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README.md

pmql

ProcessMaker Query Language

Support for simple SQL-like expressions and converting to Laravel Eloquent. Exposes a Eloquent scope 'pmql' to pass in clauses.

Table of Contents

Simple Usage

$results = Record::where('id', '<', 500)->pmql('username = "foobar" AND age < 25')->get();

Operators

Comparison Operators

Operator Name
= Equal
!= Not Equal
< Less Than
> Greater Than
<= Less Than or Equal To
>= Greater Than or Equal To
LIKE Pattern Match

Logical Operators

Operator Name
AND Match both conditions
OR Match either condition

Case Sensitivity

Note that PMQL syntax is not case sensitive. However, queries are case sensitive. For example, if querying for a string, PMQL will return results only if the case matches your query exactly. This may be bypassed by utilizing the lower(field) syntax. Examples are provided below.

Casting

Fields can be cast to various data types using the cast(field as type) syntax. Currently supported types are text and number. Examples are provided below.

Dates

Strings entered in the format "YYYY-MM-DD" are interpreted as dates and can be used in comparative queries. Dates can be compared dynamically based on the current time utilizing the now keyword. Arithmetic operations can be performed on dates using the date (+ or -)number interval syntax. The interval can be either day, hour, minute, or second. Examples are provided below.

Syntax Examples

Sample Dataset

Let's say we are managing a roster for a basketball team.

id first_name last_name position dob experience starter
8 Liz Cambage center 1991-08-18 3 true
51 Sydney Colson guard 1989-08-06 5 false
5 Dearica Hamby forward 1993-11-06 4 false
21 Kayla McBride guard 1992-06-25 5 true
19 JiSu Park center 1998-12-06 1 false
10 Kelsey Plum guard 1994-08-24 2 true
11 Epiphanny Prince guard 1988-01-11 9 false
14 Sugar Rodgers guard 1989-12-08 6 false
4 Carolyn Swords center 1989-07-19 7 false
22 A'ja Wilson forward 1996-08-08 1 true
1 Tamera Young forward 1986-10-30 11 false
0 Jackie Young guard 1997-09-16 0 true

Basic Syntax

Find players with a specific last name.

Query

last_name = "Young"

Result

id first_name last_name position dob experience starter
1 Tamera Young forward 1986-10-30 11 false
0 Jackie Young guard 1997-09-16 0 true

And

Find players with a specific last name in a specific position.

Query

last_name = "Young" and position = "forward"

Result

id first_name last_name position dob experience starter
1 Tamera Young forward 1986-10-30 11 false

Or

Find players in two different positions.

Query

position = "center" or position = "forward"

Result

id first_name last_name position dob experience starter
8 Liz Cambage center 1991-08-18 3 true
5 Dearica Hamby forward 1993-11-06 4 false
19 JiSu Park center 1998-12-06 1 false
4 Carolyn Swords center 1989-07-19 7 false
22 A'ja Wilson forward 1996-08-08 1 true
1 Tamera Young forward 1986-10-30 11 false

Grouping

Find players matching grouped criteria:

Query

(position = "center" or position = "forward") and starter = "true"

Result

id first_name last_name position dob experience starter
8 Liz Cambage center 1991-08-18 3 true
22 A'ja Wilson forward 1996-08-08 1 true

Numeric Comparison

Find players based on years of experience.

Query

experience > 8

Result

id first_name last_name position dob experience starter
11 Epiphanny Prince guard 1988-01-11 9 false
1 Tamera Young forward 1986-10-30 11 false

Casting To Number

What if a field we want to compare mathematically is stored as a string instead of an integer? No problem. We can simply cast it as a number.

Let's say our dataset has changed to store the experience field as a string but we want to find all players with 2 years of experience or less.

Query

cast(experience as number) <= 2

Result

id first_name last_name position dob experience starter
19 JiSu Park center 1998-12-06 1 false
10 Kelsey Plum guard 1994-08-24 2 true
22 A'ja Wilson forward 1996-08-08 1 true
0 Jackie Young guard 1997-09-16 0 true

Date Comparison

Find players born before 1990.

Query

dob < "1990-01-01"

Result

id first_name last_name position dob experience starter
51 Sydney Colson guard 1989-08-06 5 false
11 Epiphanny Prince guard 1988-01-11 9 false
14 Sugar Rodgers guard 1989-12-08 6 false
4 Carolyn Swords center 1989-07-19 7 false
1 Tamera Young forward 1986-10-30 11 false

Dynamic Date Comparison

Find players under 25 as of right now. We utilize the now keyword and subtract 9,125 days (365 * 25 = 9,125).

Query

dob > now -9125 day

Result

id first_name last_name position dob experience starter
19 JiSu Park center 1998-12-06 1 false
22 A'ja Wilson forward 1996-08-08 1 true
0 Jackie Young guard 1997-09-16 0 true

Pattern Matching

We can use the LIKE operator to perform pattern matching with a field. % is a wildcard which matches zero, one, or more characters. _ is a wildcard which matches one character.

Start of String

Let's find all players whose last names begin with the letter P.

Query
last_name like "P%"
Result
id first_name last_name position dob experience starter
19 JiSu Park center 1998-12-06 1 false
10 Kelsey Plum guard 1994-08-24 2 true
11 Epiphanny Prince guard 1988-01-11 9 false

Exact Pattern

Let's find all players whose last names begin with P and have three letters after that.

Query
last_name like "P___"
Result
id first_name last_name position dob experience starter
19 JiSu Park center 1998-12-06 1 false
10 Kelsey Plum guard 1994-08-24 2 true

End of String

Let's find all players whose last names end in "son."

Query
last_name like "%son"
Result
id first_name last_name position dob experience starter
51 Sydney Colson guard 1989-08-06 5 false
22 A'ja Wilson forward 1996-08-08 1 true

String Contains

Let's find all players whose names contain "am."

Query
first_name like "%am%" or last_name like "%am%"
Result
id first_name last_name position dob experience starter
8 Liz Cambage center 1991-08-18 3 true
5 Dearica Hamby forward 1993-11-06 4 false
1 Tamera Young forward 1986-10-30 11 false

Ignore Case

Let's find all players whose names contain "de" regardless of capitalization.

Query
lower(first_name) like "%de%" or lower(last_name) like "%de%"
Result
id first_name last_name position dob experience starter
5 Dearica Hamby forward 1993-11-06 4 false
21 Kayla McBride guard 1992-06-25 5 true

Custom Callbacks

You can utilize custom callbacks in your pmql call to override behavior for a specific expression

$results = Record::where('id', '<', 500)->pmql('username = "FOOBAR" AND age < 25', function($expression) {
    // This example will ensure checking for lowercase usernames as thats how it stored in our database
    if($expression->field->field() == 'username') {
        // If you want to modify the query, you need to return an anonymous function that will add your additional criteria
        return function($query) use($expression) {
                $query->where(DB::raw('LOWER(username)', $expression->operator, strtolower($expression->value->value()));
        }
    }
    // Let default behavior win for non username fields
    return false;
})->get();
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