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version](https://badge.fury.io/js/noflo-pgorm.png)](http://badge.fury.io/js/noflo-pgorm) [![Stories in Ready](https://badge.waffle.io/kenhkan/noflo-pgorm.png)](http://waffle.io/kenhkan/noflo-pgorm)\n\nThis is an Object-Relational Mapping interface to\n[noflo-pg](https://github.com/kenhkan/noflo-pg). This ORM tries to be a\nthin layer on top of noflo-pg's raw access to a pgSQL server. It\ncontains two usable components, one for `Read`ing and another for\n`Write`ing. A basic workflow would be something like:\n\n  1. Provide the URL to either the 'Read' or 'Write' component.\n  2. Provide an alternative primary key column if it is not the column\n     'id'.\n  3. It fetches table and column information from the server at\n     initiation.\n  4. You may then 'Read' or 'Write' from/to the database.\n\nFeel free to contribute new components and graphs! I'll try to\nincorporate as soon as time allows.\n\n\n## Usage\n\nThere are two operatioins when it comes to interacting with the ORM:\n'Read' and 'Write'. Both expect the same format when it comes to what is\ngiven and what is output. For the output, the following format is used:\n\n    BEGINGROUP: session-token\n    BEGINGROUP: type-name\n    DATA: record-as-JavaScript-object\n    ... (more records)\n    ENDGROUP: 'users'\n    ... (more records by type)\n    ENDGROUP: 'token'\n\n`type` is synonymous as a table. An example:\n\n    BEGINGROUP: 'token'\n    BEGINGROUP: 'users'\n    DATA: { id: 1 }\n    DATA: { id: 2 }\n    ENDGROUP: 'users'\n    BEGINGROUP: 'things'\n    DATA: { id: 3 }\n    DATA: { id: 4 }\n    DATA: { id: 5 }\n    ENDGROUP: 'things'\n    ENDGROUP: 'token'\n\nThe input, or what the ORM expects to take, follows this format:\n\n    BEGINGROUP: session-token\n    BEGINGROUP: type-name\n    BEGINGROUP: additional-type-name\n    ... (more additional types)\n    DATA: constraint-or-record-as-JavaScript-object\n    ... (more records)\n    ENDGROUP: 'users'\n    ... (more records by type)\n    ENDGROUP: 'token'\n\nIt is similar to how the output is formatted except that it differs a\nbit between 'Read' and 'Write'. Keep on reading for the different input\nformat.\n\n\n### Reading from PostgreSQL ###\n\nReading is as simple as sending the target table name and constraints to\nthe 'Read' component.\n\nFirst set up a component with a server URL.\n\n    'tcp://default@localhost:5432/postgres' -> SERVER Read(pgorm/Read)\n\nThe 'IN' port accepts a series of packets. Each packet is a tuple as an\narray, in the form of `[column_name, operator, value]`. It is the\nequivalent to the SQL construct of `column_name operator value`, as in\n`username = elephant`. Note that the value does not need to be quoted as\nthe ORM would sanitize it for you.\n\n    'username,=,elephant' -> IN Arrayify(adapters/TupleToArray)\n    Arrayify() OUT -> IN Read()\n\nYou must group this series of packets with an TOKEN, which would be used\nto group the output, since this is an asynchronous operation. Inside the\nTOKEN group, you must also group the packets with a number of groups\nrepresenting the tables to fetch from.\n\n    'token' -> GROUP Token(Group)\n    'username,=,elephant' -> IN Arrayify(adapters/TupleToArray)\n    Arrayify() OUT -> IN Token() OUT -> IN Read()\n\nYou may optionally pass no packets but simply group(s) to fetch\neverything in the said tables.\n\n    'token' -> GROUP Token(Group)\n    '_' -> IN Empty(Kick) OUT -> IN Token() OUT -> IN Read()\n\nA more complete example:\n\n    'token' -> GROUP Token(Group)\n    ',' -> DELIMITER SplitTables(SplitStr)\n    'users,things' -> IN SplitTables() OUT -> GROUP Tables(Group)\n    'username,=,elephant' -> IN Arrayify(adapters/TupleToArray)\n    Arrayify() OUT -> IN Tables() OUT -> IN Token()\n    Token() OUT -> IN Read(pgorm/Read) OUT -> IN Rows(Output)\n\n`Read()` receives:\n\n    BEGINGROUP: 'token'\n    BEGINGROUP: 'users'\n    BEGINGROUP: 'things'\n    DATA: 'username,=,elephant'\n    ENDGROUP: 'things'\n    ENDGROUP: 'users'\n    ENDGROUP: 'token'\n\nThe executed SQL should be something like:\n\n    SELECT users.* FROM users, things WHERE username = 'elephant';\n\nwhile `Rows()` should receive something similar to:\n\n    BEGINGROUP: 'token'\n    BEGINGROUP: 'users'\n    DATA: {\n        ...\n        username: 'elephant'\n        ...\n      }\n    ENDGROUP: 'users'\n    ENDGROUP: 'token'\n\n#### Options\n\nYou may specify the certain options when reading. The available options\nare, as in-ports:\n\n  1. LIMIT: directly placed as `LIMIT { number | ALL }`\n  2. OFFSET: directly placed as `OFFSET number`\n  3. ORDERBY: directly placed as\n     `ORDER BY column1 [ASC | DESC] [, column2 [ASC | DESC] ...]`\n\n#### Value list\n\nThe tuple may also exceeds 3 elements, in which case the rest of the\npassed packets are also values, as in `[column_name, operator,\nvalue1, value2, value3]`. All the values are then compressed into an\narray and the resulting SQL would be an parenthesized list as specified\nin SQL syntax.\n\n    BEGINGROUP: 'token'\n    BEGINGROUP: 'users'\n    DATA: 'username,in,elephant,dog,cat'\n    ENDGROUP: 'users'\n    ENDGROUP: 'token'\n\nwould be turned into:\n\n    SELECT users.* FROM users WHERE username IN ('elephant', 'dog',\n    'cat');\n\n\n### Writing to PostgreSQL ###\n\nWriting is handled by the 'Write' component, very similar to the 'Read'\ncomponent except it fetches table and column information from the\nPostgreSQL server at initialization so that it can filter out invalid\ntables and columns when executing SQL.\n\nFirst set up a component with a server URL.\n\n    'tcp://default@localhost:5432/postgres' -> SERVER Write(pgorm/Write)\n\nThe 'IN' port expects a series of packets, each of which is an object to\nbe translated into SQL. It filters out all keys that do not have\ncorresponding columns.\n\nThe packets, like `Read()`, must also be grouped by the table name:\n\n    BEGINGROUP: 'users'\n    DATA: { \"id\": 1, \"name\": \"elephant\" }\n    ENDGROUP: 'users'\n    BEGINGROUP: 'things'\n    DATA: { \"id\": 3, \"type\": \"person\" }\n    ENDGROUP: 'things'\n\n#### Note on ORM's attempt to upsert\n\nThe above would write to the 'users' and the 'things' tables. The\nexecuted SQL would be something like:\n\n    BEGIN;\n      SET TRANSACTION ISOLATION LEVEL SERIALIZABLE;\n\n      UPDATE users SET id=&users_id_1, name=&users_name_1\n        WHERE id = &users_id_1;\n      INSERT INTO users (id, name)\n        SELECT &users_id_1, &users_name_1\n        WHERE NOT EXISTS (SELECT 1 FROM users WHERE id = &users_id_1);\n\n      UPDATE things SET id=&things_id_3, type=&things_type_3\n        WHERE id = &things_id_3;\n      INSERT INTO things (id, type)\n        SELECT &things_id_3, &things_type_3\n        WHERE NOT EXISTS (SELECT 3 FROM things WHERE id = &things_id_3);\n    END;\n\nIt uses dirty upsert for PostgreSQL, stolen from [bovine's answer on\nthis StackOverflow\nquestion](http://stackoverflow.com/questions/1109061/insert-on-duplicate-update-postgresql).\nThis dirty solution is good enough for most cases unless you use\nautoincrement on the primary key and your transaction is large, or in\nany scenario where primary key collision upon row creation is frequent.\nIt is recommended that you use UUID to avoid any problem. Upserting is a\n[complicated\nproblem](http://www.depesz.com/2012/06/10/why-is-upsert-so-complicated/)\nso some compromises must be made.\n\n#### The return values\n\n'Write' returns all the records *after* they have been updated (or not)\nby the database server. The format is exactly like what `Read` returns.\nFor instance:\n\n    BEGINGROUP: 'token'\n    BEGINGROUP: 'users'\n    DATA: {\n        ...\n        name: 'elephant'\n        ...\n      }\n    ENDGROUP: 'users'\n    BEGINGROUP: 'things'\n    DATA: {\n        ...\n        type: 'person'\n        ...\n      }\n    ENDGROUP: 'things'\n    ENDGROUP: 'token'\n\n\n### Output Filtering ###\n\nBecause the ORM outputs records as an array of records grouped by types\n(i.e. tables), it inserts a `_type` attribute to each record. If you\nwould like to remove it, pass an empty string to the 'FILTER' port and\nall attributes starting with an underscore (i.e. `_`) will be removed\nfor all records.\n\nYou may also pass in additional filters. Each packet is a filter that is\na RegExp string and filters based on the record's attribute key. For\ninstance, the following filters everything starting with an 'a' and\neverything ending with a 'z':\n\n    '^a' -> FILTER Read(pgorm/Read)\n    'z$' -> FILTER Read()\n    ... -> IN Read() OUT -> ...\n\n\n### Automatic table/column existence check ###\n\nThe 'Write' component also automatically filter incoming queries for\ninvalid tables and columns. This is possible as 'Write' fetches\ntable/column information from the server on initialization. The\ndownside, of course, is when the schema has changed on the PostgreSQL\nserver the NoFlo network needs to be refreshed.\n\nAnother note when using 'Write' is to remember to pipe the 'READY' port\nto your initialization process that activates anything that would run a\nquery against 'Write'. The component emits an empty connection to the\n'READY' port when it has finished fetching table/column information.\n\n    'tcp://default@localhost:5432/postgres' -> SERVER Write(pgorm/Write)\n    Write() READY -> ...\n\n\n### Different key ###\n\nThe ORM puts a `DISTINCT ON` on the \"primary\" key to ensure uniqueness\neven though the primary key itself should of course be declared unique\nwhen schema is set up. This \"primary\" key is defaulted to 'id'. You may\nconfigure the key by sending a new key to to the 'KEY' port. This only\nneeds to be done once at initialization.\n\nThis key is also used to order the rows with the `ORDER BY` clause. You\nmay change the order-by key to something else by sending `*key* ASC` to\nthe 'ORDERBY' port or change just the ordering by sending `DESC` to the\n'ORDERBY' port.\n\n    'tcp://default@localhost:5432/postgres' -> SERVER Write(pgorm/Write)\n    'uuid' -> KEY Write()\n    'name DESC' -> ORDERBY Write()\n\n\n### Error handling ###\n\nErrors from the PostgreSQL server are emitted to the 'ERROR' port.\nAttach a process to it to handle any server-side error.\n\n    'tcp://default@localhost:5432/postgres' -> SERVER Write(pgorm/Write)\n    Write() ERROR -> IN Error(Output)\n\n\n### Shutting down ###\n\nYou may shut down the connection to the PostgreSQL server by sending a\nnull packet to the 'QUIT' port.\n\n    'tcp://default@localhost:5432/postgres' -> SERVER Write(pgorm/Write)\n    '_' -> IN Kick(Kick) OUT -> QUIT Write()\n\nAll connections in a single program are pooled for efficiency. Sending a\nnull packet would kill all pgSQL connections. Pass the URL that was used\nto initialize the connection to 'QUIT' in order to kill just that one\nconnection.\n","maintainers":[{"name":"kenhkan","email":"kenhkan@gmail.com"}],"time":{"modified":"2022-06-22T04:26:40.830Z","created":"2013-04-30T05:39:46.928Z","0.0.1":"2013-04-30T05:39:48.532Z","0.0.2":"2013-05-01T22:15:01.620Z","0.0.3":"2013-05-03T05:13:06.865Z","0.0.4":"2013-05-03T08:11:41.848Z","0.0.5":"2013-05-04T16:16:39.750Z","0.0.6":"2013-05-05T03:25:43.785Z","0.0.7":"2013-05-06T08:48:42.291Z","0.0.8":"2013-05-09T05:34:47.266Z","0.0.9":"2013-05-09T21:28:43.822Z","0.0.10":"2013-05-10T01:42:20.253Z","0.0.11":"2013-05-11T00:16:29.208Z","0.0.12":"2013-06-12T07:30:27.832Z","0.0.13":"2013-06-12T07:57:31.320Z","0.0.14":"2013-09-10T02:20:04.035Z","0.0.15":"2013-09-12T01:51:10.858Z","0.0.16":"2013-09-12T04:23:58.449Z","0.0.17":"2013-09-12T06:26:46.825Z","0.0.18":"2013-09-12T21:31:19.807Z","0.0.19":"2013-09-18T02:18:26.671Z","0.0.20":"2013-09-18T02:42:39.354Z","0.0.21":"2013-09-18T04:17:33.255Z"},"author":{"name":"Kenneth Kan","email":"kenhkan@gmail.com"},"repository":{"type":"git","url":"https://github.com/kenhkan/noflo-pgorm"},"users":{"fgribreau":true},"keywords":["noflo","database","postgresql","postgres","pgsql","pg","sql","relational","mapping","orm"],"bugs":{"url":"https://github.com/kenhkan/noflo-pgorm/issues"},"readmeFilename":"README.md"}