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A high-performance Redis client for Flutter and Dart, designed for simplicity and efficiency. It enables seamless integration with Redis databases across multiple platforms, including Android, iOS, macOS, Windows, and Linux. The package provides a clean, intuitive API to interact with Redis, supporting common operations like key-value storage, pub/sub messaging, and atomic commands. Built with performance in mind, it's ideal for real-time applications requiring fast data access and low-latency operations.
Use cases
Real-time data caching
Message brokering with pub/sub
Session management
Rate limiting
High-speed data retrieval
Key features
Cross-platform support
Low-latency operations
Simple API design
Pub/Sub messaging
Atomic command execution
Suitable for
Real-time apps
High-traffic services
Caching layers
Backend integrations
Considerations
Requires a running Redis server
Limited to basic Redis commands
No built-in connection pooling
Not suitable for complex Redis modules
Network dependency for remote instances
Original README
Original README snapshot from the linked source repository. Visit the repository for the latest content.
Another way is to execute commands without waiting for the previous command to
complete, and we can still be sure that the response handled by Future will be
completed in the correct order.
Difference is that there are five commands in last examples
and only one in the previous example.
Generic
Redis responses and requests can be arbitrarily nested.
Mapping
Redis
Dart
String
String
Integer
Integer
Array
List
Error
RedisError
Bulk
String or Binary
* Both simple string and bulk string from Redis are serialized to Dart string.
Strings from Dart to Redis are converted to bulk string. UTF8 encoding is used
in both directions.
New feature since 3.0: Support for converting received data as [binary data](#Binary data).
Lists can be nested. This is useful when executing the EVAL command.
or by passing any other Socket to
RedisConnection.connectWithSocket(Socket s) in similar fashion.
Fast
Tested on a laptop, we can execute and process 180K INCR operations per second.
Example
constint N = 200000;
int start;
final conn = RedisConnection();
conn.connect('localhost',6379).then((Command command){
print("test started, please wait ...");
start = DateTime.now().millisecondsSinceEpoch;
command.pipe_start();
command.send_object(["SET","test","0"]);
for(int i=1;i<=N;i++){
command.send_object(["INCR","test"])
.then((v){
if(i != v)
throw("wrong received value, we got $v");
});
}
//last command will be executed and then processed last
command.send_object(["GET","test"]).then((v){
print(v);
double diff = (newDateTime.now().millisecondsSinceEpoch - start)/1000.0;
double perf = N/diff;
print("$N operations done in $diff s\nperformance $perf/s");
});
command.pipe_end();
});
We are not just sending 200K commands here, but also checking result of every send command.
Using command.pipe_start(); and command.pipe_end(); does nothing more
than enabling and disabling the Nagle's algorhitm on socket. By default it is disabled to achieve shortest
possible latency at the expense of more TCP packets and extra overhead. Enabling
Nagle's algorithm during transactions can achieve greater data throughput and
less overhead.
Transactions by redis protocol are started by MULTI command and completed with
EXEC command. .multi(), .exec() and class Transaction are implemented as
helpers for checking the result of each command executed during transaction.
Future<Transaction> Command.multi();
Executing multi() returns a Future<Transaction>. This class should be used
to execute commands by calling .send_object. It returns a Future that is
called after calling .exec().
import'package:redis/redis.dart';
...
final conn = RedisConnection();
conn.connect('localhost',6379).then((Command command){
command.multi().then((Transaction trans){
trans.send_object(["SET","val","0"]);
for(int i=0;i<200000;++i){
trans.send_object(["INCR","val"]).then((v){
assert(i==v);
});
}
trans.send_object(["GET","val"]).then((v){
print("number is now $v");
});
trans.exec();
});
});
It's impossible to write code that depends on the result of the previous command
during a transaction, because all commands are executed at once. To overcome
this, user should use the CAS.
Cas requires a Command as a constructor argument. It implements two methods:
watch and multiAndExec.
watch takes two arguments: a list of keys to watch and a handler to call and
to proceed with CAS.
Example:
cas.watch(["key1,key2,key3"],(){
//body of CAS
});
Failure happens if the watched key is modified outside of the transaction. When
this happens the handler is called until final transaction completes.
multiAndExec is used to complete a transaction with a handler where
the argument is Transaction.
Example:
//last part in body of CAS
cas.multiAndExec((Transaction trans){
trans.send_object(["SET","key1",v1]);
trans.send_object(["SET","key2",v2]);
trans.send_object(["SET","key2",v2]);
});
Lets imagine we need to atomically increment the value of a key by 1 (and that
Redis does not have the INCR command).
Cas cas = newCas(command);
cas.watch(["key"], (){
command.send_object(["GET","key"]).then((String val){
int i = int.parse(val);
i++;
cas.multiAndExec((Transaction trans){
trans.send_object(["SET","key",i.toString()]);
});
});
});
Unicode
By default UTF8 encoding/decoding for string is used. Each string is converted
in binary array using UTF8 encoding. This makes ascii string compatible in both
direction.
Binary data
Default conversion response from Redis of Bulk data is converted to utf-8 string.
In case when binary interpretation is needed, there is option to request such parsing.
final conn = RedisConnection();
Command cmd = await conn.connect('localhost',6379);
Command cmd_bin = Command.from(cmd).setParser(RedisParserBulkBinary());
List<int> d = [1,2,3,4,5,6,7,8,9];
// send binaryawait cmd_bin.send_object(["SET", key, RedisBulk(d)]);
// receive binary from binary command handlervar r = await cmd_bin.send_object(["GET", key])
// r is now same as d