(t *testing.T, request *PrepareRequest) bool populate databstore with provided data PrepareRequest MappingResponse
PrepareFromURL(t *testing.T, URL string) bool as above, where JSON request is fetched from URL/relative path PrepareRequest MappingResponse
PrepareDatastore(t *testing.T, datastore string) bool match to populate all data files that are in the same location as a test file, with the same test file prefix, followed by lowe camel case test name n/a n/a
PrepareFor(t *testing.T, datastore string, baseDirectory string, method string) bool match to populate all data files that are located in baseDirectory with method name n/a n/a
Expect(t *testing.T, request *ExpectRequest) bool verify databstore with provided data ExpectRequest MappingResponse
ExpectFromURL(t *testing.T, URL string) bool as above, where JSON request is fetched from URL/relative path ExpectRequest MappingResponse
ExpectDatasets(t *testing.T, datastore string, checkPolicy int) bool match to verify all data files that are in the same location as a test file, with the same test file prefix, followed by lowe camel case test name n/a n/a
ExpectFor(t *testing.T, datastore string, checkPolicy int, baseDirectory string, method string) bool match to verify all dataset files that are located in the same directory as the test file with method name n/a n/a

Validation

This library uses assertly as the undelying validation mechanism

Macros

The macro is an expression with parameters that expands original text value. The general format of macro: <ds:MACRO_NAME [json formated array of parameters]>

The following macro are build-in:

Name Parameters Description Example
sql SQL expression Returns value of SQL expression <ds:sql["SELECT CURRENT_DATE()"]>
seq name of sequence/table for autoicrement Returns value of Sequence <ds:seq["users"]>

Predicates

Predicate allows expected value to be evaluated with actual dataset value using custom predicate logic.

Name Parameters Description Example
between from, to values Evaluate actual value with between predicate <ds:between[1.888889, 1.88889]>
within_sec base time, delta, optional date format Evaluate if actual time is within delta of the base time <ds:within_sec["now", 6, "yyyyMMdd HH:mm:ss"]>

Directives

Data preparation

Most SQL drivers provide meta data about autoincrement, primary key, however if this is not available or partial verification with SQL is used, the following directive come handy.

@autoincrement@

Allows specifying autoincrement field

[
  {"@autoincrement@":"id"},
  {"id":1, "username":"Dudi", "active":true, "salary":12400, "comments":"abc","last_access_time": "2016-03-01 03:10:00"},
  {"id":2, "username":"Rudi", "active":true, "salary":12600, "comments":"def","last_access_time": "2016-03-01 05:10:00"}
]

@indexBy@

(see also asserly indexBy directive usage, for nested data structe validation)

Allows specifying pk fields

[
  {"@indexBy@":["id"]},
  {"id":1, "username":"Dudi", "active":true, "salary":12400, "comments":"abc","last_access_time": "2016-03-01 03:10:00"},
  {"id":2, "username":"Rudi", "active":true, "salary":12600, "comments":"def","last_access_time": "2016-03-01 05:10:00"}
]

Data validation.

@fromQuery@

Allows specified query to fetch actual dataset to be validated against expected dataset

users.json

[
  {"@fromQuery@":"SELECT *  FROM users where id <= 2 ORDER BY id"},
  {"id":1, "username":"Dudi", "active":true, "salary":12400, "comments":"abc","last_access_time": "2016-03-01 03:10:00"},
  {"id":2, "username":"Rudi", "active":true, "salary":12600, "comments":"def","last_access_time": "2016-03-01 05:10:00"}
]

API Documentation

API documentation is available in the docs directory.

GoCover

GoCover

Examples

This project provide a various datasore dsunit integration examples (some with docker vi endly).

RDBMS

NoSQL

External projects::

License

The source code is made available under the terms of the Apache License, Version 2, as stated in the file LICENSE.

Individual files may be made available under their own specific license, all compatible with Apache License, Version 2. Please see individual files for details.

Credits and Acknowledgements

Library Author: Adrian Witas

Contributors: Sudhakaran Dharmaraj