gocrud

Go framework to simplify CRUD of structured data using Graph operations

  • 所有者: manishrjain/gocrud
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gocrud

Go framework to simplify creating, reading, updating, and deleting arbitrary depth structured data — to make building REST services fast and easy.

wercker status
GoDoc

Releases

Note that the master branch always refers to latest version of Gocrud, which would contain breaking changes.
To use stable version of Gocrud APIs, please use the packages released via gopkg.in.

Gocrud version, Install instructions, Godoc, Source
:---:, ---, ---, ---
v1 (stable), go get -v gopkg.in/manishrjain/gocrud.v1/..., godoc, source
master (dev), go get -v github.com/manishrjain/gocrud/..., godoc, source

Questions / Support

I primarily use IRC on freenode network. Channel is #gocrud. I'm mrjn on the network.
#gocrud on freenode

I also hang out at the gophers.slack.com, at #gocrud channel.
Although, Slack doesn't have a linux client which is what my workstation runs, and hence, I prefer IRC over Slack.
You can get an invitation to join Slack via this link:
Gopher Slack Signup.
You can also direct message me, my user id is @manishrjain.

Why?

Courtesy: Monish, co-founder karma.wiki

Having built over 3 different startup backends, I think a lot of time is wasted figuring out and coding CRUD for data structures. In addition, the choice of database has to be made up front, which causes a lot of headache for startup founders. Gocrud was written with the aim to make CRUD easy, and provide the flexibility to switch out both the underlying storage and search engines at any stage of development.

Data stores

Datastore, Driver Available, Status
---, :---:, ---
LevelDB, Yes, Ready
MySQL, Yes, Needs to implement Iterate func
PostgreSQL, Yes, Needs to implement Iterate func
Cassandra, Yes, Ready
MongoDB, Yes, Needs to implement Iterate func
Google Datastore, Yes, Needs to implement Iterate func
RethinkDB, Yes, Needs to implement Iterate func
Amazon DynamoDB, No, Needs work
Datastore usage shows how to use and initialize various datastores. One can add support for more by implementing this interface:

type Store interface {
  Init(args ...string)
  Commit(its []*x.Instruction) error
  IsNew(subject string) bool
  GetEntity(subject string) ([]x.Instruction, error)
  Iterate(fromId string, num int, ch chan x.Entity) (int, error)
}

Search engines

Search Engine, Drive Available
---, :---:
Elastic Search, Yes
Solr, No

Can be added by implementing these interfaces:

type Engine interface {
	Init(args ...string)
	Update(x.Doc) error
	NewQuery(kind string) Query
}

type Query interface {
	Limit(num int) Query
	Order(field string) Query
	Run() ([]x.Doc, error)
  // and few others
}

Framework

This framework is built to follow these principles:

  1. Versioning: Keep track of all edits to the data, including deletion operations.
  2. Authorship: Be able to track who edited (/deleted) what.
  3. Retention: On deletion, only mark it as deleted. Never actually delete any data.

The framework makes it easy to have Parent-Child relationships, quite common in today’s CRUD operations. For e.g.

- Posts created by User (User -> Post)
- Comments on Posts (Post -> Comment)
- Likes on Posts (Post -> Like)
- Likes on Comments (Comment -> Like)

And be able to traverse these relationships and retrieve all of the children, grandchildren etc. For e.g. (User -> Post -> [(Comment -> Like), Like])

The framework does this by utilizing Graph operations, but without using a Graph database. This means the framework can be used to quickly build a Go backend to serve arbitrarily complex data, while still using your database of choice. See example usage

Dependency management

Users who import Gocrud into their packages are responsible to organize
and maintain all of their dependencies to ensure code compatibility and build
reproducibility. Gocrud makes no direct use of dependency management tools like
Godep.

Performance considerations

For the example, this is what gets stored in the database:

mysql> select * from instructions;
+------------+--------------+-----------+--------------------------------------+-----------+---------------------+---------+----+, subject_id, subject_type, predicate, object, object_id, nano_ts, source, id, +------------+--------------+-----------+--------------------------------------+-----------+---------------------+---------+----+, uid_oNM, User, Post, NULL, wClGp, 1435408916326573229, uid_oNM, 1, wClGp, Post, body, "You can search for cat videos here", 1435408916326573229, uid_oNM, 2, wClGp, Post, tags, ["search","cat","videos"], 1435408916326573229, uid_oNM, 3, wClGp, Post, url, "www.google.com", 1435408916326573229, uid_oNM, 4, wClGp, Post, Like, NULL, kStx9, 1435408916341828408, uid_qB3, 5, kStx9, Like, thumb, 1, 1435408916341828408, uid_qB3, 6, wClGp, Post, Comment, NULL, 8f78r, 1435408916341828408, uid_qB3, 7, 8f78r, Comment, body, "Comment by on the post", 1435408916341828408, uid_qB3, 8, wClGp, Post, Like, NULL, Gyd7G, 1435408916352622582, uid_a30, 9, Gyd7G, Like, thumb, 1, 1435408916352622582, uid_a30, 10, 8f78r, Comment, Like, NULL, q2IKK, 1435408916357443075, uid_I5u, 11, q2IKK, Like, thumb, 1, 1435408916357443075, uid_I5u, 12, 8f78r, Comment, Comment, NULL, g8llL, 1435408916357443075, uid_I5u, 13, g8llL, Comment, body, "Comment xv on comment", 1435408916357443075, uid_I5u, 14, q2IKK, Like, Comment, NULL, oaztb, 1435408916368908590, uid_SPX, 15, oaztb, Comment, body, "Comment kL on Like", 1435408916368908590, uid_SPX, 16, 8f78r, Comment, censored, true, 1435408916377065650, uid_D2g, 17, kStx9, Like, _delete_, true, 1435408916384422689, uid_2a5, 18, +------------+--------------+-----------+--------------------------------------+-----------+---------------------+---------+----+
18 rows in set (0.00 sec)

The writes are in constant time, where each (entity,predicate) constitutes one row. As the properties per entity grow, more rows need to be read (1 row = 1 edge/predicate) to get the entity, it's predicates and it's children. This however, shouldn't be much of a concern for any standard data, which has limited number of predicates/properties per entity. Gocrud in addition, retrieves all children in parallel via goroutines, instead of retrieving them one by one.

Property value filtering, sorting, full and partial text matching are now being made available via various search engines. Gocrud provides a search interface, which provides the most common search functionality right out of the box. Thus, there's a clear distinction between data store and search right from the beginning.

Reserved keywords

The following predicates are reserved by the framework, and shouldn't be used by the caller. Currently, this guideline isn't being hardly enforced by the framework.

Predicate, Meaning
---, ---
_parent_, Stores an edge from child -> parent entity.
_delete_, Marks a particular entity as deleted.

Contact

Feel free to contact me at my Twitter handle @manishrjain for any discussions related to this framework. Also, feel free to send pull requests, they're welcome!

主要指標

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名稱與所有者manishrjain/gocrud
主編程語言Go
編程語言Go (語言數: 1)
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許可證MIT License
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創建於2015-06-19 01:42:33
推送於2019-03-01 00:20:42
最后一次提交2019-02-28 16:20:41
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