Piñata

Piñata is a simple and lightweight .NET library for managing database state during integration testing.

Compatibility

.Net Framework 4.5 or higher

Database server supports

MySQL (5.0 or higher)
MongoDB (2.6 or higher)
Microsoft SQL Server - coming soon
SQLLite - coming soon
PostgreSQL - coming soon
Oracle - coming soon

Getting Started

How to install via NugGet

To install Piñata, run the following command in the Package Manager Console

PM> Install-Package Pinata

How it Works

Given a JSON file having tables schema and data you want to handle, Piñata organize a dataset and try to execute insert and delete command into a database. Actually it works with MySQL and MongoDB.

Data Schema

JSON file should provide an array describing table's schema including primary and foreign keys, and the rows you want to handle. The following sample shows a JSON data for MySQL database:

[
  {
    "Table": "TestPinata_Actor",
    "Keys": [ "Id" ],
    "Schema": [
        {
            "Column": "Id",
            "Type": "guid"
        },
        {
            "Column": "Name",
            "Type": "string"
        }
    ],
    "Rows": [
        {
            "Id": "b3e6447b-38e3-11e6-8aa3-0003ff500b9d",
            "Name": "Chris Evans"
        },
        {
            "Id": "dee91372-38e3-11e6-8aa3-0003ff500b9d",
            "Name": "Robert Downey Jr."
        },
        {
            "Id": "e4b94626-38e3-11e6-8aa3-0003ff500b9d",
            "Name": "Scarlett Johansson"
        },
        {
            "Id": "1cb9da05-38e5-11e6-8aa3-0003ff500b9d",
            "Name": "Ryan Reynolds"
        },
        {
            "Id": "1cb9da05-38e5-11e6-8aa3-0003ff500b9e",
            "Name": "dynamic_param"
        }

    ],
    "FK_References": [ ]
  }
]

Field	Type	Description	Observation
Table	string	name of table inside database
Keys	array	primary keys of table	used as reference to execute delete operations
Schema	array	type of data value to each column	types: int, long, short, byte, bool, string, char, guid, double, decimal, float, datetime, array, document, objectid
Rows	array	data to insert on database
FK_References	array	foreign key tables

Piñata allows you to work with MongoDB. The structure is similar to MySQL except that you don't need foreign keys, as the following sample:

[
    {
        "Collection": "TestPinata_Movie",
        "Keys": [ "_id" ],
        "Schema": [
            {
                "Column": "_id",
                "Type": "objectId"
            },
            {
                "Column": "Name",
                "Type": "string"
            }
        ],
        "Rows": [
            {
                "_id": "577aedd825e7695ec2a81145",
                "Name": "Capitan America - Civil War"
            },
            {
                "_id": "577aedfc25e7695ec2a81147",
                "Name": "Avengers"
            }            
        ]
    }
]

Field	Type	Description	Observation
collection	string	name of collection inside database
Keys	array	unique identifier for collection	used as reference to execute delete operations
Schema	array	type of data value to each column	types: int, long, short, byte, bool, string, char, guid, double, decimal, float, datetime, array, document, objectid
Rows	array	data to insert on database

Hands On

After create your data schema and install Piñata into your project, you can start an instance. Work with MySQL requires a ProviderType, otherwise you just need provide your database address. The next step is having Piñata read the data schema file by the Feed method.

Pinata pinata = new Pinata(ConfigurationManager.ConnectionStrings["myConnectionString"].ToString(), Provider.Type.MySQL);

pinata.Feed("sample/data.json");

Is recommended to execute a delete command before the insert to ensure data coherence.

pinata.Execute(CommandType.Delete);

pinata.Execute(CommandType.Insert);

Another way to load data is provide a JSON struct passing variables instead values. You'll keep the same data schema but the Execute command must have a dictionary with the corresponding parameters.

private IDictionary<string, string> parameters = new Dictionary<string, string>();

parameters.Add("dynamic_param", "Lights Out");

pinata.Execute(CommandType.Insert, parameters);

Documentation

Pinata Class

new Pinata(options)

Pinata pinata = new Pinata(ConfigurationManager.ConnectionStrings["myConnectionString"].ToString(), Provider.Type.MySQL);

or

Pinata pinata = new Pinata(ConfigurationManager.ConnectionStrings["myConnectionString"].ToString(), Provider.Type.MySQL, "data1.json", "data2.json");

Parameter	Type	optional	Description
ConnectionString	string	false
Provider	enum	false	values: Provider.Type.MySQL , Provider.Type.MongoDB
SamplePath	array	true	array of json files, this is optional you can load json files direct from feed method as well.

Feed(options)

pinata.Feed();

or

pinata.Feed("data1.json");

Parameter	Type	optional	Description
SamplePath	array	true	array of json files, this is optional you can load json files direct from Piñata constructor as well.

Execute(options)

pinata.Execute(CommandType.Insert);

or

pinata.Execute(CommandType.Insert, Parameters);

Parameter	Type	optional	Description
CommandType	enum	false	type of command to execute. values: CommandType.Insert, CommandType.Delete.
Parameters	dictionary	true	dictionary having variable name and value

Supported data types at schema

Int
Long
Short
Byte
Bool
String
Char
Guid
Double
Decimal
Float
DateTime
Array
Document
ObjectId

Examples

JSON example of tables with relationship to SQL database

[
    {
        "Table": "TestPinata_Movie",
        "Keys": [ "Id" ],
        "Schema": [
            {
                "Column": "Id",
                "Type": "guid"
            },
            {
                "Column": "Name",
                "Type": "string"
            },
            {
                "Column": "CategoryId",
                "Type": "int"
            }
        ],
        "Rows": [
            {
                "Id": "adef64eb-38e4-11e6-8aa3-0003ff500b9d",
                "Name": "Capitan America - Civil War",
                "CategoryId": "1"
            },
            {
                "Id": "b6210be7-38e4-11e6-8aa3-0003ff500b9d",
                "Name": "Avangers",
                "CategoryId": "4"
            },
            {
                "Id": "ddbb311a-38e4-11e6-8aa3-0003ff500b9d",
                "Name": "Deadpool",
                "CategoryId": "1"
            }
        ],
        "FK_References": [
            { "Table": "TestPinata_Category" }
        ]
    },
    {
        "Table": "TestPinata_MovieActor",
        "Keys": [ "MovieId", "ActorId" ],
        "Schema": [
            {
                "Column": "MovieId",
                "Type": "guid"
            },
            {
                "Column": "ActorId",
                "Type": "guid"
            }
        ],
        "Rows": [
            {
                "MovieId": "adef64eb-38e4-11e6-8aa3-0003ff500b9d",
                "ActorId": "b3e6447b-38e3-11e6-8aa3-0003ff500b9d"
            },
            {
                "MovieId": "adef64eb-38e4-11e6-8aa3-0003ff500b9d",
                "ActorId": "dee91372-38e3-11e6-8aa3-0003ff500b9d"
            },
            {
                "MovieId": "adef64eb-38e4-11e6-8aa3-0003ff500b9d",
                "ActorId": "e4b94626-38e3-11e6-8aa3-0003ff500b9d"
            },
            {
                "MovieId": "ddbb311a-38e4-11e6-8aa3-0003ff500b9d",
                "ActorId": "1cb9da05-38e5-11e6-8aa3-0003ff500b9d"
            }
        ],
        "FK_References": [
            { "Table": "TestPinata_Movie" },
            { "Table": "TestPinata_Actor" }
        ]
    },
    {
        "Table": "TestPinata_Actor",
        "Keys": [ "Id" ],
        "Schema": [
            {
                "Column": "Id",
                "Type": "guid"
            },
            {
                "Column": "Name",
                "Type": "string"
            }
        ],
        "Rows": [
            {
                "Id": "b3e6447b-38e3-11e6-8aa3-0003ff500b9d",
                "Name": "Chris Evans"
            },
            {
                "Id": "dee91372-38e3-11e6-8aa3-0003ff500b9d",
                "Name": "Robert Downey Jr."
            },
            {
                "Id": "e4b94626-38e3-11e6-8aa3-0003ff500b9d",
                "Name": "Scarlett Johansson"
            },
            {
                "Id": "1cb9da05-38e5-11e6-8aa3-0003ff500b9d",
                "Name": "Ryan Reynolds"
            }
        ],
        "FK_References": [ ]
    },
    {
        "Table": "TestPinata_Category",
        "Keys": [ "Id" ],
        "Schema": [
            {
                "Column": "Id",
                "Type": "int"
            },
            {
                "Column": "Name",
                "Type": "string"
            }
        ],
        "Rows": [
            {
                "Id": "1",
                "Name": "Action"
            },
            {
                "Id": "2",
                "Name": "Sci-Fi"
            },
            {
                "Id": "3",
                "Name": "Thriller"
            },
            {
                "Id": "4",
                "Name": "Adventure"
            }
        ],
        "FK_References": [ ]
    }
]

JSON example of collection with complex documents to MongoDB

[
    {
        "Collection": "TestPinata_User",
        "Keys": [ "_id" ],
        "Schema": [
            {
                "Column": "_id",
                "Type": "objectId"
            },
            {
                "Column": "Email",
                "Type": "string"
            },
            {
                "Column": "Age",
                "Type": "int"
            },
            {
                "Column": "Birthday",
                "Type": "datetime"
            },
            {
                "Column": "Interest",
                "Type": "array"
            },
            {
                "Column": "Address",
                "Type": "document"
            }
        ],
        "Rows": [
            {
                "_id": "577aedd825e7695ec2a81145",
                "Email": "teste@soclminer.com.br",
                "Age": "28",
                "Birthday": "1990-01-25T10:30:00.000Z",
                "Interest": [ "sports" ],
                "Address": {
                    "Street": "R. Maria Carolina, 1001",
                    "District": "Jardim Paulistano",
                    "City": "São Paulo",
                    "State": "SP"
                }
            },
            {
                "_id": "577aedfc25e7695ec2a81147",
                "Email": "teste2@soclminer.com.br",
                "Age": "31",
                "Birthday": "1985-03-15T00:00:00.000Z",
                "Interest": [ "series", "anime", "sports" ],
                "Address": {
                    "Street": "R. Maria Carolina, 1001",
                    "District": "Jardim Paulistano",
                    "City": "São Paulo",
                    "State": "SP"
                }
            }
        ]
    }
]

OSS Libraries used

Jil
[Dapper] (https://github.com/StackExchange/dapper-dot-net)
[Mongo C# Driver] (https://github.com/mongodb/mongo-csharp-driver)
[MySQL .NET Driver] (https://github.com/mysql/mysql-connector-net)

License

This software is licensed in MIT License (MIT)

Name		Name	Last commit message	Last commit date
Latest commit History 87 Commits
.nuget		.nuget
.vs/config		.vs/config
Pinata.Core		Pinata.Core
Pinata.Data		Pinata.Data
Pinata.Package		Pinata.Package
Pinata.UnitTest		Pinata.UnitTest
Pinata		Pinata
.gitignore		.gitignore
LICENSE		LICENSE
Pinata.sln		Pinata.sln
README.md		README.md

License

rmattos/Pinata

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Piñata

Compatibility

Database server supports

Getting Started

How to install via NugGet

How it Works

Data Schema

Hands On

Documentation

Pinata Class

new Pinata(options)

Feed(options)

Execute(options)

Supported data types at schema

Examples

JSON example of tables with relationship to SQL database

JSON example of collection with complex documents to MongoDB

OSS Libraries used

License

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