I have some trouble building a function that can dynamically use parametrized structs. For that reason my code has 20+ functions that are similar except basically for one type that gets used. Most of my experience is with Java, and I'd just develop basic generic functions, or use plain Object as parameter to function (and reflection from that point on). I would need something similar, using Go.
I have several types like:
// The List structs are mostly needed for json marshalling
type OrangeList struct {
Oranges []Orange
}
type BananaList struct {
Bananas []Banana
}
type Orange struct {
Orange_id string
Field_1 int
// The fields are different for different types, I am simplifying the code example
}
type Banana struct {
Banana_id string
Field_1 int
// The fields are different for different types, I am simplifying the code example
}
Then I have function, basically for each list type:
// In the end there are 20+ of these, the only difference is basically in two types!
// This is very un-DRY!
func buildOranges(rows *sqlx.Rows) ([]byte, error) {
oranges := OrangeList{} // This type changes
for rows.Next() {
orange := Orange{} // This type changes
err := rows.StructScan(&orange) // This can handle each case already, could also use reflect myself too
checkError(err, "rows.Scan")
oranges.Oranges = append(oranges.Oranges,orange)
}
checkError(rows.Err(), "rows.Err")
jsontext, err := json.Marshal(oranges)
return jsontext, err
}
Yes, I could change the sql library to use more intelligent ORM or framework, but that's besides the point. I want to learn on how to build generic function that can handle similar function for all my different types.
I got this far, but it still doesn't work properly (target isn't expected struct I think):
func buildWhatever(rows *sqlx.Rows, tgt interface{}) ([]byte, error) {
tgtValueOf := reflect.ValueOf(tgt)
tgtType := tgtValueOf.Type()
targets := reflect.SliceOf(tgtValueOf.Type())
for rows.Next() {
target := reflect.New(tgtType)
err := rows.StructScan(&target) // At this stage target still isn't 1:1 smilar struct so the StructScan fails... It's some perverted "Value" object instead. Meh.
// Removed appending to the list because the solutions for that would be similar
checkError(err, "rows.Scan")
}
checkError(rows.Err(), "rows.Err")
jsontext, err := json.Marshal(targets)
return jsontext, err
}
So umm, I would need to give the list type, and the vanilla type as parameters, then build one of each, and the rest of my logic would be probably fixable quite easily.
Turns out there's an sqlx.StructScan(rows, &destSlice) function that will do your inner loop, given a slice of the appropriate type. The sqlx docs refer to caching results of reflection operations, so it may have some additional optimizations compared to writing one.
Sounds like the immediate question you're actually asking is "how do I get something out of my reflect.Value that rows.StructScan will accept?" And the direct answer is reflect.Interface(target); it should return an interface{} representing an *Orange you can pass directly to StructScan (no additional & operation needed). Then, I think targets = reflect.Append(targets, target.Indirect()) will turn your target into a reflect.Value representing an Orange and append it to the slice. targets.Interface() should get you an interface{} representing an []Orange that json.Marshal understands. I say all these 'should's and 'I think's because I haven't tried that route.
Reflection, in general, is verbose and slow. Sometimes it's the best or only way to get something done, but it's often worth looking for a way to get your task done without it when you can.
So, if it works in your app, you can also convert Rows straight to JSON, without going through intermediate structs. Here's a sample program (requires sqlite3 of course) that turns sql.Rows into map[string]string and then into JSON. (Note it doesn't try to handle NULL, represent numbers as JSON numbers, or generally handle anything that won't fit in a map[string]string.)
package main
import (
_ "code.google.com/p/go-sqlite/go1/sqlite3"
"database/sql"
"encoding/json"
"os"
)
func main() {
db, err := sql.Open("sqlite3", "foo")
if err != nil {
panic(err)
}
tryQuery := func(query string, args ...interface{}) *sql.Rows {
rows, err := db.Query(query, args...)
if err != nil {
panic(err)
}
return rows
}
tryQuery("drop table if exists t")
tryQuery("create table t(i integer, j integer)")
tryQuery("insert into t values(?, ?)", 1, 2)
tryQuery("insert into t values(?, ?)", 3, 1)
// now query and serialize
rows := tryQuery("select * from t")
names, err := rows.Columns()
if err != nil {
panic(err)
}
// vals stores the values from one row
vals := make([]interface{}, 0, len(names))
for _, _ = range names {
vals = append(vals, new(string))
}
// rowMaps stores all rows
rowMaps := make([]map[string]string, 0)
for rows.Next() {
rows.Scan(vals...)
// now make value list into name=>value map
currRow := make(map[string]string)
for i, name := range names {
currRow[name] = *(vals[i].(*string))
}
// accumulating rowMaps is the easy way out
rowMaps = append(rowMaps, currRow)
}
json, err := json.Marshal(rowMaps)
if err != nil {
panic(err)
}
os.Stdout.Write(json)
}
In theory, you could build this to do fewer allocations by not reusing the same rowMap each time and using a json.Encoder to append each row's JSON to a buffer. You could go a step further and not use a rowMap at all, just the lists of names and values. I should say I haven't compared the speed against a reflect-based approach, though I know reflect is slow enough it might be worth comparing them if you can put up with either strategy.