Update README and small stuff
Changed the zipponschema example to have friends as list of string Better README, created ZiQL.md for more details on query Added fast build option
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README.md
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README.md
@ -2,26 +2,28 @@
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# Introduction
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ZipponDB is a relational database written entirely in Zig from stractch with 0 dependency.
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ZipponDB is a relational database written entirely in Zig from scratch with 0 dependency.
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ZipponDB goal is to be ACID, light, simple and high performance. It aim small to medium application that don't need fancy features but a simple and reliable database.
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ZipponDB goal is to be ACID, light, simple and high performance. It aim small to medium application that don't need fancy features but a simple and reliable database.
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### Why Zippon ?
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- Open-source and written 100% in Zig with 0 dependency
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- Relational database
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- Relational database (Soon)
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- Simple and minimal query language
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- Small, light, fast and implementable everywhere
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# Quickstart
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You can build the binary directly from the source code (tuto is comming), or using the binary in the release (comming too).
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1. **Get a binary:** You can build the binary directly from the source code for any architecture (tuto is comming), or using the binary in the release (comming too).
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2. **Create a database:** You can then run the binary, this will start a Command Line Interface. The first thing to do is to create a new database. For that run the command `db new path/to/directory`,
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it will create a `ZipponDB` directory. Then `database metrics` to see if it worked.
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3. **Select a database:** You can select a database by using `db use path/to/ZipponDB`. You can also set the environment variable ZIPPONDB_PATH and it will and use this path,
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this need to be the path to a directory with proper DATA, BACKUP and LOG directory.
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4. **Attach a schema:** Once the database created, you need to attach a schema to it (see next section for how to define a schema). For that you can run `schema init path/to/schema.txt`.
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This will create new directories and empty files used to store data. You can test the current db schema by running `schema describe`.
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5. **Use the database:** You can now start using the database by sending query like that: `run "ADD User (name = 'Bob')"`.
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You can then run it, starting a Command Line Interface. The first thing to do is to create a new database. For that run the command `db new path/to/folder`, it will create a `ZipponDB` folder with multiple stuffs inside. Then `database metrics` to see if it worked. You can change between database by using `db swap path/to/ZipponDB`.
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Once the database created, you need to attach a schema to it (see next section for how to define a schema). For that you can run `schema init path/to/schema.txt`. This will create new folder and empty files used to store data.
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You can now start using the database by sending query like that: `run "ADD User (name = 'Bob')"`.
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***Note: For the moment ZipponDB use the current working directory as main directory so all path are a sub_path of it.***
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# Declare a schema
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@ -67,9 +69,7 @@ Comment (
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Note: `[]` before the type mean a list/array of this type.
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### Migration to a new schema
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***Not yet implemented***
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### Migration to a new schema - Not yet implemented
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In the future, you will be able to update the schema like add a new member to a struct and update the database. For the moment, you can't change the schema once init.
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@ -79,212 +79,61 @@ ZipponDB use it's own query language, ZipponQL or ZiQL for short. Here the keys
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- 4 actions available: `GRAB` `ADD` `UPDATE` `DELETE`
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- All query start with an action then a struct name
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- `{}` Are filters
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- `[]` Are how much; what data
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- `()` Are new or updated data (Not already in file)
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- `||` Are additional options
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- By default all member that are not link are return
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- To return link or only some members, specify them between `[]`
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- `{}` For filters
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- `[]` For how much; what data
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- `()` For new or updated data (Not already in file)
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- `||` For additional options
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***Disclaimer: Lot of stuff are still missing and the language may change over time.***
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## GRAB
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## Quickstart
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The main action is `GRAB`, this will parse files and return data.
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**For more information see [ZiQL Introduction](https://github.com/MrBounty/ZipponDB/blob/main/ZiQL.md)**
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Here how to return all `User` without any filtering:
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```js
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GRAB User
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```
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### GRAB
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To get all `User` above 18 years old:
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```js
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GRAB User {age > 18}
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```
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To only return the name of `User`:
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```js
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GRAB User [name] {age > 18}
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```
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To return the 10 first `User`:
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```js
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GRAB User [10] {age > 18}
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```
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You can use both:
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```js
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GRAB User [10; name] {age > 18}
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```
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To order it using the name:
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```js
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GRAB User [10; name] {age > 10} |ASC name|
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```
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Use multiple condition:
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The main action is `GRAB`, this will parse files and return data.
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```js
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GRAB User {name = 'Bob' AND (age > 30 OR age < 10)}
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```
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#### Not yet implemented
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You can specify how much and what to return even for link inside struct. In this example I get 1 friend name for 10 `User`:
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```js
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GRAB User [10; friends [1; name]]
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GRAB query return a list of JSON with the data inside, e.g:
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```
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[{id:"1e170a80-84c9-429a-be25-ab4657894653", name: "Gwendolyn Ray", age: 70, email: "austin92@example.org", scores: [ 77 ], friends: [], }, ]
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```
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##### Using IN
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You can use the `IN` operator to check if something is in an array:
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```js
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GRAB User { age > 10 AND name IN ['Adrien' 'Bob']}
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```
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### ADD
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This also work by using other filter. Here I get `User` that have a best friend named Adrien:
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```js
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GRAB User { bestfriend IN { name = 'Adrien' } }
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```
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When using an array with IN, it will return all `User` that have at least ONE friend named Adrien:
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```js
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GRAB User { friends IN { name = 'Adrien' } }
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```
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To get `User` with ALL friends named Adrien:
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```js
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GRAB User { friends ALLIN { name = 'Adrien' } }
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```
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You can use `IN` on itself. Here I get all `User` that liked a `Comment` that is from 2024. Both queries return the same thing:
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```js
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GRAB User { IN Comment {at > '2024/01/01'}.like_by}
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GRAB Comment.like_by { at > '2024/01/01'}
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```
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You can optain a similar result with this query but it will return a list of `Comment` with a member `liked_by` that is similar to `User` above. If you take all `liked_by` inside all `Comment`, it will be the same list but you can end up with duplicate as one `User` can like multiple `Comment`.
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```js
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GRAB Comment [liked_by] {at > '2024/01/01'}
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```
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##### Return relationship
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You can also return a relationship only. The filter will be done on `User` but will return `Comment`:
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```js
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GRAB User.comments {name = 'Bob'}
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```
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You can do it as much as you like. This will return all `User` that liked comments from Bob:
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```js
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GRAB User.comments.like_by {name = 'Bob'}
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```
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This can also be use inside filter. Note that we need to specify `User` because it is a different struct that `Post`. Here I get all `Post` that have a comment from Bob:
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```js
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GRAB Post {comments IN User{name = 'Bob'}.comments}
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```
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Can also do the same but only for the first Bob found:
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```js
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GRAB Post {comments IN User [1] {name = 'Bob'}.comments}
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```
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Be carefull, this will return all `User` that liked a comment from 10 `User` named Bob:
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```js
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GRAB User.comments.like_by [10] {name = 'Bob'}
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```
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To get 10 `User` that liked a comment from any `User` named Bob, you need to use:
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```js
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GRAB User.comments.like_by [comments [like_by [10]]] {name = 'Bob'}
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```
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##### Using !
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You can use `!` to return the opposite. Use with `IN`, it check if it is NOT is the list. Use it with filters, it return entities that do not respect the filter.
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This will return all `User` that didn't like a `Comment` in 2024:
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```js
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GRAB User { !IN Comment {at > '2024/01/01'}.like_by}
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```
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Be carefull because this do not return the same, it return all `User` that liked a `Comment` not in 2024:
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```js
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GRAB Comment.like_by !{ at > '2024/01/01'}
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```
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Which is the same as:
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```js
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GRAB Comment.like_by { at < '2024/01/01'}
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```
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## ADD
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The `ADD` action will add one entity into the database.
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The synthax is similare but use `()`, this mean that the data is not yet in the database.
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Here an example:
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The `ADD` action will add one entity into the database.
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```js
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ADD User (name = 'Bob', age = 30, email = 'bob@email.com', scores = [1 100 44 82])
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```
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You need to specify all member when adding an entity (default value are comming).
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### DELETE
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#### Not yet implemented
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And you can also add them in batch
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```js
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ADD User (name = 'Bob', age = 30, email = 'bob@email.com', scores = [1 100 44 82]) (name = 'Bob2', age = 33, email = 'bob2@email.com', scores = [])
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```
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You don't need to specify the member in the second entity as long as the order is respected.
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```js
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ADD User (name = 'Bob', age = 30, email = 'bob@email.com', scores = [1 100 44 82]) ('Bob2', 33, 'bob2@email.com', [])
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```
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## DELETE
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Similare to `GRAB` but delete all entity found using the filter and return the list of UUID deleted.
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Similare to `GRAB` but delete all entity found using the filter.
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```js
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DELETE User {name = 'Bob'}
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```
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## UPDATE
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### UPDATE
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A mix of `GRAB` and `ADD`. This take a filter first, then the new data.
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Here we update the 5 first User named `adrien` to add a capital and become `Adrien`.
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Here we update the 5 first User named `bob` to add a capital and become `Bob`.
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```js
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UPDATE User [5] {name='adrien'} TO (name = 'Adrien')
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UPDATE User [5] {name='bob'} TO (name = 'Bob')
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```
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Note that compared to `ADD`, you don't need to specify all member between `()`. Only the one specify will be updated.
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### Not yet implemented
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#### Not yet implemented
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A lot of things are not yet implemented, you can find examples in the [ZiQL Introduction](https://github.com/MrBounty/ZipponDB/blob/main/ZiQL.md).
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You can use operations on itself too when updating:
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```js
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UPDATE User {name = 'Bob'} TO (age += 1)
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```
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You can also manipulate array, like adding or removing values.
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```js
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UPDATE User {name='Bob'} TO (scores APPEND 45)
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UPDATE User {name='Bob'} TO (scores REMOVEAT [0 1 2])
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```
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For now there is 4 keywords to manipulate list:
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- `APPEND`: Add value at the end of the list.
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- `REMOVE`: Check the list and if the same value is found, delete it.
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- `REMOVEAT`: Delete the value at a specific index.
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- `CLEAR`: Remove all value in the array.
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Except `CLEAR` that take no value, each can use one value or an array of value, if chose an array it will perform the operation on all value in the array.
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For relationship, you can use filter on it:
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```js
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UPDATE User {name='Bob'} TO (comments APPEND {id = '000'})
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UPDATE User {name='Bob'} TO (comments REMOVE { at < '2023/12/31'})
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```
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I may include more options later.
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This include:
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- Relationship
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- Ordering
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- Batch
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- Array manipulation
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- And more...
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## Link query - Not yet implemented
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@ -314,11 +163,15 @@ All data type can be an array of those type using [] in front of it. So []int is
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All data type can also be `null`. Expect array that can only be empty.
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# Lexique
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# Why I created it ?
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- **Struct:** A struct of how to store data. E.g. `User`
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- **Entity:** An entity is one instance of a struct.
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- **Member:** A member is one data saved in a struct. E.g. `name` in `User`
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Well the first reason is to learn, both zig and databases.
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The second is to use it in my apps. I like to deploy Golang + HTMX app on Fly.io but I often find myself struggelling to get a simple database.
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I can either host it myself but I need to link my app and the db securely. Or use a cloud db service but that mean my db is far from my app.
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All I want is to give to a Fly machine 10go of storage, do some backup on it and call it a day. But for that I need to include it to the Dockerfile of my app, what easier way than just a binary ?
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So that my goal long term, to use it in my apps as a simple database that live WITH the app, sharing CPU and memory.
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# How does it work ?
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@ -326,19 +179,21 @@ TODO: Create a tech doc of what is happening inside.
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# Roadmap
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***Note: This will probably evolve over time.***
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#### v0.1 - Base
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- [X] UUID
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- [X] CLI
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- [X] Tokenizers
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- [ ] ZiQL parser
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- [ ] Schema engine
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- [X] ZiQL parser
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- [X] Schema engine
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- [X] File engine
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#### v0.2 - Usable
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- [ ] B+Tree
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- [ ] Relationships
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- [ ] Date
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- [ ] Link query
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- [ ] Linked query
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- [ ] Docker
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#### v0.3 - QoL
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@ -346,9 +201,11 @@ TODO: Create a tech doc of what is happening inside.
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- [ ] Dump/Bump data
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- [ ] Recovery
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- [ ] Better CLI
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- [ ] Logs
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#### v0.4 - Usability
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- [ ] Server
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- [ ] Config file
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- [ ] Python interface
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- [ ] Go interface
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@ -360,6 +217,7 @@ TODO: Create a tech doc of what is happening inside.
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- [ ] Transaction
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- [ ] Multi threading
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- [ ] Lock manager
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- [ ] Optimized data file
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#### v0.7 - Safety
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- [ ] Auth
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252
ZiQL.md
Normal file
252
ZiQL.md
Normal file
@ -0,0 +1,252 @@
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# ZipponQL
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ZipponDB use it's own query language, ZipponQL or ZiQL for short. Here the keys point to remember:
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- 4 actions available: `GRAB` `ADD` `UPDATE` `DELETE`
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- All query start with an action then a struct name
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- `{}` Are filters
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- `[]` Are how much; what data
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- `()` Are new or updated data (Not already in file)
|
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- `||` Are additional options
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- By default all member that are not link are return
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- To return link or only some members, specify them between `[]`
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***Disclaimer: Lot of stuff are still missing and the language may change over time.***
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# Making erros
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When you do an error writting ZiQL, you should see something like this to help you understand where you did a mistake:
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```
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Error: Expected string
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GRAB User {name = Bob}
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^^^
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```
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```
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Error: Expected ( or member name.
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GRAB User {name = 'Bob' AND {age > 10}}
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^
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```
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# Examples
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## GRAB
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The main action is `GRAB`, this will parse files and return data.
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Here how to return all `User` without any filtering:
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```js
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GRAB User
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```
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To get all `User` above 18 years old:
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```js
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GRAB User {age > 18}
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```
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To only return the name of `User`:
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```js
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GRAB User [name] {age > 18}
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```
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To return the 10 first `User`:
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```js
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GRAB User [10] {age > 18}
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```
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You can use both:
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```js
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GRAB User [10; name] {age > 18}
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```
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Use multiple condition:
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```js
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GRAB User {name = 'Bob' AND (age > 30 OR age < 10)}
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```
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GRAB query return a list of JSON with the data inside, e.g:
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```
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[{id:"1e170a80-84c9-429a-be25-ab4657894653", name: "Gwendolyn Ray", age: 70, email: "austin92@example.org", scores: [ 77 ], friends: [], }, ]
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```
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#### Not yet implemented
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To order it using the name:
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```js
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GRAB User [10; name] {age > 10} |ASC name|
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```
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You can specify how much and what to return even for link inside struct. In this example I get 1 friend name for 10 `User`:
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```js
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GRAB User [10; friends [1; name]]
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```
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|
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##### Using IN
|
||||
You can use the `IN` operator to check if something is in an array:
|
||||
```js
|
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GRAB User { age > 10 AND name IN ['Adrien' 'Bob']}
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```
|
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|
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This also work by using other filter. Here I get `User` that have a best friend named Adrien:
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```js
|
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GRAB User { bestfriend IN { name = 'Adrien' } }
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```
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When using an array with IN, it will return all `User` that have at least ONE friend named Adrien:
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```js
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GRAB User { friends IN { name = 'Adrien' } }
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```
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To get `User` with ALL friends named Adrien:
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```js
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GRAB User { friends ALLIN { name = 'Adrien' } }
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```
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You can use `IN` on itself. Here I get all `User` that liked a `Comment` that is from 2024. Both queries return the same thing:
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```js
|
||||
GRAB User { IN Comment {at > '2024/01/01'}.like_by}
|
||||
GRAB Comment.like_by { at > '2024/01/01'}
|
||||
```
|
||||
|
||||
You can optain a similar result with this query but it will return a list of `Comment` with a member `liked_by` that is similar to `User` above. If you take all `liked_by` inside all `Comment`, it will be the same list but you can end up with duplicate as one `User` can like multiple `Comment`.
|
||||
```js
|
||||
GRAB Comment [liked_by] {at > '2024/01/01'}
|
||||
```
|
||||
|
||||
##### Return relationship
|
||||
|
||||
You can also return a relationship only. The filter will be done on `User` but will return `Comment`:
|
||||
```js
|
||||
GRAB User.comments {name = 'Bob'}
|
||||
```
|
||||
|
||||
You can do it as much as you like. This will return all `User` that liked comments from Bob:
|
||||
```js
|
||||
GRAB User.comments.like_by {name = 'Bob'}
|
||||
```
|
||||
|
||||
This can also be use inside filter. Note that we need to specify `User` because it is a different struct that `Post`. Here I get all `Post` that have a comment from Bob:
|
||||
```js
|
||||
GRAB Post {comments IN User{name = 'Bob'}.comments}
|
||||
```
|
||||
|
||||
Can also do the same but only for the first Bob found:
|
||||
```js
|
||||
GRAB Post {comments IN User [1] {name = 'Bob'}.comments}
|
||||
```
|
||||
|
||||
Be carefull, this will return all `User` that liked a comment from 10 `User` named Bob:
|
||||
```js
|
||||
GRAB User.comments.like_by [10] {name = 'Bob'}
|
||||
```
|
||||
|
||||
To get 10 `User` that liked a comment from any `User` named Bob, you need to use:
|
||||
```js
|
||||
GRAB User.comments.like_by [comments [like_by [10]]] {name = 'Bob'}
|
||||
```
|
||||
|
||||
##### Using !
|
||||
You can use `!` to return the opposite. Use with `IN`, it check if it is NOT is the list. Use it with filters, it return entities that do not respect the filter.
|
||||
|
||||
This will return all `User` that didn't like a `Comment` in 2024:
|
||||
```js
|
||||
GRAB User { !IN Comment {at > '2024/01/01'}.like_by}
|
||||
```
|
||||
|
||||
Be carefull because this do not return the same, it return all `User` that liked a `Comment` not in 2024:
|
||||
```js
|
||||
GRAB Comment.like_by !{ at > '2024/01/01'}
|
||||
```
|
||||
|
||||
Which is the same as:
|
||||
```js
|
||||
GRAB Comment.like_by { at < '2024/01/01'}
|
||||
```
|
||||
|
||||
## ADD
|
||||
|
||||
The `ADD` action will add one entity into the database.
|
||||
The synthax is similare but use `()`, this mean that the data is not yet in the database.
|
||||
|
||||
Here an example:
|
||||
```js
|
||||
ADD User (name = 'Bob', age = 30, email = 'bob@email.com', scores = [1 100 44 82])
|
||||
```
|
||||
|
||||
You need to specify all member when adding an entity (default value are comming).
|
||||
|
||||
#### Not yet implemented
|
||||
|
||||
ADD query return a list ids added, e.g:
|
||||
```
|
||||
["1e170a80-84c9-429a-be25-ab4657894653", "1e170a80-84c9-429a-be25-ab4657894654", ]
|
||||
```
|
||||
|
||||
And you can also add them in batch
|
||||
```js
|
||||
ADD User (name = 'Bob', age = 30, email = 'bob@email.com', scores = [1 100 44 82]) (name = 'Bob2', age = 33, email = 'bob2@email.com', scores = [])
|
||||
```
|
||||
|
||||
You don't need to specify the member in the second entity as long as the order is respected.
|
||||
```js
|
||||
ADD User (name = 'Bob', age = 30, email = 'bob@email.com', scores = [1 100 44 82]) ('Bob2', 33, 'bob2@email.com', [])
|
||||
```
|
||||
|
||||
## DELETE
|
||||
|
||||
Similare to `GRAB` but delete all entity found using the filter and return the list of UUID deleted.
|
||||
```js
|
||||
DELETE User {name = 'Bob'}
|
||||
```
|
||||
|
||||
#### Not yet implemented
|
||||
|
||||
DELETE query return a list ids deleted, e.g:
|
||||
```
|
||||
["1e170a80-84c9-429a-be25-ab4657894653", "1e170a80-84c9-429a-be25-ab4657894654", ]
|
||||
```
|
||||
|
||||
## UPDATE
|
||||
|
||||
A mix of `GRAB` and `ADD`. This take a filter first, then the new data.
|
||||
Here we update the 5 first User named `adrien` to add a capital and become `Adrien`.
|
||||
```js
|
||||
UPDATE User [5] {name='adrien'} TO (name = 'Adrien')
|
||||
```
|
||||
|
||||
Note that compared to `ADD`, you don't need to specify all member between `()`. Only the one specify will be updated.
|
||||
|
||||
#### Not yet implemented
|
||||
|
||||
UPDATE query return a list ids updated, e.g:
|
||||
```
|
||||
["1e170a80-84c9-429a-be25-ab4657894653", "1e170a80-84c9-429a-be25-ab4657894654", ]
|
||||
```
|
||||
|
||||
You can use operations on itself too when updating:
|
||||
```js
|
||||
UPDATE User {name = 'Bob'} TO (age += 1)
|
||||
```
|
||||
|
||||
You can also manipulate array, like adding or removing values.
|
||||
```js
|
||||
UPDATE User {name='Bob'} TO (scores APPEND 45)
|
||||
UPDATE User {name='Bob'} TO (scores APPEND [45 99])
|
||||
UPDATE User {name='Bob'} TO (scores REMOVEAT [0 1 2])
|
||||
```
|
||||
|
||||
For now there is 4 keywords to manipulate list:
|
||||
- `APPEND`: Add value at the end of the list.
|
||||
- `REMOVE`: Check the list and if the same value is found, delete it.
|
||||
- `REMOVEAT`: Delete the value at a specific index.
|
||||
- `CLEAR`: Remove all value in the array.
|
||||
|
||||
Except `CLEAR` that take no value, each can use one value or an array of value, if chose an array it will perform the operation on all value in the array.
|
||||
|
||||
For relationship, you can use filter on it:
|
||||
```js
|
||||
UPDATE User {name='Bob'} TO (comments APPEND {id = '000'})
|
||||
UPDATE User {name='Bob'} TO (comments REMOVE { at < '2023/12/31'})
|
||||
```
|
||||
|
||||
I may include more options later.
|
||||
@ -3,7 +3,7 @@ const std = @import("std");
|
||||
pub fn build(b: *std.Build) void {
|
||||
// Build part
|
||||
const target = b.standardTargetOptions(.{});
|
||||
const optimize = b.standardOptimizeOption(.{});
|
||||
const optimize = b.standardOptimizeOption(.{ .preferred_optimize_mode = .ReleaseFast });
|
||||
const exe = b.addExecutable(.{
|
||||
.name = "zippon",
|
||||
.root_source_file = b.path("src/cli.zig"),
|
||||
|
||||
@ -3,5 +3,5 @@ User (
|
||||
age: int,
|
||||
email: str,
|
||||
scores: []int,
|
||||
friends: []bool,
|
||||
friends: []str,
|
||||
)
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user