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Describing your columns
Clear offers a column macro:
column method_name : Type, [primary: bool], [converter: "any_string"],
[column_name: "any_string"], [presence: bool]
The arguments action is defined as below:
Argument name | Description |
primary | Whether this column should be setup as primary key or not.
Only one primary key per model is permitted.
Primary key are necessary for handling relations and some features (e.g default sorting) Default: false |
converter | Use a specific data converter between Clear and PostgreSQL to handle this column. <b></b> Default: Will lookup for the converter related to the type of the column; primitives and commons type are already mapped, while complex type and structures must be mapped manually.
See the section about converters for more information. |
column_name | In the case the column name is different from the field in Clear (e.g. the name is a reserved keyword in Crystal Lang), you might want to change it here. Default: Same name between the column in PostgreSQL and the property in your model |
presence | Enable of disable the presence check done on validation and insertion of the model in the database. When your column has a default value setup by PostgreSQL (like a serial type), you want to setup presence to false .Default: true unless the type is nilable . |
Clear use a column assignation system which provide safeguard against
NilException
while keeping possibility to fetch semi-fetched model. For example, you may want to fetch only the first_name
and last_name
of a User
through the database:User.query.select("first_name, last_name").each do |usr|
puts "User: #{usr.first_name} #{usr.last_name}"
end
But what if by mistake your code call a non fetched field ?
User.query.select("first_name, last_name").each do |usr|
# This will throw an exception !
puts "User: #{usr.id}"
end
Name | Description | |
xxx_column.changed? | Return true | false whether the column as changed since the last database fetch |
xxx_column.has_db_default? | Return true if the presence check is set to false | |
xxx_column.name | Return the name of the field in the database. | |
xxx_column.old_value | In case of change, return the previous value, before the change | |
xxx_column.revert | Return the column to it's initial state; changed flag is set to false and value become old_value | |
xxx_column.clear | The column become in non-present state (e.g. wasn't fetched) | |
xxx_column.defined? | Return true if the column has a value, false otherwise | |
xxx_column.value | Return the column value. Raise an error if the column is in a non-present state. Equivalent to self.xxx | |
xxx_column.value(default) | Return the current column value, OR default if the column is in a non-present state | |
Crystal | PostgreSQL |
String | text |
UUID | uuid |
Bool | boolean |
Int8 | byte |
Int16 | short |
Int32 | int , serial |
Int64 | bigint , bigserial |
Array(Type) | type[] (note: type can be of any primitives above) |
BigDecimal | numeric |
JSON::Any | jsonb |
Time | timestamp without time zone |
BigDecimal
(in .cr
) is mapped to Numeric
(in pg
) in migration columns (i.e. declaring column data type as "bigdecimal"
would be equal to the column being declared with type "numeric"
, if you wish to specify precision, and scale, please use "numeric(precision, scale)"
or "numeric(precision)"
(with scale defaulting to 0), instead of "bigdecimal"
)Please take note that PostgreSQL will throw a
numeric field overflow
(and in Clear: Clear::SQl::Error
) if you INSERT
into the database a BigDecimal/ numeric value with the integer part (to the left of the radix point) of a size that is bigger than the precision that is specified in the numeric type that you declare. This can be seen from the following example taken from specs: class Data
include Clear::Model
column id : Int32, primary: true, presence: false
column num3 : BigDecimal?
column num4 : BigDecimal?
end
class ModelSpecMigration123
include Clear::Migration
def change(dir)
create_table(:model_spec_data) do |t|
t.column "num3", "numeric(9)"
t.column "num4", "numeric(8)"
end
end
end
data = Data.new
big_number = BigDecimal.new(BigInt.new("-1029387192083710928371092837019283701982370918237".to_big_i), 40) # this is the same as "-102938719.2083710928371092837019283701982370918237"
The following case would not throw an error
data.num3 = big_number
data.save!
However this case would throw an error
data.num4 = big_number
data.save!
Last modified 3yr ago