noflo-pgorm

0.0.21 • Public • Published

PostgreSQL ORM on top of noflo-pg
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This is an Object-Relational Mapping interface to noflo-pg. This ORM tries to be a thin layer on top of noflo-pg's raw access to a pgSQL server. It contains two usable components, one for Reading and another for Writeing. A basic workflow would be something like:

  1. Provide the URL to either the 'Read' or 'Write' component.
  2. Provide an alternative primary key column if it is not the column 'id'.
  3. It fetches table and column information from the server at initiation.
  4. You may then 'Read' or 'Write' from/to the database.

Feel free to contribute new components and graphs! I'll try to incorporate as soon as time allows.

Usage

There are two operatioins when it comes to interacting with the ORM: 'Read' and 'Write'. Both expect the same format when it comes to what is given and what is output. For the output, the following format is used:

BEGINGROUP: session-token
BEGINGROUP: type-name
DATA: record-as-JavaScript-object
... (more records)
ENDGROUP: 'users'
... (more records by type)
ENDGROUP: 'token'

type is synonymous as a table. An example:

BEGINGROUP: 'token'
BEGINGROUP: 'users'
DATA: { id: 1 }
DATA: { id: 2 }
ENDGROUP: 'users'
BEGINGROUP: 'things'
DATA: { id: 3 }
DATA: { id: 4 }
DATA: { id: 5 }
ENDGROUP: 'things'
ENDGROUP: 'token'

The input, or what the ORM expects to take, follows this format:

BEGINGROUP: session-token
BEGINGROUP: type-name
BEGINGROUP: additional-type-name
... (more additional types)
DATA: constraint-or-record-as-JavaScript-object
... (more records)
ENDGROUP: 'users'
... (more records by type)
ENDGROUP: 'token'

It is similar to how the output is formatted except that it differs a bit between 'Read' and 'Write'. Keep on reading for the different input format.

Reading from PostgreSQL

Reading is as simple as sending the target table name and constraints to the 'Read' component.

First set up a component with a server URL.

'tcp://default@localhost:5432/postgres' -> SERVER Read(pgorm/Read)

The 'IN' port accepts a series of packets. Each packet is a tuple as an array, in the form of [column_name, operator, value]. It is the equivalent to the SQL construct of column_name operator value, as in username = elephant. Note that the value does not need to be quoted as the ORM would sanitize it for you.

'username,=,elephant' -> IN Arrayify(adapters/TupleToArray)
Arrayify() OUT -> IN Read()

You must group this series of packets with an TOKEN, which would be used to group the output, since this is an asynchronous operation. Inside the TOKEN group, you must also group the packets with a number of groups representing the tables to fetch from.

'token' -> GROUP Token(Group)
'username,=,elephant' -> IN Arrayify(adapters/TupleToArray)
Arrayify() OUT -> IN Token() OUT -> IN Read()

You may optionally pass no packets but simply group(s) to fetch everything in the said tables.

'token' -> GROUP Token(Group)
'_' -> IN Empty(Kick) OUT -> IN Token() OUT -> IN Read()

A more complete example:

'token' -> GROUP Token(Group)
',' -> DELIMITER SplitTables(SplitStr)
'users,things' -> IN SplitTables() OUT -> GROUP Tables(Group)
'username,=,elephant' -> IN Arrayify(adapters/TupleToArray)
Arrayify() OUT -> IN Tables() OUT -> IN Token()
Token() OUT -> IN Read(pgorm/Read) OUT -> IN Rows(Output)

Read() receives:

BEGINGROUP: 'token'
BEGINGROUP: 'users'
BEGINGROUP: 'things'
DATA: 'username,=,elephant'
ENDGROUP: 'things'
ENDGROUP: 'users'
ENDGROUP: 'token'

The executed SQL should be something like:

SELECT users.* FROM users, things WHERE username = 'elephant';

while Rows() should receive something similar to:

BEGINGROUP: 'token'
BEGINGROUP: 'users'
DATA: {
    ...
    username: 'elephant'
    ...
  }
ENDGROUP: 'users'
ENDGROUP: 'token'

Options

You may specify the certain options when reading. The available options are, as in-ports:

  1. LIMIT: directly placed as LIMIT { number | ALL }
  2. OFFSET: directly placed as OFFSET number
  3. ORDERBY: directly placed as ORDER BY column1 [ASC | DESC] [, column2 [ASC | DESC] ...]

Value list

The tuple may also exceeds 3 elements, in which case the rest of the passed packets are also values, as in [column_name, operator, value1, value2, value3]. All the values are then compressed into an array and the resulting SQL would be an parenthesized list as specified in SQL syntax.

BEGINGROUP: 'token'
BEGINGROUP: 'users'
DATA: 'username,in,elephant,dog,cat'
ENDGROUP: 'users'
ENDGROUP: 'token'

would be turned into:

SELECT users.* FROM users WHERE username IN ('elephant', 'dog',
'cat');

Writing to PostgreSQL

Writing is handled by the 'Write' component, very similar to the 'Read' component except it fetches table and column information from the PostgreSQL server at initialization so that it can filter out invalid tables and columns when executing SQL.

First set up a component with a server URL.

'tcp://default@localhost:5432/postgres' -> SERVER Write(pgorm/Write)

The 'IN' port expects a series of packets, each of which is an object to be translated into SQL. It filters out all keys that do not have corresponding columns.

The packets, like Read(), must also be grouped by the table name:

BEGINGROUP: 'users'
DATA: { "id": 1, "name": "elephant" }
ENDGROUP: 'users'
BEGINGROUP: 'things'
DATA: { "id": 3, "type": "person" }
ENDGROUP: 'things'

Note on ORM's attempt to upsert

The above would write to the 'users' and the 'things' tables. The executed SQL would be something like:

BEGIN;
  SET TRANSACTION ISOLATION LEVEL SERIALIZABLE;

  UPDATE users SET id=&users_id_1, name=&users_name_1
    WHERE id = &users_id_1;
  INSERT INTO users (id, name)
    SELECT &users_id_1, &users_name_1
    WHERE NOT EXISTS (SELECT 1 FROM users WHERE id = &users_id_1);

  UPDATE things SET id=&things_id_3, type=&things_type_3
    WHERE id = &things_id_3;
  INSERT INTO things (id, type)
    SELECT &things_id_3, &things_type_3
    WHERE NOT EXISTS (SELECT 3 FROM things WHERE id = &things_id_3);
END;

It uses dirty upsert for PostgreSQL, stolen from bovine's answer on this StackOverflow question. This dirty solution is good enough for most cases unless you use autoincrement on the primary key and your transaction is large, or in any scenario where primary key collision upon row creation is frequent. It is recommended that you use UUID to avoid any problem. Upserting is a complicated problem so some compromises must be made.

The return values

'Write' returns all the records after they have been updated (or not) by the database server. The format is exactly like what Read returns. For instance:

BEGINGROUP: 'token'
BEGINGROUP: 'users'
DATA: {
    ...
    name: 'elephant'
    ...
  }
ENDGROUP: 'users'
BEGINGROUP: 'things'
DATA: {
    ...
    type: 'person'
    ...
  }
ENDGROUP: 'things'
ENDGROUP: 'token'

Output Filtering

Because the ORM outputs records as an array of records grouped by types (i.e. tables), it inserts a _type attribute to each record. If you would like to remove it, pass an empty string to the 'FILTER' port and all attributes starting with an underscore (i.e. _) will be removed for all records.

You may also pass in additional filters. Each packet is a filter that is a RegExp string and filters based on the record's attribute key. For instance, the following filters everything starting with an 'a' and everything ending with a 'z':

'^a' -> FILTER Read(pgorm/Read)
'z$' -> FILTER Read()
... -> IN Read() OUT -> ...

Automatic table/column existence check

The 'Write' component also automatically filter incoming queries for invalid tables and columns. This is possible as 'Write' fetches table/column information from the server on initialization. The downside, of course, is when the schema has changed on the PostgreSQL server the NoFlo network needs to be refreshed.

Another note when using 'Write' is to remember to pipe the 'READY' port to your initialization process that activates anything that would run a query against 'Write'. The component emits an empty connection to the 'READY' port when it has finished fetching table/column information.

'tcp://default@localhost:5432/postgres' -> SERVER Write(pgorm/Write)
Write() READY -> ...

Different key

The ORM puts a DISTINCT ON on the "primary" key to ensure uniqueness even though the primary key itself should of course be declared unique when schema is set up. This "primary" key is defaulted to 'id'. You may configure the key by sending a new key to to the 'KEY' port. This only needs to be done once at initialization.

This key is also used to order the rows with the ORDER BY clause. You may change the order-by key to something else by sending *key* ASC to the 'ORDERBY' port or change just the ordering by sending DESC to the 'ORDERBY' port.

'tcp://default@localhost:5432/postgres' -> SERVER Write(pgorm/Write)
'uuid' -> KEY Write()
'name DESC' -> ORDERBY Write()

Error handling

Errors from the PostgreSQL server are emitted to the 'ERROR' port. Attach a process to it to handle any server-side error.

'tcp://default@localhost:5432/postgres' -> SERVER Write(pgorm/Write)
Write() ERROR -> IN Error(Output)

Shutting down

You may shut down the connection to the PostgreSQL server by sending a null packet to the 'QUIT' port.

'tcp://default@localhost:5432/postgres' -> SERVER Write(pgorm/Write)
'_' -> IN Kick(Kick) OUT -> QUIT Write()

All connections in a single program are pooled for efficiency. Sending a null packet would kill all pgSQL connections. Pass the URL that was used to initialize the connection to 'QUIT' in order to kill just that one connection.

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