As of v0.520.0, adding -sql mariadb to the usual go generate annoation, e.g.
//go:generate greenpack -sql mariadb
will cause greenpack to generate methods
for writing to, and reading from, MariaDB.
See https://github.com/glycerine/greenpack/blob/master/testdata/_sqldemo_gen.go
for an example of the generated code.
-
I compare greenpack to CBOR here: https://github.com/glycerine/demo_cbor Long story short: CBOR is 3-4x slower than greenpack, and comes in too many flavors.
-
I wrote an RPC system with modern cryptography and greenpack for serialization. Its pretty nice. https://github.com/glycerine/rpc25519 performs better than the other systems measured. It has better latency and throughput -- even when encrypted -- than gRPC and rpcx.
Since the versioning tags here were created long before Go modules were invented, it turns out the schemes were not compatible. Greenpack was at v5 but the import path is never going to have /v5 at the end, so... we'll try renaming the tags to v0.xxx.0 style tags, and see what happens.
There is also https://github.com/glycerine/greenpack2 which I know works (it is simply a clone with renamed tags and a new module path) because it has never been published with a higher version before.
But I'm going to try to make the orignial greenpack (no 2) also work, because I import it in a ton of places.
Cool: it seems to work. The only thing is that the idea of the "@latest" go module isn't going to work, because Google's proxy remembers the old v5.1.2 version that never supported modules. Since the v5.1.2 will always look like the "latest" even though its been renamed to v0.512.0, you have to manually use the v0.xxx.0 versions. Ironically, they are actually the latest.
For reference purposes in case I need to go back to it, list.of.old.tags.txt list.of.rename.operations.txt document the old tags and how they were renamed (or many were deleted if not renamed).
The true latest as of this README is v0.515.0.
Version 5.0.9 includes native support for time.Duration serialization.
Version 5.0.4 includes two new features:
- a) interfaces are supported, and automatically detected
(Since the parser didn't used to distinguish interfaces from structs, manual annotation of interface types was required, using the msgp:",iface" tag. This has now been fixed. However the manual tagging of interfaces is still available for cases when you are using an inteface from another package whose source we haven't parsed.)
Required if using interfaces: your container must implement the ConcreteFactory interface; the method NewValueAsInterface. See the example/test https://github.com/glycerine/greenpack/blob/master/_generated/def.go#L341 and https://github.com/glycerine/greenpack/blob/master/_generated/def.go#L345 .
- b) de-duplication of pointers and interfaces allows serialization of repeated/shared pointers efficiently.
NB: de-duplication is only available for EncodeMsg / DecodeMsg based on a Writer/Reader stream. The MarshalMsg/UnmarshalMsg API doesn't have a place to store the deduplication state, so at the moment de-dup from a []byte isn't supported. This isn't a huge limitation as it is trivial to turn a []byte into a stream if need be. For example, use w := msgp.NewWriter(bytes.NewBuffer(by)) to get a writer that wraps the by []byte.
greenpack is a simple convention for naming fields in msgpack data: we take the
original field name and append a version number and basic type indicator.
- See also the fork/cousin project https://github.com/glycerine/truepack if you encode/decode naked ints (not inside a struct) and want type info preserved.
//given this definition, defined in Go:
type A struct {
Name string `zid:"0"`
Bday time.Time `zid:"1"`
Phone string `zid:"2"`
Sibs int `zid:"3"`
GPA float64 `zid:"4"`
Friend bool `zid:"5"`
}
then when greenpack serializes, the it looks like msgpack2 on the wire with extended field names:
greenpack
--------
a := A{
"Name_zid00_str" : "Atlanta",
"Bday_zid01_tim" : tm("1990-12-20"),
"Phone_zid02_str" : "650-555-1212",
"Sibs_zid03_i64" : 3,
"GPA_zid04_f64" : 3.95,
"Friend_zid05_boo": true,
}
Notice the only thing that changed with respect to the msgpack2 encoding is that the the fieldnames have been extended to contain a version and a type clue.
msgpack2 [https://github.com/msgpack/msgpack/blob/master/spec.md] [http://msgpack.org] enjoys wide cross-language support, and provides efficient and self-contained data serialization. We find only two problems with msgpack2: weak support for data evolution, and insufficiently strong typing of integers.
The greenpack format addresses these problems while keeping serialized data fully self-describing. Greenpack is independent of any external schema, but as an optimization uses the Go source file itself as a schema to maintain current versioning and type information. Dynamic languages still have an easy time reading greenpack--it is just msgpack2. There's no need to worry about locating the schema under which data was written, as data stays self-contained.
The central idea of greenpack: start with msgpack2, and append version numbers and type clues to the end of the field names when stored on the wire. We say type "clues" because the type information clarifies the original size and signed-ness of the type, which adds the missing detail to integers needed to fully reconstruct the original data from the serialization. This address the problem that commonly msgpack2 implementations ignore the spec and encode numbers using the smallest unsigned type possible, which corrupts the original type information and can induce decoding errors for large and negative numbers.
If you've ever had your msgpack crash your server because you tried to change the type of a field but keep the same name, then you know how fragile msgpack can be. The type clue fixes that.
The version zid number gives us the ability to evolve our data without crashes. The moniker zid reveals greenpacks evolution from zebrapack, where it stood for "zebrapack version id". Rather than rework all the tooling to expect gid, which might be confused with a GUID, we simply keep the convention. zid indicates the field version.
An additional advantage of the zid numbering is that it makes the serialization consistent and reproducible, since greenpack writes fields in zid order.
One last easy idea: use the Go language struct definition syntax as our serialization schema. There is no need to invent a completely different format. Serialization for Go developers should be almost trivially easy. While we are focused on a serialization format for Go, because other language can read msgpack2, they can also readily read the data. While the schema is optional, greenpack (this repo) provides code generation tools based on the schema (Go file) that generates extremely fast serialization code.
Starting point: msgpack2 is great. It is has an easy to read spec, it defines a compact serialization format, and it has wide language support from both dynamic and compiled languages.
Nonetheless, data update conflicts still happen and can be hard to resolve. Encoders could use the guidance from type clues to avoid signed versus unsigned integer encodings.
For instance, sadly the widely emulated C-encoder for msgpack chooses to encode signed positive integers as unsigned integers. This causes crashes in readers who were expected a signed integer, which they may have originated themselves in the original struct.
Astonishing, but true: the existing practice for msgpack2 language bindings allows the data types to change as they are read and re-serialized. Simple copying of a serialized struct can change the types of data from signed to unsigned. This is horrible. Now we have to guess whether an unsigned integer was really intended because of the integer's range, or if data will be silently truncated or lost when coercing a 64-bit integer to a 63-bit signed integer--assuming such coercing ever makes logical sense, which it may not.
This kind of tragedy happens because of a lack of shared communication across time and space between readers and writers. It is easily addressed with type clues, small extra information about the originally defined type.
-
Conflict resolution: the Cap'nProto numbering and update conflict resolution method is used here. This method originated in the ProtocolBuffers scheme, and was enhanced after experience in Cap'nProto. How it works: Additions are always made by incrementing by one the largest number available prior to the addition. No gaps in numbering are allowed, and no numbers are ever deleted. To get the effect of deletion, add the
deprecatedvalue inmsgtag. This is an effective tombstone. It allows the tools (thegocompiler and thegreenpackcode generator) to help detect merge conflicts as soon as possible. If two people try to merge schemas where the same struct or field number is re-used, then whengreenpackis run to regenerate the serialization code (undergo generate), it will automatically detect the conflict, and flag the human to resolve the conflict before proceeding. -
All fields optional. Just as in msgpack2, Cap'nProto, Gobs, and Flatbuffers, all fields are optional. Most everyone, after experience and time with ProtocolBuffers, has come to the conclusion that required fields are a misfeature that hurt the ability to evolve data gracefully and maintain efficiency.
Design:
-
Schema language: the schema language for defining structs is identical to the Go language. Go is expressive and yet easily parsed by the standard library packages included with Go itself.
-
Requirement: greenpack requires that the msgpack2 standard be adhered to. Strings and raw binary byte arrays are distinct, and must be marked distinctly; msgpack1 encoding is not allowed.
-
All language bindings must respect the declared type in the type clue when writing data. For example, this means that signed and unsigned declarations must be respected. Even if another language uses a msgpack2 implimentation that converts signed to unsigned, as long as the field name is preserved we can still acurately reconstruct what the data's type was originally.
greenpack -fast-strings is zero-allocation, and one
of the fastest serialization formats avaiable for Go.[1]
[1] https://github.com/glycerine/go_serialization_benchmarks
For write speed, only Zebrapack is faster. For
reads, only CapnProto and Gencode are slightly faster.
Gencode isn't zero alloc, and has no versioning support.
CapnProto isn't very portable to dynamic languages
like R or Javascript; Java support was never
finished. It requires keeping duplicate
mirror structs in your code. I like CapnProto and
maintained Go bindings for CapnProto for quite a
while. However the convenience of msgpack2 won
me over. Moreover CapnProto's layout format
is undocumented, it requires a C++ build chain to
build the IDL compiler, and unused fields always
take space on the wire. greenpack is pure Go,
and there are over 50 msgpack libraries -- one for every
language imaginable -- cited at http://msgpack.org.
Compared to (Gogoprotobuf) ProtcolBuffers, greenpack reads are 6% faster on these microbenchmarks. Writes are 15% faster and do no allocation; GogoprotobufMarshal appears to allocate on write.
to actually deprecate a field, you start by adding the ,deprecated value to the msg tag key:
type A struct {
Name string `zid:"0"`
Bday time.Time `zid:"1"`
Phone string `zid:"2"`
Sibs int `zid:"3"`
GPA float64 `zid:"4" msg:",deprecated"` // a deprecated field.
Friend bool `zid:"5"`
}
In addition, you'll want to change the type of the deprecated field, substituting struct{} for the old type. By converting the type of the deprecated field to struct{}, it will no longer takes up any space in the Go struct. This saves space. Even if a struct evolves heavily in time (rare), the changes will cause no extra overhead in terms of memory. It also allows the compiler to detect and reject any new writes to the field that are using the old type.
// best practice for deprecation of fields, to save space + get compiler support for deprecation
type A struct {
Name string `zid:"0"`
Bday time.Time `zid:"1"`
Phone string `zid:"2"`
Sibs int `zid:"3"`
GPA struct{} `zid:"4" msg:",deprecated"` // a deprecated field should have its type changed to struct{}, as well as being marked msg:",deprecated"
Friend bool `zid:"5"`
}
Rules for safe data changes: To preserve forwards/backwards compatible changes, you must never remove a field from a struct, once that field has been defined and used. In the example above, the zid:"4" tag must stay in place, to prevent someone else from ever using 4 again. This allows sane data forward evolution, without tears, fears, or crashing of servers. The fact that struct{} fields take up no space also means that there is no need to worry about loss of performance when deprecating. We retain all fields ever used for their zebra ids, and the compiled Go code wastes no extra space for the deprecated fields.
NB: There is one exception to this struct{} consumes no space rule: if the newly deprecated struct{} field happens to be the very last field in a struct, it will take up one pointer worth of space. If you want to deprecate the last field in a struct, if possible you should move it up in the field order (e.g. make it the first field in the Go struct), so it doesn't still consume space; reference golang/go#17450.
$ greenpack -h
Usage of greenpack:
-alltuple
use tuples for everything. Negates the point
of greenpack, but useful in a pinch for
performance. Provides no data versioning
whatsoever. If you even so much as change
the order of your fields, you won't be
able to read back your earlier data
correctly/without crashing.
-fast-strings
for speed when reading a string in
a message that won't be reused, this
flag means we'll use unsafe to cast
the string header and avoid allocation.
-file go generate
input file (or directory); default
is $GOFILE, which is set by the
go generate command.
-io
create Encode and Decode methods (default true)
-marshal
create Marshal and Unmarshal methods
(default true)
-method-prefix string
(optional) prefix that will be pre-prended
to the front of generated method names;
useful when you need to avoid namespace
collisions, but the generated tests will
break/the msgp package interfaces won't be satisfied.
-o string
output file (default is {input_file}_gen.go
-msgpack2 (alias for -omit-clue)
-omit-clue
don't append zid and clue to field name
(makes things just like msgpack2 traditional
encoding, without version + type clue)
-tests
create tests and benchmarks (default true)
-unexported
also process unexported types
-write-zeros
serialize zero-value fields to the wire,
consuming much more space. By default
all fields are treated as omitempty fields,
where they are omitted from the
serialization if they contain their zero-value.
If -write-zero is given, then only fields
specifically marked as `omitempty` are
treated as such.
By default, all fields are treated as omitempty. If the
field contains its zero-value (see the Go spec), then it
is not serialized on the wire.
If you wish to consume space unnecessarily, you can
use the greenpack -write-zeros flag. Then only
fields specifically marked with the struct tag
omitempty will be treated as such.
For example, in the following example,
type Hedgehog struct {
Furriness string `msg:",omitempty"`
}
If Furriness is the empty string, the field will not be serialized, thus saving the space of the field name on the wire. If the -write-zeros flags was given and the omitempty tag removed, then Furriness would be serialized no matter what value it contained.
It is safe to re-use structs by default, and with omitempty. For reference:
from tinylib/msgp#154:
The only special feature of UnmarshalMsg and DecodeMsg (from a zero-alloc standpoint) is that they will use pre-existing fields in an object rather than allocating new ones. So, if you decode into the same object repeatedly, things like slices and maps won't be re-allocated on each decode; instead, they will be re-sized appropriately. In other words, mutable fields are simply mutated in-place.
This continues to hold true, and a missing field on the wire will zero the field in any re-used struct.
NB: Under tuple encoding (https://github.com/tinylib/msgp/wiki/Preprocessor-Directives), for example //msgp:tuple Hedgehog, then all fields are always serialized and the omitempty tag is ignored.
The addzid utility (in the cmd/addzid subdir) can help you
get started. Running addzid mysource.go on a .go source file
will add the zid:"0"... fields automatically. This makes adding greenpack
serialization to existing Go projects easy.
See https://github.com/glycerine/greenpack/blob/master/cmd/addzid/README.md
for more detail.
-
my own internal projects
-
your project here
Portions Copyright (c) 2016, 2017 Jason E. Aten, Ph.D.
Portions Copyright (c) 2014 Philip Hofer
Portions Copyright (c) 2009 The Go Authors (license at http://golang.org) where indicated
LICENSE: MIT. See https://github.com/glycerine/greenpack/blob/master/LICENSE
greenpack gets most of its speed by descending from the
fantastic and highly tuned https://github.com/tinylib/msgp library by
Philip Hofer. The special tag and shim handling is best documented
in the msgp writeup and wiki [https://github.com/tinylib/msgp/wiki].
Advances in greenpack beyond msgp:
-
with
zidnumbering, serialization becomes consistent and reproducible, sincegreenpackwrites fields inzidorder. -
all fields are
omitemptyby default. If you don't use a field, you don't pay for it in serialization time. -
generated code is reproducible, so you don't get version control churn everytime you re-run the code generator (tinylib/msgp#185)
-
support for marking fields as deprecated
-
if you don't want the zid and type-clue appended to field names, the
-omit-clueoption means you can usegreenpackas just a better (omit empty by default) msgpack-only generator. -
the
-alltupleflag is convenient if you do alot of tuple-only work. -
the
-fast-stringsflag is a useful performance optimization when you need zero-allocation and you know you won't look at your message flow again (or when you do, you make a copy manually). -
the msgp.PostLoad and msgp.PreSave interfaces let you hook into the serialization process to write custom procedures to prepare your data structures for writing. For example, a tree frequently needs flattening before storage. On the read, the tree will need reconstrution right after loading. These interfaces are particularly helpful for nested structures, as they are invoked automatically if they are available.
(see prim2clue in https://github.com/glycerine/greenpack/blob/master/gen/elem.go#L112)
base types:
"bin" // []byte, a slice of bytes
"str" // string (not struct, which is "rct")
"f32" // float32
"f64" // float64
"c64" // complex64
"c28" // complex128
"unt" // uint (machine word size, like Go)
"u08" // uint8
"u16" // uint16
"u32" // uint32
"u64" // uint64
"byt" // byte
"int" // int (machine word size, like Go)
"i08" // int8
"i16" // int16
"i32" // int32
"i64" // int64
"boo" // bool
"ifc" // interface
"tim" // time.Time
"dur" // time.Duration
"ext" // msgpack extension
compound types:
"ary" // array
"map" // map
"slc" // slice
"ptr" // pointer
"rct" // struct
appendix B: from the original https://github.com/tinylib/msgp README
This is a code generation tool and serialization library for MessagePack. You can read more about MessagePack in the wiki, or at msgpack.org.
- Use Go as your schema language
- Performance
- JSON interop
- User-defined extensions
- Type safety
- Encoding flexibility
In a source file, include the following directive:
//go:generate greenpackThe greenpack command will generate serialization methods for all exported type declarations in the file. If you add the flag -msgp, it will generate msgpack2 rather than greenpack format.
For other language's use, schemas can can be written to a separate file using greenpack -file my.go -write-schema at the shell. (By default schemas are not written to the wire, just as in protobufs/CapnProto/Thrift.)
You can read more about the code generation options here.
Field names can be set in much the same way as the encoding/json package. For example:
type Person struct {
Name string `msg:"name"`
Address string `msg:"address"`
Age int `msg:"age"`
Hidden string `msg:"-"` // this field is ignored
unexported bool // this field is also ignored
}By default, the code generator will satisfy msgp.Sizer, msgp.Encodable, msgp.Decodable,
msgp.Marshaler, and msgp.Unmarshaler. Carefully-designed applications can use these methods to do
marshalling/unmarshalling with zero heap allocations.
While msgp.Marshaler and msgp.Unmarshaler are quite similar to the standard library's
json.Marshaler and json.Unmarshaler, msgp.Encodable and msgp.Decodable are useful for
stream serialization. (*msgp.Writer and *msgp.Reader are essentially protocol-aware versions
of *bufio.Writer and *bufio.Reader, respectively.)
- Extremely fast generated code
- Test and benchmark generation
- JSON interoperability (see
msgp.CopyToJSON() and msgp.UnmarshalAsJSON()) - Support for complex type declarations
- Native support for Go's
time.Time,complex64, andcomplex128types - Generation of both
[]byte-oriented andio.Reader/io.Writer-oriented methods - Support for arbitrary type system extensions
- Preprocessor directives
- File-based dependency model means fast codegen regardless of source tree size.
Consider the following:
const Eight = 8
type MyInt int
type Data []byte
type Struct struct {
Which map[string]*MyInt `msg:"which"`
Other Data `msg:"other"`
Nums [Eight]float64 `msg:"nums"`
}As long as the declarations of MyInt and Data are in the same file as Struct, the parser will determine that the type information for MyInt and Data can be passed into the definition of Struct before its methods are generated.
MessagePack supports defining your own types through "extensions," which are just a tuple of
the data "type" (int8) and the raw binary. You can see a worked example in the wiki.
Mostly stable, in that no breaking changes have been made to the /msgp library in more than a year. Newer versions
of the code may generate different code than older versions for performance reasons. I (@philhofer) am aware of a
number of stability-critical commercial applications that use this code with good results. But, caveat emptor.
You can read more about how msgp maps MessagePack types onto Go types in the wiki.
Here some of the known limitations/restrictions:
- Identifiers from outside the processed source file are assumed (optimistically) to satisfy the generator's interfaces. If this isn't the case, your code will fail to compile.
- Like most serializers,
chanandfuncfields are ignored, as well as non-exported fields. - Encoding of
interface{}is limited to built-ins or types that have explicit encoding methods.
If the output compiles, then there's a pretty good chance things are fine. (Plus, we generate tests for you.) Please, please, please file an issue if you think the generator is writing broken code.
If you like benchmarks, see here and above in the greenpack benchmarks section; see here for the benchmark source code.
As one might expect, the generated methods that deal with []byte are faster for small objects, but the io.Reader/Writer methods are generally more memory-efficient (and, at some point, faster) for large (> 2KB) objects.