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\"DynQ\")\n\n# DynQ\nAWS DynamoDB datastore library.  It makes data access layers based on DynamoDB easier to develop and maintain.  Call it \"dink\" if you like.  Amongst other things, this library features:\n\n* Schemas\n* Queries\n* Mixins\n* Automatic encoding/decoding of DynamoDB typed JSON format\n* Multi-master support\n\n## Installation\n\n    npm install dynq\n    \nTo use dynq, you need an [AWS account](https://aws.amazon.com/).  Once [signed into AWS](https://console.aws.amazon.com/console/home), go to [IAM Security Credentials](https://console.aws.amazon.com/iam/home?#security_credential) section, click on the Access Keys section and get an `access key id` and a `secret access key`.  Use these credentials to configure and connect `dynq` to AWS DynamoDB.\n\n## Get Started\n\nThe flexibility of `dynq` comes from using metadata.  A `schema` model uses table definitions and gets existing table metadata to facilitate more seamless programming.\n\n```javascript\nvar dynq = require(\"dynq\");\n\n// Configure using object or JSON file.\ndynq.config({ accessKeyId: \"xxx\", secretAccessKey: \"yyy\", maxRetries: 5, region: \"us-east-1\" });\n\n// Load a schema of tables from file or folder\nvar schema = dynq.connect().schema().require(path.join(__dirname, \"model\"), { \n    customize: \"reuseable model\", \n    configuration: \"Setting\", \n    enableFeature: true \n});\n    \n// Ensure tables exist and are 'active'\nschema.create({ \n    prefix: \"TABLE_PREFIX_\",\n    minReadCapacity: 25,\n    minWriteCapacity: 20\n}, (err) => { /* ready! */ });\n\n// Easily backup and restore data\nschema.backup(__dirname + \"/directory\", (err) => { });\nschema.restore(__dirname + \"/directory\", (err) => { });\n```\n\nConnections and tables build on the basic `putItem`, `deleteItem`, and `updateItem` actions to provide a more comprehensive set of record-level mutation methods.\n\n```javascript\n// Mutation operations\nvar table = schema.tables.table;\ntable.insert({ id: 1, range: 2 }, err => { ... });\ntable.write({ id: 1, range: 2 }, err => { ... });\ntable.upsert({ id: 1 range: 2 }, err => { ... });\ntable.update({ id: 1 range: 3 }, err => { ... });\ntable.delete(1, err => { ... });\n\n// Query operations\ntable.exists(1, (err, exists) = > { ... });\ntable.get(1, (err, item) => { ... });\ntable.getPart(1, [ \"range\" ], (err, item) => { ... });\n\n// Bulk operations\ntable.writeAll([ ... ], err => { ... });\ntable.getAll([ ... ], err => { ... });\ntable.deleteAll([ ... ], err => { ... });\n```\n\n__Queries__\n\nThe most advanced features of mutation operations supported by DyanmoDB are exposed though a series of builder classes exposed by a `table`.  \n\n```javascript\n// Query keys-only index and project rest of record\ntable.query({ id: 1 }).select.all((err, results) => { ... });\n\n// Query and update data\ntable.query({ id: 1, range: [ \"LT\", 10 ] })\n    .filter({ field: [ \"BEGINS_WITH\", \"abc\" ] })\n    .update((edit, cb) => {\n        edit.change({ ... }).add({ ... }).remove({ ... }).upsert(cb);\n    }).all(err => { ... });\n\n// Query and delete data\ntable.query({ id: 1, range: [ \"LT\", 10 ] })\n    .filter({ field: [ \"BEGINS_WITH\", \"abc\" ] })\n    .delete().all(err => { ... });\n```\n\n## Configuration\n\nConfigure library with standard [AWS configuration options](http://docs.aws.amazon.com/AWSJavaScriptSDK/latest/AWS/Config.html#constructor-property).\n\n* `dynq.config(config)` – Configure the AWS DynamoDB. Chainable with `connect` call.\n* `dynq.throughputHandler(destination, table, index)` – Callback on `ProvisionedThroughputExceededException` errors\n* `dynq.debug` – Outputs all Dynamo operations to the logger.\n* `dynq.logger` – Logger used in conjunction with debug.  Defaults to console.log.\n\n### Connections\n\n```javascript\n// Create a simple connection\nvar cxn = new dynq.Connection({ region: \"us-east-1\" });\n\n// Create a multi-master connection with an array of AWS regions.\ncxn = dynq.connect({ regions: [ \"us-east-1\", \"us-west-1\" ], distribute: true });\n```\n\nCreate connections with the builder method or constructor syntax.\n\n* `dynq.connect(options)`\n* `new dynq.Connection(options)`\n\n__Additional Options__\n\n* `regions` - A string or array of AWS regions (e.g. us-east-1).\n* `distribute` - A boolean value specifying if reads should be distributed across regions.\n\n### Schemas\n\nSchemas put a programming model around DynamoDB tables using metadata and definition objects.  The easiest way to define a table schema is within a javascript file loaded with the `schema.require` method.\n\n__Schema Example__\n```javascript\n// index.js\nvar schema = dynq.connect().schema().require(\"user.js\", { \n    ... /* options */\n}).create({ \n    ... /* options */\n}, (err, schema) => {\n    ... /* ready */\n});\n\n// user.js\nmodule.exports = {\n    name: \"UsersTable\",\n    key: { id: \"string\" },\n    read: 5,\n    write: 5,\n    sort: {\n        ByUser: {\n            columns: { user: \"string\" },\n            project: \"ALL\"\n        }\n    },\n    indices: {\n        ByTimestamp: {\n            columns: { timestamp: \"number\" },\n            read: 5,\n            write: 5,\n            project: \"ALL\"\n        }\n    },\n    members: function(table) {\n        // These methods will be mixed-in with the table object\n        this.foo = function(cb) {\n            cb();\n        };\n    }\n};\n```\n\n__NOTE:__ The `schema.require` method uses the file name as the identifier within the programming model (i.e. `schema.tables.user`).\n\nThe `schema.require` method may take options, which allows development of reuseable table schema generators, or components.  `options` passed to the `schema.require` method are available to a schema definition when defined as a function.\n\n```javascript\n// to expose options use a function\nmodule.exports = function(options) {\n    return { \n        name: \"Users\",\n        key: { id: \"string\" },\n        read: 5,\n        write: 5,\n        ...\n    };\n}\n```\n\nBecause a schema definition can be thought of as a flexible component, the `schema.create` method also takes options that support customizations like table name prefixes (`prefix`) and read/write capacities (`minReadCapacity` and `minWriteCapacity`).\n\n__Mixins and Behaviors__\n\nA big advantage of schemaless databases like Dynamo is that the data model is readily extensible.  Methods added to the table can easily manipulate state, thereby implementing some semantically significant functionality.  For example, an `articles` table might benefit from a `publish` method.\n\nTable objects in a schema can be extended through mixins.  A mixin takes the form of a function or class which will be initialized with the inheriting table.  They are mounted on table definitions using the `mixin`, `members`, `properties`, or `methods` fields.  The `mixins` field may be used to mount multiple mixins as an array, which is useful in the development and composition of components.\n\n```javascript\nfunction(table) { \n    this.sample = cb => { cb(); };\n}\n\n// - or -\n\nclass mixin {\n    constructor(table) { }\n}\n```\n\nA behavior is a mixin that also has access to, and may manipulate, the table definition itself.  In the example of the `articles` table and `publish` method above, this functionality may be enhanced by a global secondary index on a `published` field.  A behavior not only implements the functional logic, but might also add an index or query the existing schema.\n\n```javascript\n// behavior.js\nexports.module = function(option) {\n    // perform some logic based on options\n    var indexName = options.indexName;\n    return function(definition) {\n        // inspect or alter defintion\n        defintion.indicies[indexName] = { columns: { id: \"text\" } };\n        return function(table) {\n            // add mixin methods\n            this.operation = (cb) => {\n                // table exists within this scope\n            };\n        };\n    };\n};\n\n// schema.js\nexports.module = function(options) {\n    // behaviors allow composition of table functionality\n    return {\n        name: \"table\",\n        key: { id: \"string\" },\n        behaviors: require(\"behavior.js\")(options)\n    };\n};\n```\n\n__Programming Model__\n\nA `dyna.schema` provides table creation, modification, and deletion functionality and pares this with table definition and description schemas.\n\nTables can be defined with the `schema.define` and `schema.require` methods, which merge into the overall `schema.definition` object.  If you have a tables already created, use the `schema.load` to populate the schema from DynamoDB table descriptions.\n\nTo bring a schema to life, call the `schema.create` which enumerates through each table in `schema.definition`.  Existing tables are loaded via `schema.load` and ones that do not are created.  All tables can be deleted with `schema.drop`.  The entire schema can be `schema.backup`'d to and `schema.restore`'d from a folder of flat files.\n\nOnce a schema has been created, `schema.tables` contain the `dynq.table` objects to be read and written.\n\n```javascript\nvar schema = dynq.connect(\"us-east-1\").schema();\n```\n\n__State__\n* `schema.connection` - The underlying connection.\n* `schema.tables` - A map of loaded tables.\n* `schema.definition` - A definition of tables to be created or loaded.\n\n__Table Creation, Modification, and Deletion Methods__\n* `schema.listSomeTables(last, cb)` - List a page of tables starting from last.\n* `schema.listAllTables(cb)` - List all tables (automatically page until end).\n* `schema.createTable(definition, cb)` - Create a table.  Definition is in format of the _Schema Example_ below.\n* `schema.deleteTable(table, cb)` - Deletes a table.\n* `schema.describeTable(table, cb)` - Load table metadata.\n* `schema.changeThroughput(table, read, write, cb)` - Change throughput for a table.\n* `schema.changeIndexThroughput(table, index, read, write, cb)` - Change throughput for an index.\n* `schema.factorThroughput(description, factor, cb)` - Factors throughput across the table and its indices.\n\n__Schema Management Methods__\n* `schema.load(filter, cb)` - Load tables with names that match filter.\n* `schema.define(definition)` - Merge into `schema.definition` from object.\n* `schema.require(filepath, [options])` - Loads a table into `schema.definition` from a module.  If a directory is specified, all modules are loaded.\n* `schema.create([options,] cb)` - Load tables from `schema.definition` and create ones that do not exist.\n* `schema.drop(cb)` - Drop tables from `schema.definition` that exist.\n* `schema.backup(dir, cb)` - Saves data from loaded DyanmoDB tables into JSON files.\n* `schema.restore(dir, cb)` - Load records into DynamoDB tables from JSON files in the given directory.\n\n### Tables\n\nTables are accessed through the `schema.table` object and use DynamoDB table description metadata to provide programming abstrations above the low-level DynamoDB API.  With knowledge of the key attributes, a `table` provide conditional record-level methods like `insert`, `update`, and `exists`.  Mass operations like `writeAll`, `deleteAll`, and `getAll` use smart batching logic to gracefully handle DynamoDB operation limitations.\n\nThe `table.query` and `table.edit` are builder interfaces for more complicated actions.  The `edit` interface allows for `add` and `remove` operations (in addition to `change`) on individual items.  The `query` interface invokes index queries and table scans, whose data can either be directly returned, or repurposed as keys for a batch select, update, or delete operation.\n\n`table.mixin` enables extension of `table` methods.  Only methods with names who do not already exist will be mixed into the `table`.\n\n```javascript\nvar schema = dynq.connect(\"us-east-1\").schema();\n\nschema.load(/PREFIX_.*/i, function(err) {\n    var table = schema.tables[\"PREFIX_Users\"];\n    table.mixin(function(table) {\n        this.foo = cb => { cb() };\n    });\n    \n    table.foo(cb => { });\n});\n```\n\n__Table-Level Members__\n* `table.name` - The name of the table.\n* `table.schema` - The schema to which this table belongs.\n* `table.description` - The metadata from `schema.describeTable(name)`.\n* `table.mixin(class)` – Initializes a `class` with this table and mixes in the instance methods.\n* `table.changeThroughput(read, write, cb)` - Change throughput for a table.\n* `table.changeIndexThroughput(index, read, write, cb)` - Change throughput for an index.\n* `table.factorThroughput(factor, cb)` - Factors throughput across the table and its indices.\n* `table.drop(cb)` - Drops this table.\n\n__File Methods__\n* `table.backup(filepath, cb)` - Save the contents of the DynamoDB table to a file.\n* `table.restore(filepath, cb)` - Load the contents of a file to the DynamoDB table.\n\n__Record-Level Methods__\n* `table.write(obj, cb)` - Writes a record to the table.  If a record with the same key already exists, it is overwritten.\n* `table.writeAll(objs, cb)` - Writes records to the table.  If a record with the same key already exists, it is overwritten.\n* `table.insert(obj, cb)` - Inserts a record into the table.  If a record with the same key already exists, the operation fails.\n* `table.delete(key, cb)` - Deletes a record from the table with the given key.\n* `table.deleteAll(keys, cb)` - Deletes records from the table with the given keys.\n* `table.deleteIf(key, expect, cb)` - Deletes a record from the table with the given key if the expected field values are matched.\n* `table.exists(key, cb)` - Indicates if a record with the given key exists.\n* `table.get(key, cb)` - Gets the full record that matches the given key.\n* `table.getPart(key, select, cb)` - Get part of the record that matches the given key.\n* `table.getAll(keys, select, cb)` - Get many records.\n\n__Query Interface__\n* `table.query()` - Returns a query interface configured to filter based on an index.\n* `table.scan()` - Returns a query interface configured to filter on a table scan.\n* `query.index(name)` - The name of an index to query (if not querying the primary key).\n* `query.conditions(conditions)` - The conditions on the key and hash of the index.\n* `query.filter(filter)` - Set filter conditions on non-indexed fields.\n* `query.expression(expression)` - Set filter expression on non-indexed fields.\n* `query.or()` - Change filter conditions from \"and\" to \"or\".\n* `query.select(select)` - A list of attributes to select, an attribute qualifier, or a projection expression. If empty, the whole record is projected with a separate getItem operation.\n* `query.update(editor)` – An update operation to be performed on each item, taking an `edit` interface object and a `cb`.\n* `query.delete()` - Delete the queried records.\n* `query.backwards()` - Reverse the order in which records are returned.\n* `query.direction(direction)` - Set the order in which records are returned.\n* `query.segment(segment, total)` - Segment a scan operation into parts.\n* `query.start(start)` - Start query from this key.\n* `query.limit(count)` - Maximum number of records to query.\n* `query.first(cb)` - Return the first record from the query.\n* `query.page(cb)` - Return a page of records.\n* `query.all(cb)` - Return all records (automatically paging until the end).\n* `query.debug(cb)` - Write the JSON of the query and return it if a cb is supplied.\n\n__Edit Interface__\n* `table.edit(obj)` - Returns an edit interface to alter or insert records.\n* `edit.change(values)` - Field values to be changed/overwritten.  (Fields without a value are set to null; to remove fields, use remove/delete.)\n* `edit.put(values)` – Alias for `edit.change`.\n* `edit.add(values)` - Field values to be added.  If numeric, this means atomic addition/subtraction.  If a set, this means addition to the set.\n* `edit.remove(values)` - Field values to be removed.  If a set, this means removal from the set.  If an array, denotes a list of fields to be removed.\n* `edit.delete(values)` - Alias for `edit.remove`.\n* `edit.conditions(expected)` - Values expected to be found in the record.  If not matched, the operation fails.\n* `edit.select(select)` - A list of fields to select from the record.\n* `edit.update(cb)` - Updates the record.  If a record does not exist, the operation fails.\n* `edit.upsert(cb)` - Upserts the record.  If a record does not exists, one is created.\n* `edit.debug(cb)` - Write the JSON of the query and return it if a cb is supplied.\n\n__Conditions Composer__\n\nCalls that take a `conditions` object may build this object using the conditions composer interface by passing a function instead.\n\n```javascript\ntable.where(op => op.field(\"id\").equals(1).and(\"timestamp\").greaterThan(12341234));\n// instead of\ntable.where({ id: 1, timestamp: [ \"greater than\", 12341234 ] });\n```\n\n* `conditions.field(name)` - Sets up a new condition on a table attribute.\n* `conditions.and(name)` - Alias for `conditions.field` to improve readability.  Actual conditional operator set on `query` interface.\n* `conditions.or(name)` - Alias for `conditions.field`.  Actual conditional operator set on `query` interface.\n* `conditions.equals(value)` - Right hand side of field condition.  Should follow a field declaration.\n* `conditions.notEqual(value)` - Right hand side of field condition.  Should follow a field declaration.\n* `conditions.lessThan(value)` - Right hand side of field condition.  Should follow a field declaration.\n* `conditions.lessThanOrEqual(value)` - Right hand side of field condition.  Should follow a field declaration.\n* `conditions.greaterThan(value)` - Right hand side of field condition.  Should follow a field declaration.\n* `conditions.greaterThanOrEqual(value)` - Right hand side of field condition.  Should follow a field declaration.\n* `conditions.notNull()` - Right hand side of field condition.  Should follow a field declaration.\n* `conditions.isNull()` - Right hand side of field condition.  Should follow a field declaration.\n* `conditions.contains(value)` - Right hand side of field condition.  Should follow a field declaration.\n* `conditions.doesNotContain(value)` - Right hand side of field condition.  Should follow a field declaration.\n* `conditions.beginsWith(value)` - Right hand side of field condition.  Should follow a field declaration.\n* `conditions.in(array)` - Right hand side of field condition.  Should follow a field declaration.\n* `conditions.between(min, max)` - Right hand side of field condition.  Should follow a field declaration.\n* `conditions.toConditions()` - Returns a conditions object that can be used in a call to `conditions`.\n\n__Expression Composer__\n\nThe expression composer interface simplifies DynamoDB expressions by assembling the expression string while simultaneously populating the `ExpressionAttributeNames` and `ExpressionAttributeValues` parameters.\n\n```javascript\ntable.query().expression(if => if(\"id\", \"=\", 1).and(\"timestamp\", \"between\", 12341234, 23452345).and().exists(\"somefield\").or(\"size(text)\", \">\", 2));\n```\n__comparator__ can be \"in\", \"between\", \"<>\", \"<\", \"<=\", \">\", \">=\".\n__operand__ can be an attribute name, a path, or the \"size\" function.\n__value2__ is only used with the \"between\" comparator.\n\n* `expression.if(operand, comparator, value, [value2])` - Sets up a new condition on a table attribute.\n* `expression.and([operand, comparator, value, [value2]])` - Sets up a new condition on a table attribute.\n* `expression.or([operand, comparator, value, [value2]])` - Sets up a new condition on a table attribute.\n* `expression.not([operand, comparator, value, [value2]])` - Sets up a new condition on a table attribute.\n* `expression.exists(path)` - Checks if an attribute or path exists.\n* `expression.missing(path)` - Checks if an attribute or path does not exist.\n* `expression.type(path, type)` - Checks if an attribute or path has the given datatype.\n* `expression.begins(path, substr)` - Checks if an attribute or path begins with a given value.\n* `expression.contains(path, value)` - Checks if an attribute or path contains a given value.\n* `expression.toExpression()` - Returns the composed expression string\n\n### Low-Level Connection Interface\n\nThe `dynq` module supports the `logger` and `debug` global configuration operations.  The `logger` defaults to `console.log`.  If `debug` is set to true, all DynamoDB native operations are logged.\n\nThe `Connection` class provides access to native DynamoDB operations with multi-master support and throughput handling infrastructure.  Some  conditional and mass operations like `insert` and `insertAll` are build on top of the native calls to support higher-level table operations.\n\n##### Configuration\n\n* `cxn.distributeReads` – If multiple masters are specified, each read is dispatched to a randomly selected source.\n* `cxn.destinations` – An array of service interfaces used in a multi-master configuration.\n* `cxn.debug` –  Outputs all connection operations to the logger.\n* `cxn.addDestination(options)` – Adds an additional destination to the `destinations` array after construction.\n\n##### Methods\n\n* `cxn.write(table, item, cb)` – Writes an item.\n* `cxn.writeAll(table, items, cb)` – Writes multiple items.\n* `cxn.insert(table, keyAttr, item, cb)` – Inserts an item.  If an item with the same key exists, the operation fails.\n* `cxn.upsert(table, keyAttr, item, cb)` – Upserts an item.  If the item exists, the fields are merged with the existing item.\n* `cxn.update(table, keyAttr, item, cb)` – Updates an item.  If an item with the same key does not exist, the operation fails.\n* `cxn.exists(table, key, cb)` – Returns a boolean value indicating if an item with the given key exists.\n* `cxn.get(table, key, cb)` – Gets an item with the given key.\n* `cxn.getPart(table, key, select, cb)` – Gets part of an item.\n* `cxn.getAll(table, keys, select, cb)` – Gets all items with matching keys.\n* `cxn.getMany(map, cb)` – Get many items from multple tables.  Map has keys corresponding to table names, and values containing `keys` and `select`.\n* `cxn.delete(table, key, expected, cb)` – Deletes a item with the matching key and optionally other expected values.\n* `cxn.deleteAll(table, keys, cb)` – Deletes all items with matching keys.\n\n__Arguments__\n\n* `table` - A string specifying the name of a DynamoDB table.\n* `keyAttr` - A string or array of key attribute names.\n* `key` - An object specifying the unique key of the item.\n* `item` - An object representing a table record.\n* `select` - An projection expression or an array of strings specifying attributes to get.\n* `expected` - An object representing a set of fields that must be matched for the operation to succeed.\n* `cb` - Callback with an error and results parameters.\n\nThese methods automatically encode parameters to and decode responses from the DynamoDB typed JSON format.\n\n##### Native DynamoDB Operation Proxies\n\nThe returned connections are compatible with the [AWS DynamoDB API](http://docs.aws.amazon.com/AWSJavaScriptSDK/latest/AWS/DynamoDB.html).\n\n* `cxn.batchGetItem(params, cb)`\n* `cxn.batchWriteItem(params, cb)`\n* `cxn.createTable(params, cb)`\n* `cxn.deleteItem(params, cb)`\n* `cxn.deleteTable(params, cb)`\n* `cxn.describeTable(params, cb)`\n* `cxn.getItem(params, cb)`\n* `cxn.listTables(params, cb)`\n* `cxn.putItem(params, cb)`\n* `cxn.query(params, cb)`\n* `cxn.scan(params, cb)`\n* `cxn.updateItem(params, cb)`\n* `cxn.updateTable(params, cb)`\n* `cxn.waitFor(event, options, cb)`\n\n__Arguments__\n\n* `params` - An object specifying query parameters according to AWS Dynamo documentation.\n* `cb` - Callback with an error and results parameters.\n\nThese methods do not automatically decode responses in the DynamoDB typed JSON format.","maintainers":[{"name":"triploc","email":"src@jonholl.com"}],"time":{"modified":"2022-06-16T02:58:33.425Z","created":"2016-03-02T05:56:19.613Z","1.0.0":"2016-03-02T05:56:19.613Z","1.0.1":"2016-03-08T07:26:54.450Z","1.0.2":"2016-03-09T02:08:49.900Z","1.0.3":"2016-03-09T05:53:28.211Z","1.0.4":"2016-03-09T21:18:20.893Z","1.0.5":"2016-03-09T21:22:30.302Z","1.0.6":"2016-03-10T00:11:57.221Z","1.0.7":"2016-03-10T02:26:37.090Z","1.0.8":"2016-03-10T04:14:09.281Z","1.0.9":"2016-03-11T20:45:41.508Z","1.0.10":"2016-03-11T22:29:58.263Z","1.0.11":"2016-03-11T22:59:12.758Z","1.0.12":"2016-03-13T00:34:34.410Z","1.0.13":"2016-03-13T21:55:48.845Z","1.0.14":"2016-03-13T22:42:20.947Z","1.0.15":"2016-03-20T03:05:26.758Z","1.0.16":"2016-03-20T05:15:03.743Z","1.0.17":"2016-03-20T07:26:14.129Z","1.0.18":"2016-03-20T19:44:34.636Z","1.0.19":"2016-03-21T01:04:24.000Z","1.0.20":"2016-03-26T04:17:10.008Z","1.0.21":"2016-03-27T03:24:39.553Z","1.0.22":"2016-03-27T10:43:18.742Z","1.0.23":"2016-03-27T22:47:06.529Z","1.1.0":"2016-04-16T21:40:25.490Z","1.1.1":"2016-04-18T23:51:56.035Z","1.1.2":"2016-04-19T19:52:29.574Z","1.1.3":"2016-04-19T21:52:53.244Z","1.1.4":"2016-04-21T17:57:02.245Z","1.1.5":"2016-04-21T19:29:01.104Z","1.1.6":"2016-04-22T00:28:10.781Z","1.1.7":"2016-04-22T19:46:18.825Z","1.1.8":"2016-04-22T20:33:33.429Z","1.1.9":"2016-04-22T21:07:45.206Z","1.2.0":"2016-04-28T01:34:32.290Z","1.2.1":"2016-05-01T20:38:36.029Z"},"homepage":"https://github.com/triploc/dynq#readme","keywords":["AWS","DynamoDB","query","dynamo"],"repository":{"type":"git","url":"git+ssh://git@github.com/triploc/dynq.git"},"author":{"name":"Jonathan Hollinger"},"bugs":{"url":"https://github.com/triploc/dynq/issues"},"license":"MIT","readmeFilename":"README.md"}