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Minor improvements on the text of the README file

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Vinícius Garcia 2022-02-22 22:40:37 -03:00
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@ -81,29 +81,30 @@ but work on different databases, they are:
> Note: If you want numbers see our [Benchmark section](https://github.com/vingarcia/ksql#benchmark-comparison) below
ksql is meant to improve on the existing ecosystem by optimizing
for the most interesting use-cases with as little extra baggage
possible, offering among other things:
ksql is meant to improve on the existing ecosystem by providing
a well-designed database package that has:
- An easier time setting up and learning it
1. A small number of easy-to-use helper functions for common use cases
2. Support for more complicated use-cases by allowing
the user to write SQL directly
This strategy allows the API to be
- Very simple with a small number of functions
- Harness all the power of SQL, by just allowing the user to type SQL
- Less opportunities for making mistakes, which makes code reviews easier
- A succinct and idiomatic Go idiom reducing the cognitive
complexity of your code
- Easy ways of mocking your database when you need to.
- Support for all common databases
- No DSL: Use SQL for your queries
- A succinct and idiomatic Go idiom reducing the cognitive complexity of your code
- Easy ways of mocking your database when you need to
- Support for all common relational database: `mysql`, `sqlite`, `sqlserver` and `postgres`
And for a few important use-cases that cannot follow these rules perfectly,
we have carefully chosen a few powerful abstractions that might be
slightly more complicated to learn, such as:
Some special use-cases also have some special support:
- The `QueryChunks()` function which is necessary for the few
situations when you might load big amounts of the data in a
single query.
- And the possibility of omitting the `SELECT ...` part of the
query which causes ksql to write this part for you saving a
lot of work when working with big structs/tables.
- Support for nesting structs when working with JOINs.
- The `QueryChunks()` method helps you in the few situations when you might
need to load in a single query more data than would fit in memory.
- For saving you time when you are selecting all fields from a struct you
can omit the `SELECT ...` part of the query which causes ksql to write
this part for you saving a lot of work when working with big structs/tables.
- The Nested Structs feature will help you reuse existing structs/models when working with JOINs.
**Supported Drivers:**
@ -576,10 +577,10 @@ that we actually care about, so it's better not to use composite structs.
This library has a few helper functions for helping your tests:
- `kstructs.FillStructWith(struct interface{}, dbRow map[string]interface{}) error`
- `kstructs.FillSliceWith(structSlice interface{}, dbRows []map[string]interface{}) error`
- `kstructs.StructToMap(struct interface{}) (map[string]interface{}, error)`
- `kstructs.CallFunctionWithRows(fn interface{}, rows []map[string]interface{}) (map[string]interface{}, error)`
- `ksqltest.FillStructWith(struct interface{}, dbRow map[string]interface{}) error`
- `ksqltest.FillSliceWith(structSlice interface{}, dbRows []map[string]interface{}) error`
- `ksqltest.StructToMap(struct interface{}) (map[string]interface{}, error)`
- `ksqltest.CallFunctionWithRows(fn interface{}, rows []map[string]interface{}) (map[string]interface{}, error)`
If you want to see examples (we have examples for all the public functions) just
read the example tests available on our [example service](./examples/example_service)
@ -692,7 +693,7 @@ is configured to kill the containers after 20 seconds.
- Add tests for tables using composite keys
- Add support for serializing structs as other formats such as YAML
- Update `kstructs.FillStructWith` to work with `ksql:"..,json"` tagged attributes
- Update `ksqltest.FillStructWith` to work with `ksql:"..,json"` tagged attributes
- Create a way for users to submit user defined dialects
- Improve error messages
- Add support for the update function to work with maps for partial updates