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gaum

A story about Bare Minimum Struct Relational Mapping, by Horacio Duran

This intends to provide a bare minimum ORM-Like-but-not-quite interface to work with postgres.

The original intent behind this project is to allow us to replace gorm in a project at work because it is falling a bit short.

This library is, as it's name indicates, a bare minimum. It is not a "drop in" replacement for gorm because I wanted to change a bit the behavior.

How to use it, there are two components that can be used separately:

  • The DB connector: Which allows interaction with the underlying DB, it adds almost nothing to the underlying API but some minor level of magic when fetching the data and a set of helpers to convert from the more practical ? argument placeholders to the numbered positionals required by the DB $1, $2,.... with a few convenient expansions like making (?) into ($1...n) based on the passed arguments (with limitations).
  • The Chain: Provides a set of convenience functions and methods that allows chaining and combining to produce a struct that can render itself into a consistent SQL query (the promise is that the same object renders itself into the same SQL object each time).

DB

Note all the examples in this doc are using the postgres driver because it is the itch I am scratching, along with it we provide a standard postgres driver, which can be used if you hit a limitation in the other one (which we did), I do not intend to write other drivers and most of the code will be strongly opinionated towards postgres, this said, if someone else feels like writing different drivers I'll gladly accept PRs

As stated above, the DB component provides a set of convenience functions that allow querying and executing statements in the db and retrieving the results if any with slightlty less friction than the bare bones functions.

To first open a connection we will need an instance of connection.DatabaseHandler and invoke the Open method.

DatabaseHandler.Open (postgrespq flavor)

Open creates a db connection pool and returns a connection.DB object containing it. By default it uses a pool, once again, because I have no use for single connection.

// imports used
// "github.com/ShiftLeftSecurity/gaum/db/connection"
// "github.com/ShiftLeftSecurity/gaum/db/postgrespq"
// "github.com/ShiftLeftSecurity/gaum/db/logging"
 
var connector connection.DatabaseHandler

// This uses Postgres PQ driver, which is the standard sql driver for postgres, you can use
// pgx one for a bit of efficiency increase in some aspects but outcome is not always guaranteed
// as we use PQ for real life testing (automated tests use both)
connector = postgrespq.Connector{
	ConnectionString: "a connection string",
}

// Wrappers are provider for go standard logging and testging t.Log but build more is trivial
// and can be pretty much cargo culted from the existing one.
logger := logging.NewGoLogger(standardgologger)

maxConnLifetime := 1 * time.Minute

dbConnection, err := gaumConnector.Open(&connection.Information{
	Logger:          logger,
	// For production `Error` is the recommended logging level as the driver and the underlying
	// library are quite chatty.
	LogLevel:        connection.Error,
	// You can omit this if you don't have special db requirements, most uses should be ok
	// with default but we provide just in case.
	// Side note: this only works with PQ driver.
	ConnMaxLifetime: &maxConnLifetime,
	// This is possible but rarely necessary, I just added the example in case you hit one of
	// the corner cases which require it.
	CustomDial: func(network, addr string) (net.Conn, error) {
		d := &net.Dialer{
			KeepAlive: time.Minute,
		}
		return d.Dial(network, addr)
	},
	// Most of these can be provided as the ConnectionString when instantiating the connector
	Host:             "127.0.0.1",
	Port:             5432,
	Database:         "postgres",
	User:             "postgres",
	Password:         "mysecretpassword",
	MaxConnPoolConns: 10,
})

if err != nil {
	// do something
}
	

The connection string is enough to open a connection but if Open receives a non nil parameter the overlapping parameters will be taken from the connection.Information in the Open invocation.

The Information struct contains most of the possible data one can use for a connection, strongly biased to postgres.

A note about the logger object passed to Open, its an instance of logging.Logger which is basically an Interface for logging that I consider sane enough and that I in turn addapt to what pgx takes.

For ease of use, as stated in this example a wrapper for the standard go log is provided. For testing purposes, another wrapper is provided that wraps on the *testing.T object to facilitate testing info.

Some of the items in DB

DB.Clone

DB.Clone returns a deep copy of the db.

EscapeArgs

EscapeArgs is in the wrong place in the code, but will do for now. This is something to be known before any querying function. To avoid the hassle of having to put $<argnumber> in each query argument placeholder, the convenience gorm provides was taken and it's possible to use ? as a placeholder. To allow for our lazy side to take over, we need to invoke EscapeArgs on the query and args to both check for number of arg consistency and properly escape the placeholders before calling any of the queries, now for all of these functions, there is also another with the same name provided with an E prepend that invokes EscapeArgs for you.

A more useful and feature complete of EscapeArgs can be found in chain.MarksToPlaceholders that will not only convert ? signs into positional arguments that the db accepts but also unwrap slice arguments where appropriate and returns the expanded list of arguments.

DB.EQueryIter

( See EscapeArgs And QueryIter )

EQueryIter will execute the query and return a closure that holds the cursor. Calling the returned closure produces advancement of the cursor, one can pass the pointer to a struct that one wants populated. The rules for populating a struct are made from the passed list of fields (containing the column names to be fetched in the query, beware no consistency is checked until query time and by then all will go boom or you will be missing data) there will be snake to camel case conversion and matching that to the struct member name (or the contents of gaum:"field_name:something"). If no fields are specified we will make a query to the db to ask for a description of the fields returned, try not to let that happen as it requires extra roundtrips and adds uncertainty.

Ideally this and all other queries will be used through chain that will take care of the ugly parts.

Note: this WILL hold a connection from the pool until you either invoke close() function returned in each iteration or deplete results, a timer option is planned but don't hold your breath.

DB.EQuery

(See EscapeArgs And Query )

EQuery will return a closure, similar to QueryIter but it will take a slice pointer (sorry, reflection) only since it will fetch all the results in one call and populate the slice. The rest of the behavior is the same.

Note: this WILL hold a connection from the pool until you either invoke close() function returned or run the closure, a timer option is planned but don't hold your breath.

DB.EQueryPrimitive

( See EscapeArgs And QueryPrimitive )

QueryPrimitive will return a closure, similar to Query but it will take a pointer to slice of primitives, for this the SELECT statement must return only one column or the query will fail before even executing. The rest of the behavior is the same.

Note: this WILL hold a connection from the pool until you either invoke close() function returned or run the closure, a timer option is planned but don't hold your breath.

DB.ERaw

( See EscapeArgs And Raw )

Raw will run the passed query with the passed arguments and try to fetch the resulting row into the passed pointer receivers, this will do for one row only and you have to be careful to pass enough (and properly typed, see sql.Scanner ) receivers for the fields you are querying and no more.

DB.EExec

( See EscapeArgs And Exec )

Exec is intended for queries that do not return results such as... well anything that is not a SELECT (and sometimes SELECT if you do not expect results, such as when invoking a stored procedure) you just pass the query and the arguments.

Transactions

Transactions are fairly simple. DB offers BeginTransaction that returns a disposable DB object whose life extends only to the boundary of the transaction and will end when you either RollbackTransaction or CommitTransaction. These things are idempotent so if you call Begin on a transaction nothing bad happens and equally if you call Rollback or Commit on a non transaction. To know if your db is a transaction use IsTransaction

DB.BulkInsert

This has not yet been tested, it's intention is to use the COPY statement.

Chain

The Chain (poor decision on my part used the very long ExpressionChain name) is the main SQL building element, it is an object that contains enough information to render itself into a SQL query and invoke the database with it optionally. The object itself has a plethora of methods that mutate its attributes with the different parts of a query and allow easy manipulation, unlike working with just string concatenation and also providing some of the safety and syntax of go.

To use a Chain you must create one with chain.New if you want it to be able to also invoke the DB or chain.NewNoDB if you don't need (such as to formulate sub-queries, CTEs, Where Groups and others that we will see ahead)

Crafting the SQL is achieved by just calling the corresponding methods that abstract the SQL we want added, the changes mutate the Chain object itself, most of them return nevertheless a pointer to it's own so it is more natural to chain commands (ie: chain.New(db).Select("field1" ,"field2").From("a_table").AndWhere("a_condition = ?", 1)).

The methods that generate the SQL verbs such as SELECT, INSERT, UPDATE, DELETE and any other exclusive SQL keywords will set what we call the main operation and replace each other when invoked unlike modificators such as WHERE, JOIN, etc.

Note: Currently FROM which is manipulated by .From or .Table methods will also replace existing ones instead of appending, this might change in the near future but plans for it are not yet clear.

For fine details on the chain object you can check the main reference

Composing Helpers

Chain Helpers

Before the actual statements, let's see some of the helpers available to ease the crafting of SQL using as much go as possible (working under the assumption that the more freeform strings we use, the more possibilities for syntax errors uncaught until runtime will slip). Many of these do simple string concatenation or formatted printing but when the query grows to a decent lenght they are much less error prone and definitely much easier to read.

TablePrefix

Table prefix returns a function that when invoked with a string as parameter returns the passed in string namespaced with the construcing table name. (See also TablePrefixes which provides a more complex, template based version of this built into ExpressionChain)

tn := chain.TablePrefix("TableName")
tn("column") // -> "TableName.column

SimpleFunction

Simple Function allows to craft a simple function call that takes a column or constant as parameter, ideally you will use to construct totalization functions, for convenience we provide some of the basic ones (check to see if he one you need is there already, we add more when we need) at the time of writing this we had:

chain.AVG("colum") // -> AVG(column)

MyCustomFunction := func(column string) string { 
	return chain.SimpleFunction("MyCustomFunction", column)
}
MyCustomFunction("acolumn") // -> MyCustomFunction(acolumn)

AnotherFN := func(columns ...string) string {
	return chain.SimpleFunction("AnotherFn", strings.Join(columns, ","))
}
AnotherFN("one", "two", "three") // -> AnotherFn(one, two, three)

ComplexFunction

Complex Function returns, much like Simple function, a struct that allows chain calling of arguments to construct a function that takes both static (columns, constants, etc) parameters and external ones (which will be passed as positional to the query in the form func($1, $2..., $n) with separated args for safety)

c := ComplexFunction("afn")
something := 1
c.Static("column").Static("column2").Parametric(something)
c.Fn() // -> afn(column, column2, ?) // []interface{}{1}

// For FnSelect, see `chain.SelectWithArgs`
c.FnSelect() // -> SelectArgument { Field: "afn(column, column2, ?)", Args: []interface{}{1} }

ColumnGroup

Column Group groups columns in parenthesis for cases like:

WHERE (col1, col2, col3) IN ((1,2,3), (4,5,6))
cg := chain.ColumnGroup("col1", "col2", "col3") // -> (col1, col2, col3)
// this can be used in places like
chain.New().
	Select("field").
	From("table").
	AndWhere(chain.In(gc), args)

AndConditions

And Conditions concatenates Several conditions using AND

chain.AndConditions("a = 1", "b = 2") // -> a = 1 AND b = 2

OrConditions

Or Conditions concatenates Several conditions using OR

chain.OrConditions("a = 1", "b = 2") // -> a = 1 OR b = 2

CompareExpressions

Compare Expressions makes a comparision between two SQL values (columns, constants, etc) using one of the predefined operators (you may define your own too)

chain.CompareExpressions(chain.Eq, "column1", "column2") // -> column1 = column2

The main goal of this is to craft expression comparision between columns or constants instead of ones that use external arguments.

This particular helper is useful when crafting group comparisions for WHERE or JOIN

Example

t1 := chain.TablePrefix("Table1")
t2 := chain.TablePrefix("Table2")

joinConditions := chain.AndConditions(
	chain.CompareExpressions(
		chain.Eq,
		chain.ColumnGroup(t1("col1"),t1("col2"),t1("col3")),
		chain.ColumnGroup(t2("col1"),t2("col2"),t2("col3")),
	),
	chain.CompareExpressions(
		chain.Gt,
		t1("gtColumn"),
		t2("gtColumn"),
	)
)

When rendered joinConditions in this case is:

(Table1.col1, Table1.col2, Table1.col3) = (Table2.col1, Table2.col2, Table2.col3) AND Table1.gtColumn = Table2.gtColumn

As

As returns the string with an added SQL alias

chain.As("column", "analias") // -> column AS analias

Equals, NotEquals, GreaterThan, GreaterOrEqualThan, LesserThan, LesserOrEqualThan

These are all simple comparision operators and are here to prevent typos mostly.

chain.Equals("column") // -> column = ?
chain.NotEquals("column") // -> column != ?
chain.GreaterThan("column") // -> column > ?
chain.GreaterOrEqualThan("column") // -> column >=
chain.LesserThan("column") // -> column <
chain.LesserOrEqualThan("column") // ->  column <=

In

In creates the IN (....) construction.

chain.In("column", 1,2,3) // column IN (?) // []interface{}{1,2,3}

InSlice

In creates the IN (....) construction but helps if you already have the items in slice form so you do not have to unpack them

chain.InSlice("column", []int64{1,2,3}) // column IN (?) // interface{} = []int64{1,2,3}

Null, NotNull

Null and Not Null respectively craft the x IS NULL and x IS NOT NULL constructions.

chain.Null("column") // -> column IS NULL
chain.NotNull("column") // -> column IS NOT NULL

SetToCurrentTimestamp

Set to current timestamp creates a set construction that uses the pg current timestamp value.

chain.SetToCurrentTimestamp("column") // -> column = CURRENT_TIMESTAMP

NillableString, NillableInt64

These two are useful when fetching results, not when composing the query. Nillable* converts safely from pointer to it's concrete type for the two most common types, when retrieving nillable columns from db is best that the recipient be a "pointer to" instead of a concrete type otherwise encountering NULL values to return would result in either Zero value (for string and time.Time) of failure to assign in other cases. To avoid the typicall issues of nil pointer dereference these methods were added. In case of nil these will return the zero value of the type, If you need other types you will have to copy from these:

var s *string
var as = "astring"
chain.NillableString(s) // ""
s = &as
chain.NillableString(s) // "astring"

var i *int64
var ai = "42"
chain.NillableInt64(i) // 0
i = &ai
chain.NillableString(ai) // 42

Composing Main Operations

Before Beginning

Any invocation to the methods of ExpressionChain requires you to have an instance of it, which can be obtained in two ways.

  • If you require this expression chain to conclude with a call to the DB you might want to use the New constructor that receives a connection.DB

     c, err := postgrespq.Connector{
     	ConnectionString: "a valid connection string",
     }.Open()
    
     // [snip] error checking
    
     q := chain.New(c)
  • Constructing an ExpressionChain unbound to a db: If your purpose is to just render the query or use it as a subquery you can use instead the constructor NewNoDB

     q := NewNoDB()

Bear in mind that invoking the methods that fetch data from the DB will panic.

All chain methods mutate the query in place, the only reason a pointer is returned is for ease composing queries.

Clone

At any point in the use of the query you can invoque q.Clone() to obtain a deep copy of it (safe the connection.DB which is copied as is). This is useful in cases where a query departs from the same root but at some point you want to fork it to create two similar queries.

Select

Select allows you to craft a select of multiple columns or expressions, this method will help you craft a query with any valid syntax that SELECT accepts excepting for expressions requiring an external positional parameter, for that use SelectWithArguments

tp := chain.TablePrefix("ATable")
q.Select(
	"one", 
	"two", 
	"three AS four",
	chain.As("four", "five"),
	chain.As(tp("five"), "six"),
	AVG("something"))

will produce:

SELECT one, two, three AS four, four AS five, ATable.five as six, AVG(something)

SelectWithArguments

Select With Arguments acts the same as ExpressionChain.Select but allows for external arguments, since its produced code is a bit more complex, instead of receiving a variadic list of arguments, it receives a variadic list of chain.SelectArgument

q.Select(
	chain.SelectArgument{Field:"one"},
	chain.SelectArgument{Field: chain.As("two", "something")},
	chain.ComplexFunction("afn").Static("oneparam").Parametric(3).FnSelect(),
)

will produce:

SELECT one, two AS something, afn(oneparam, ?)
-- And the int 3 will be passed to the final render/call to db

Note that select will accept either a list of strings that will be concatenated with , or one string containing the whole expression in free form.

Update

This version of UPDATE will take a string with the contents of the SET portion of an update SQL query, there is a more structured form that will be described next

chain.Update("field1 = ?, field3 = ?", "value2", 9).Table("something").Where("id = ?", 1)

will produce:

UPDATE something SET (field1 = $1, field3 = $2) WHERE id = $3

UpdateMap

This version of UPDATE will take a map of string to interface{} to allow a more structured code when crafting an update.

updateArgs := map[string]interface{}{
	"field1": "value2",
	"field2": 9,
}
chain.UpdateMap(updateArgs).Table("something").AndWhere("id = ?", 1)

will produce:

UPDATE something SET (field1 = $1, field3 = $2) WHERE id = $3

Delete

chain.Delete().Table("something").Where("arg1=? AND arg2>?", 1,4)

will produce:

DELETE FROM something WHERE arg1 = $1 AND arg2>$2

Insert

q.Insert(map[string]interface{}{
	"field1": "value1", 
	"field2": 2, 
	"field3": "blah"}).
	Table("something")

will produce:

INSERT INTO something (field1, field2, field3) VALUES ($1, $2, $3)

And Arguments

[]interface{}{"value1", 2, "blah"}

InsertMulti

This variation of insert allows to make inserts of multiple rows.

q.InsertMulti(map[string][]interface{}{
	"field1": []interface{}{"value1", "value1.1"}, 
	"field2": []interface{}{2, 22}, 
	"field3": []interface{}{"blah", "blah2"}}).
	Table("something")

will produce:

INSERT INTO convenient_table(field1, field2, field3) VALUES ($1, $2, $3), ($4, $5, $6)

And Arguments

[]interface{}{"value1", 2, "blah", "value1.1", 22, "blah2"}

Conflict

The Conflict method allows a variety of ON CONFLICT SQL expressions to be generated, among the options (please see doc for exhaustive detail) you can find DO NOTHING, SET and others enough to make upserts.

chain.Insert(map[string]interface{}{"field1": "value1", "field2": 2, "field3": "blah"}).Table("something").
Conflict(
	chain.Constraint("therecanbeonlyone"), 
	chain.ConflictActionNothing)

will produce:

INSERT INTO something (field1, field2, field3) VALUES ($1, $2, $3) ON CONFLICT ON CONSTRAINT (therecanbeonlyone) DO NOTHING

Constraint to a field

chain.Insert(map[string]interface{}{"field1": "value1", "field2": 2, "field3": "blah"}).Table("something").Conflict("id", chain.ConflictActionNothing)

will produce:

INSERT INTO something (field1, field2, field3) VALUES ($1, $2, $3) ON CONFLICT (id) DO NOTHING

Table, From

chain.Select("one", "two", "three as four").Table("something")
// or
chain.Select("one", "two", "three as four").From("something")

will produce:

SELECT one, two, three FROM something

Composing Query modificators

WHERE AndWhere, OrWhere

Using And

q.Select("one", "two", chain.As("three","four")).From("something").
AndWhere(chain.Equals("arg1", 1)).
AndWhere(chain.GreaterThan("arg2", 4)).
AndWhere(chain.Equals("arg4", 3))

will produce :

SELECT one, two, three FROM something WHERE arg1=$1 AND arg2>$2 AND arg4 = $3

Using Or

q.Select("one", "two", "three as four").From("something").AndWhere("arg1=?", 1).AndWhere("arg2>?", 4).AndWhere("arg4 = ?", 3).OrWhere("other_condition = ?", 1)

will produce :

SELECT one, two, three FROM something WHERE arg1=$1 AND arg2>$2 AND arg4 = $3 OR other_condition = $4

Bear in mind when this is rendered, the first condition rendered are always the AND ones, the first of course will not have effect since the operator refers to the prepend operation, so q.AndWhere("1=1").OrWhere("2=2") will be equivalent to q.OrWhere("2=2").AndWhere("1=1") and to q.OrWhere("1=1").OrWhere("2=2") but not to q.OrWhere("2=2").OrWhere("1=1") in general the order and operator dictated by the common sense is the righ one.

Using Groups (AndWhereGroup and OrWhereGroup)

q.Select("one", "two", "three as four").
	From("something").
	AndWhere(chain.Equals("arg1"), 1).
	AndWhere(chain.GreaterThan("arg2"), 4).
	AndWhere(chain.Equals("arg4"), 3).
	OrWhereGroup(
		NewNoDB().AndWhere("inner == ?", 1).AndWhere("inner2 > ?", 2))

will produce :

SELECT one, two, three FROM something WHERE arg1=$1 AND arg2>$2 AND arg4 = $3 OR (inner == $4 AND inner2 == $5)

And Arguments

[]interface{}{1,4,3,1,2}

Join, InnerJoin, FullJoin, RightJoin, LeftJoin

chain.Select("one, two, three as four, other.five").From("something").Join("other", "field = ?", "fieldvalue").Where("arg1=? AND arg2>?", 1,4)

will produce:

SELECT one, two, three as four, other.five FROM something JOIN other ON field = $1 WHERE arg1=$2 AND arg2>$3).Where("arg1=? AND arg2>?", 1,4)

Union

There are two ways to make an UNION:

Union

c := New(db).Select("*").From("a").AndWhere("a.field = ?", 1)
c.Union("SELECT * FROM b WHERE b.field = ?", 2)

will produce

SELECT * FROM a WHERE a.field = $1
UNION
SELECT * FROM b WHERE b.field = $2

and arguments

[]interface{}{1, 2}

AddUnionFromChain

c := New(db).Select("*").From("a").AndWhere("a.field = ?", 1)
d := New(db).Select("*").From("b").AndWhere("b.field = ?", 2)
c.AddUnionFromChain(d)

will produce

SELECT * FROM a WHERE a.field = $1
UNION
SELECT * FROM b WHERE b.field = $2

and arguments

[]interface{}{1, 2}

CTEs

There is some limited support for CTEs

With

"With" will render CTEs in the order they were added (to ease testing and preserve inter-dependency)

Note: Unions only support CTEs if they are added to the receiving function.

cte := NewNoDB().Select("*").From("some_table_in_cte")
New(db).Select("field1", "field2", "field3").
	With("a_cte", cte).
	From("a_cte").
	AndWhere("field1 > ?", 1).
	AndWhere("field2 = ?", 2).
	AndWhere("field3 > ?", "astring")

will produce

WITH a_cte AS (SELECT * FROM some_table_in_cte) 
SELECT field1, field2, field3 
FROM a_cte 
WHERE field1 > $1 AND field2 = $2 AND field3 > $3

and arguments

[]interface{}{1, 2, "astring"}

TablePrefixes

Since crafting a query using a lot of invocations of TablePrefix functions it might be easier to use the version of this feature built into chain (this is not very efficient as it compiles and executes a template per modificator invocated (Select, Insert, AndWhere, etc)

Note: The prefixes should be set before calling any modificator as they are rendered upon invocation and not at final render time to avoid large memory allocations in large queries.

c := New(db)
c.TablePrefixes().Add("t1", "really_long_alias")
c.TablePrefixes().Add("t2", "other_really_long_aliasalias")
c.Select("{.t1}.field1, {.t1}.field2, {.t2}.field1").From("tablename AS really_long_alias").Join("othertable AS other_really_long_aliasalias", "{.t1}.field1 = {.t2}.fieldx")

will produce

SELECT really_long_alias.field1, really_long_alias.field2, other_really_long_aliasalias.field1
FROM tablename AS really_long_alias.field1
JOIN othertable AS other_really_long_aliasalias ON 
really_long_alias.field1 = other_really_long_aliasalias

The replacement will not be run on arguments to reduce the surface for pottential injections.

TablePrefixes

Rendering

There are two forms of rendering, both will return the query string and a slice of the args:

Render

Returns the query string with the ? appearances replaced by the positional argument ($1, $2.. etc)

RenderRaw

Returns the query and args but without replacement, ideal for subqueries or for the future implementation of Constraint or just for debugging.

Running

For running all the same functions that are available on DB are here but you don't need to pass on the query components, only the receivers, if any:

All of these return a fetch function that, when invoked with the receiver (that must always be a pointer to the desired type, even for slices) will populate it or fail, notice that this separation allows for better detection of errors as you will be able to check error output for query and for data fetch (ie, syntax error vs no rows)

As an additional convenience function there is Fetch and FetchPrimitives that combine both the query and invocation of fetch for Query and QueryPrimitives respectively.

GroupChain (untested)

Therefore Undocumented, but ideally it is to make groups of queries in one go.