1599530182
When I first stepped into the web development world, git and GitHub were the things that I went to learn after so long. I always used to avoid it in my learning phase. But when I got used to it, it was really helpful.
GitHub is not just a version control. There is so much more great stuff for you to discover. And in this story, I will be talking of 3 GitHub repositories that I think you must know as a developer. These repositories helped me become a better developer. And I believe they will be of value to you too.
Readers are leaders, even in the programming world. Reading books allow you to get introduced to a concept in an unbiased and complete manner and you can pick what you need.
Courses are great. But if you want a reason why books are better, it is because most of the time when we see a tutorial, we see someone coding or an actual person telling us how to do things. This can trick your brain as if the job is done because you have seen someone coding, and you realize you can do it too. But in reality, you do not do it. You do not write the actual code. This is a big problem.
Books allow us to test our knowledge and understanding of a subject and apply it to a real machine. you are compelled to write the actual code if you want to see the results in action. This repository has over 157k stars.
Check it here
APIs allow applications to communicate with each other. They facilitate the development processes by providing functionalities you need for your project.
This GitHub repository is a collection of free APIs available to use in the software and web development world. APIs are lifesavers. And every developer needs them. No matter what niche you are programming for, an API can solve your problem with much less effort and in much less time. So this repository is for you. It has over 94.5k start
Check it here
JavaScript is not what it used to be when it first came out. It is so much better. It is the language that powers the web. Hence it makes sense that there is so much new to learn. A front-end developer cannot survive without a good understanding of JavaScript.
JavaScript is one of the essential things you need to have in your skillset to become good and earn a decent amount. I have seen people doing astonishing stuff with just vanilla JavaScript. And you can do it too. But you need a solid foundation and good understanding.
This GitHub repository is a series of books diving deep into JavaScript. It is a valuable resource for both new and experienced developers. It has well over 127k stars.
Everyone cannot afford to buy courses that cost an arm and a leg. So we need good, free resources. I believe all these GitHub repositories will help you as a developer. Feel free to share what you think is a must-know repository.
Thank you for reading!
#software-development #coding #javascript #web-development #programming
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naveen
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Thanks!
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Nice Post
Mobile App Development Company
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niceeee! thank
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Awesome
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I love GitHub articles. Thx!
Hey, developers, what do think about my most popular post? Read here:
Best Databases to Use for React Native Mobile App Development
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Thanks so much.
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1653475560
msgpack.php
A pure PHP implementation of the MessagePack serialization format.
The recommended way to install the library is through Composer:
composer require rybakit/msgpack
To pack values you can either use an instance of a Packer
:
$packer = new Packer();
$packed = $packer->pack($value);
or call a static method on the MessagePack
class:
$packed = MessagePack::pack($value);
In the examples above, the method pack
automatically packs a value depending on its type. However, not all PHP types can be uniquely translated to MessagePack types. For example, the MessagePack format defines map
and array
types, which are represented by a single array
type in PHP. By default, the packer will pack a PHP array as a MessagePack array if it has sequential numeric keys, starting from 0
and as a MessagePack map otherwise:
$mpArr1 = $packer->pack([1, 2]); // MP array [1, 2]
$mpArr2 = $packer->pack([0 => 1, 1 => 2]); // MP array [1, 2]
$mpMap1 = $packer->pack([0 => 1, 2 => 3]); // MP map {0: 1, 2: 3}
$mpMap2 = $packer->pack([1 => 2, 2 => 3]); // MP map {1: 2, 2: 3}
$mpMap3 = $packer->pack(['a' => 1, 'b' => 2]); // MP map {a: 1, b: 2}
However, sometimes you need to pack a sequential array as a MessagePack map. To do this, use the packMap
method:
$mpMap = $packer->packMap([1, 2]); // {0: 1, 1: 2}
Here is a list of type-specific packing methods:
$packer->packNil(); // MP nil
$packer->packBool(true); // MP bool
$packer->packInt(42); // MP int
$packer->packFloat(M_PI); // MP float (32 or 64)
$packer->packFloat32(M_PI); // MP float 32
$packer->packFloat64(M_PI); // MP float 64
$packer->packStr('foo'); // MP str
$packer->packBin("\x80"); // MP bin
$packer->packArray([1, 2]); // MP array
$packer->packMap(['a' => 1]); // MP map
$packer->packExt(1, "\xaa"); // MP ext
Check the "Custom types" section below on how to pack custom types.
The Packer
object supports a number of bitmask-based options for fine-tuning the packing process (defaults are in bold):
Name | Description |
---|---|
FORCE_STR | Forces PHP strings to be packed as MessagePack UTF-8 strings |
FORCE_BIN | Forces PHP strings to be packed as MessagePack binary data |
DETECT_STR_BIN | Detects MessagePack str/bin type automatically |
FORCE_ARR | Forces PHP arrays to be packed as MessagePack arrays |
FORCE_MAP | Forces PHP arrays to be packed as MessagePack maps |
DETECT_ARR_MAP | Detects MessagePack array/map type automatically |
FORCE_FLOAT32 | Forces PHP floats to be packed as 32-bits MessagePack floats |
FORCE_FLOAT64 | Forces PHP floats to be packed as 64-bits MessagePack floats |
The type detection mode (
DETECT_STR_BIN
/DETECT_ARR_MAP
) adds some overhead which can be noticed when you pack large (16- and 32-bit) arrays or strings. However, if you know the value type in advance (for example, you only work with UTF-8 strings or/and associative arrays), you can eliminate this overhead by forcing the packer to use the appropriate type, which will save it from running the auto-detection routine. Another option is to explicitly specify the value type. The library provides 2 auxiliary classes for this,Map
andBin
. Check the "Custom types" section below for details.
Examples:
// detect str/bin type and pack PHP 64-bit floats (doubles) to MP 32-bit floats
$packer = new Packer(PackOptions::DETECT_STR_BIN | PackOptions::FORCE_FLOAT32);
// these will throw MessagePack\Exception\InvalidOptionException
$packer = new Packer(PackOptions::FORCE_STR | PackOptions::FORCE_BIN);
$packer = new Packer(PackOptions::FORCE_FLOAT32 | PackOptions::FORCE_FLOAT64);
To unpack data you can either use an instance of a BufferUnpacker
:
$unpacker = new BufferUnpacker();
$unpacker->reset($packed);
$value = $unpacker->unpack();
or call a static method on the MessagePack
class:
$value = MessagePack::unpack($packed);
If the packed data is received in chunks (e.g. when reading from a stream), use the tryUnpack
method, which attempts to unpack data and returns an array of unpacked messages (if any) instead of throwing an InsufficientDataException
:
while ($chunk = ...) {
$unpacker->append($chunk);
if ($messages = $unpacker->tryUnpack()) {
return $messages;
}
}
If you want to unpack from a specific position in a buffer, use seek
:
$unpacker->seek(42); // set position equal to 42 bytes
$unpacker->seek(-8); // set position to 8 bytes before the end of the buffer
To skip bytes from the current position, use skip
:
$unpacker->skip(10); // set position to 10 bytes ahead of the current position
To get the number of remaining (unread) bytes in the buffer:
$unreadBytesCount = $unpacker->getRemainingCount();
To check whether the buffer has unread data:
$hasUnreadBytes = $unpacker->hasRemaining();
If needed, you can remove already read data from the buffer by calling:
$releasedBytesCount = $unpacker->release();
With the read
method you can read raw (packed) data:
$packedData = $unpacker->read(2); // read 2 bytes
Besides the above methods BufferUnpacker
provides type-specific unpacking methods, namely:
$unpacker->unpackNil(); // PHP null
$unpacker->unpackBool(); // PHP bool
$unpacker->unpackInt(); // PHP int
$unpacker->unpackFloat(); // PHP float
$unpacker->unpackStr(); // PHP UTF-8 string
$unpacker->unpackBin(); // PHP binary string
$unpacker->unpackArray(); // PHP sequential array
$unpacker->unpackMap(); // PHP associative array
$unpacker->unpackExt(); // PHP MessagePack\Type\Ext object
The BufferUnpacker
object supports a number of bitmask-based options for fine-tuning the unpacking process (defaults are in bold):
Name | Description |
---|---|
BIGINT_AS_STR | Converts overflowed integers to strings [1] |
BIGINT_AS_GMP | Converts overflowed integers to GMP objects [2] |
BIGINT_AS_DEC | Converts overflowed integers to Decimal\Decimal objects [3] |
1. The binary MessagePack format has unsigned 64-bit as its largest integer data type, but PHP does not support such integers, which means that an overflow can occur during unpacking.
2. Make sure the GMP extension is enabled.
3. Make sure the Decimal extension is enabled.
Examples:
$packedUint64 = "\xcf"."\xff\xff\xff\xff"."\xff\xff\xff\xff";
$unpacker = new BufferUnpacker($packedUint64);
var_dump($unpacker->unpack()); // string(20) "18446744073709551615"
$unpacker = new BufferUnpacker($packedUint64, UnpackOptions::BIGINT_AS_GMP);
var_dump($unpacker->unpack()); // object(GMP) {...}
$unpacker = new BufferUnpacker($packedUint64, UnpackOptions::BIGINT_AS_DEC);
var_dump($unpacker->unpack()); // object(Decimal\Decimal) {...}
In addition to the basic types, the library provides functionality to serialize and deserialize arbitrary types. This can be done in several ways, depending on your use case. Let's take a look at them.
If you need to serialize an instance of one of your classes into one of the basic MessagePack types, the best way to do this is to implement the CanBePacked interface in the class. A good example of such a class is the Map
type class that comes with the library. This type is useful when you want to explicitly specify that a given PHP array should be packed as a MessagePack map without triggering an automatic type detection routine:
$packer = new Packer();
$packedMap = $packer->pack(new Map([1, 2, 3]));
$packedArray = $packer->pack([1, 2, 3]);
More type examples can be found in the src/Type directory.
As with type objects, type transformers are only responsible for serializing values. They should be used when you need to serialize a value that does not implement the CanBePacked interface. Examples of such values could be instances of built-in or third-party classes that you don't own, or non-objects such as resources.
A transformer class must implement the CanPack interface. To use a transformer, it must first be registered in the packer. Here is an example of how to serialize PHP streams into the MessagePack bin
format type using one of the supplied transformers, StreamTransformer
:
$packer = new Packer(null, [new StreamTransformer()]);
$packedBin = $packer->pack(fopen('/path/to/file', 'r+'));
More type transformer examples can be found in the src/TypeTransformer directory.
In contrast to the cases described above, extensions are intended to handle extension types and are responsible for both serialization and deserialization of values (types).
An extension class must implement the Extension interface. To use an extension, it must first be registered in the packer and the unpacker.
The MessagePack specification divides extension types into two groups: predefined and application-specific. Currently, there is only one predefined type in the specification, Timestamp.
Timestamp
The Timestamp extension type is a predefined type. Support for this type in the library is done through the TimestampExtension
class. This class is responsible for handling Timestamp
objects, which represent the number of seconds and optional adjustment in nanoseconds:
$timestampExtension = new TimestampExtension();
$packer = new Packer();
$packer = $packer->extendWith($timestampExtension);
$unpacker = new BufferUnpacker();
$unpacker = $unpacker->extendWith($timestampExtension);
$packedTimestamp = $packer->pack(Timestamp::now());
$timestamp = $unpacker->reset($packedTimestamp)->unpack();
$seconds = $timestamp->getSeconds();
$nanoseconds = $timestamp->getNanoseconds();
When using the MessagePack
class, the Timestamp extension is already registered:
$packedTimestamp = MessagePack::pack(Timestamp::now());
$timestamp = MessagePack::unpack($packedTimestamp);
Application-specific extensions
In addition, the format can be extended with your own types. For example, to make the built-in PHP DateTime
objects first-class citizens in your code, you can create a corresponding extension, as shown in the example. Please note, that custom extensions have to be registered with a unique extension ID (an integer from 0
to 127
).
More extension examples can be found in the examples/MessagePack directory.
To learn more about how extension types can be useful, check out this article.
If an error occurs during packing/unpacking, a PackingFailedException
or an UnpackingFailedException
will be thrown, respectively. In addition, an InsufficientDataException
can be thrown during unpacking.
An InvalidOptionException
will be thrown in case an invalid option (or a combination of mutually exclusive options) is used.
Run tests as follows:
vendor/bin/phpunit
Also, if you already have Docker installed, you can run the tests in a docker container. First, create a container:
./dockerfile.sh | docker build -t msgpack -
The command above will create a container named msgpack
with PHP 8.1 runtime. You may change the default runtime by defining the PHP_IMAGE
environment variable:
PHP_IMAGE='php:8.0-cli' ./dockerfile.sh | docker build -t msgpack -
See a list of various images here.
Then run the unit tests:
docker run --rm -v $PWD:/msgpack -w /msgpack msgpack
To ensure that the unpacking works correctly with malformed/semi-malformed data, you can use a testing technique called Fuzzing. The library ships with a help file (target) for PHP-Fuzzer and can be used as follows:
php-fuzzer fuzz tests/fuzz_buffer_unpacker.php
To check performance, run:
php -n -dzend_extension=opcache.so \
-dpcre.jit=1 -dopcache.enable=1 -dopcache.enable_cli=1 \
tests/bench.php
Example output
Filter: MessagePack\Tests\Perf\Filter\ListFilter
Rounds: 3
Iterations: 100000
=============================================
Test/Target Packer BufferUnpacker
---------------------------------------------
nil .................. 0.0030 ........ 0.0139
false ................ 0.0037 ........ 0.0144
true ................. 0.0040 ........ 0.0137
7-bit uint #1 ........ 0.0052 ........ 0.0120
7-bit uint #2 ........ 0.0059 ........ 0.0114
7-bit uint #3 ........ 0.0061 ........ 0.0119
5-bit sint #1 ........ 0.0067 ........ 0.0126
5-bit sint #2 ........ 0.0064 ........ 0.0132
5-bit sint #3 ........ 0.0066 ........ 0.0135
8-bit uint #1 ........ 0.0078 ........ 0.0200
8-bit uint #2 ........ 0.0077 ........ 0.0212
8-bit uint #3 ........ 0.0086 ........ 0.0203
16-bit uint #1 ....... 0.0111 ........ 0.0271
16-bit uint #2 ....... 0.0115 ........ 0.0260
16-bit uint #3 ....... 0.0103 ........ 0.0273
32-bit uint #1 ....... 0.0116 ........ 0.0326
32-bit uint #2 ....... 0.0118 ........ 0.0332
32-bit uint #3 ....... 0.0127 ........ 0.0325
64-bit uint #1 ....... 0.0140 ........ 0.0277
64-bit uint #2 ....... 0.0134 ........ 0.0294
64-bit uint #3 ....... 0.0134 ........ 0.0281
8-bit int #1 ......... 0.0086 ........ 0.0241
8-bit int #2 ......... 0.0089 ........ 0.0225
8-bit int #3 ......... 0.0085 ........ 0.0229
16-bit int #1 ........ 0.0118 ........ 0.0280
16-bit int #2 ........ 0.0121 ........ 0.0270
16-bit int #3 ........ 0.0109 ........ 0.0274
32-bit int #1 ........ 0.0128 ........ 0.0346
32-bit int #2 ........ 0.0118 ........ 0.0339
32-bit int #3 ........ 0.0135 ........ 0.0368
64-bit int #1 ........ 0.0138 ........ 0.0276
64-bit int #2 ........ 0.0132 ........ 0.0286
64-bit int #3 ........ 0.0137 ........ 0.0274
64-bit int #4 ........ 0.0180 ........ 0.0285
64-bit float #1 ...... 0.0134 ........ 0.0284
64-bit float #2 ...... 0.0125 ........ 0.0275
64-bit float #3 ...... 0.0126 ........ 0.0283
fix string #1 ........ 0.0035 ........ 0.0133
fix string #2 ........ 0.0094 ........ 0.0216
fix string #3 ........ 0.0094 ........ 0.0222
fix string #4 ........ 0.0091 ........ 0.0241
8-bit string #1 ...... 0.0122 ........ 0.0301
8-bit string #2 ...... 0.0118 ........ 0.0304
8-bit string #3 ...... 0.0119 ........ 0.0315
16-bit string #1 ..... 0.0150 ........ 0.0388
16-bit string #2 ..... 0.1545 ........ 0.1665
32-bit string ........ 0.1570 ........ 0.1756
wide char string #1 .. 0.0091 ........ 0.0236
wide char string #2 .. 0.0122 ........ 0.0313
8-bit binary #1 ...... 0.0100 ........ 0.0302
8-bit binary #2 ...... 0.0123 ........ 0.0324
8-bit binary #3 ...... 0.0126 ........ 0.0327
16-bit binary ........ 0.0168 ........ 0.0372
32-bit binary ........ 0.1588 ........ 0.1754
fix array #1 ......... 0.0042 ........ 0.0131
fix array #2 ......... 0.0294 ........ 0.0367
fix array #3 ......... 0.0412 ........ 0.0472
16-bit array #1 ...... 0.1378 ........ 0.1596
16-bit array #2 ........... S ............. S
32-bit array .............. S ............. S
complex array ........ 0.1865 ........ 0.2283
fix map #1 ........... 0.0725 ........ 0.1048
fix map #2 ........... 0.0319 ........ 0.0405
fix map #3 ........... 0.0356 ........ 0.0665
fix map #4 ........... 0.0465 ........ 0.0497
16-bit map #1 ........ 0.2540 ........ 0.3028
16-bit map #2 ............. S ............. S
32-bit map ................ S ............. S
complex map .......... 0.2372 ........ 0.2710
fixext 1 ............. 0.0283 ........ 0.0358
fixext 2 ............. 0.0291 ........ 0.0371
fixext 4 ............. 0.0302 ........ 0.0355
fixext 8 ............. 0.0288 ........ 0.0384
fixext 16 ............ 0.0293 ........ 0.0359
8-bit ext ............ 0.0302 ........ 0.0439
16-bit ext ........... 0.0334 ........ 0.0499
32-bit ext ........... 0.1845 ........ 0.1888
32-bit timestamp #1 .. 0.0337 ........ 0.0547
32-bit timestamp #2 .. 0.0335 ........ 0.0560
64-bit timestamp #1 .. 0.0371 ........ 0.0575
64-bit timestamp #2 .. 0.0374 ........ 0.0542
64-bit timestamp #3 .. 0.0356 ........ 0.0533
96-bit timestamp #1 .. 0.0362 ........ 0.0699
96-bit timestamp #2 .. 0.0381 ........ 0.0701
96-bit timestamp #3 .. 0.0367 ........ 0.0687
=============================================
Total 2.7618 4.0820
Skipped 4 4
Failed 0 0
Ignored 0 0
With JIT:
php -n -dzend_extension=opcache.so \
-dpcre.jit=1 -dopcache.jit_buffer_size=64M -dopcache.jit=tracing -dopcache.enable=1 -dopcache.enable_cli=1 \
tests/bench.php
Example output
Filter: MessagePack\Tests\Perf\Filter\ListFilter
Rounds: 3
Iterations: 100000
=============================================
Test/Target Packer BufferUnpacker
---------------------------------------------
nil .................. 0.0005 ........ 0.0054
false ................ 0.0004 ........ 0.0059
true ................. 0.0004 ........ 0.0059
7-bit uint #1 ........ 0.0010 ........ 0.0047
7-bit uint #2 ........ 0.0010 ........ 0.0046
7-bit uint #3 ........ 0.0010 ........ 0.0046
5-bit sint #1 ........ 0.0025 ........ 0.0046
5-bit sint #2 ........ 0.0023 ........ 0.0046
5-bit sint #3 ........ 0.0024 ........ 0.0045
8-bit uint #1 ........ 0.0043 ........ 0.0081
8-bit uint #2 ........ 0.0043 ........ 0.0079
8-bit uint #3 ........ 0.0041 ........ 0.0080
16-bit uint #1 ....... 0.0064 ........ 0.0095
16-bit uint #2 ....... 0.0064 ........ 0.0091
16-bit uint #3 ....... 0.0064 ........ 0.0094
32-bit uint #1 ....... 0.0085 ........ 0.0114
32-bit uint #2 ....... 0.0077 ........ 0.0122
32-bit uint #3 ....... 0.0077 ........ 0.0120
64-bit uint #1 ....... 0.0085 ........ 0.0159
64-bit uint #2 ....... 0.0086 ........ 0.0157
64-bit uint #3 ....... 0.0086 ........ 0.0158
8-bit int #1 ......... 0.0042 ........ 0.0080
8-bit int #2 ......... 0.0042 ........ 0.0080
8-bit int #3 ......... 0.0042 ........ 0.0081
16-bit int #1 ........ 0.0065 ........ 0.0095
16-bit int #2 ........ 0.0065 ........ 0.0090
16-bit int #3 ........ 0.0056 ........ 0.0085
32-bit int #1 ........ 0.0067 ........ 0.0107
32-bit int #2 ........ 0.0066 ........ 0.0106
32-bit int #3 ........ 0.0063 ........ 0.0104
64-bit int #1 ........ 0.0072 ........ 0.0162
64-bit int #2 ........ 0.0073 ........ 0.0174
64-bit int #3 ........ 0.0072 ........ 0.0164
64-bit int #4 ........ 0.0077 ........ 0.0161
64-bit float #1 ...... 0.0053 ........ 0.0135
64-bit float #2 ...... 0.0053 ........ 0.0135
64-bit float #3 ...... 0.0052 ........ 0.0135
fix string #1 ....... -0.0002 ........ 0.0044
fix string #2 ........ 0.0035 ........ 0.0067
fix string #3 ........ 0.0035 ........ 0.0077
fix string #4 ........ 0.0033 ........ 0.0078
8-bit string #1 ...... 0.0059 ........ 0.0110
8-bit string #2 ...... 0.0063 ........ 0.0121
8-bit string #3 ...... 0.0064 ........ 0.0124
16-bit string #1 ..... 0.0099 ........ 0.0146
16-bit string #2 ..... 0.1522 ........ 0.1474
32-bit string ........ 0.1511 ........ 0.1483
wide char string #1 .. 0.0039 ........ 0.0084
wide char string #2 .. 0.0073 ........ 0.0123
8-bit binary #1 ...... 0.0040 ........ 0.0112
8-bit binary #2 ...... 0.0075 ........ 0.0123
8-bit binary #3 ...... 0.0077 ........ 0.0129
16-bit binary ........ 0.0096 ........ 0.0145
32-bit binary ........ 0.1535 ........ 0.1479
fix array #1 ......... 0.0008 ........ 0.0061
fix array #2 ......... 0.0121 ........ 0.0165
fix array #3 ......... 0.0193 ........ 0.0222
16-bit array #1 ...... 0.0607 ........ 0.0479
16-bit array #2 ........... S ............. S
32-bit array .............. S ............. S
complex array ........ 0.0749 ........ 0.0824
fix map #1 ........... 0.0329 ........ 0.0431
fix map #2 ........... 0.0161 ........ 0.0189
fix map #3 ........... 0.0205 ........ 0.0262
fix map #4 ........... 0.0252 ........ 0.0205
16-bit map #1 ........ 0.1016 ........ 0.0927
16-bit map #2 ............. S ............. S
32-bit map ................ S ............. S
complex map .......... 0.1096 ........ 0.1030
fixext 1 ............. 0.0157 ........ 0.0161
fixext 2 ............. 0.0175 ........ 0.0183
fixext 4 ............. 0.0156 ........ 0.0185
fixext 8 ............. 0.0163 ........ 0.0184
fixext 16 ............ 0.0164 ........ 0.0182
8-bit ext ............ 0.0158 ........ 0.0207
16-bit ext ........... 0.0203 ........ 0.0219
32-bit ext ........... 0.1614 ........ 0.1539
32-bit timestamp #1 .. 0.0195 ........ 0.0249
32-bit timestamp #2 .. 0.0188 ........ 0.0260
64-bit timestamp #1 .. 0.0207 ........ 0.0281
64-bit timestamp #2 .. 0.0212 ........ 0.0291
64-bit timestamp #3 .. 0.0207 ........ 0.0295
96-bit timestamp #1 .. 0.0222 ........ 0.0358
96-bit timestamp #2 .. 0.0228 ........ 0.0353
96-bit timestamp #3 .. 0.0210 ........ 0.0319
=============================================
Total 1.6432 1.9674
Skipped 4 4
Failed 0 0
Ignored 0 0
You may change default benchmark settings by defining the following environment variables:
Name | Default |
---|---|
MP_BENCH_TARGETS | pure_p,pure_u , see a list of available targets |
MP_BENCH_ITERATIONS | 100_000 |
MP_BENCH_DURATION | not set |
MP_BENCH_ROUNDS | 3 |
MP_BENCH_TESTS | -@slow , see a list of available tests |
For example:
export MP_BENCH_TARGETS=pure_p
export MP_BENCH_ITERATIONS=1000000
export MP_BENCH_ROUNDS=5
# a comma separated list of test names
export MP_BENCH_TESTS='complex array, complex map'
# or a group name
# export MP_BENCH_TESTS='-@slow' // @pecl_comp
# or a regexp
# export MP_BENCH_TESTS='/complex (array|map)/'
Another example, benchmarking both the library and the PECL extension:
MP_BENCH_TARGETS=pure_p,pure_u,pecl_p,pecl_u \
php -n -dextension=msgpack.so -dzend_extension=opcache.so \
-dpcre.jit=1 -dopcache.enable=1 -dopcache.enable_cli=1 \
tests/bench.php
Example output
Filter: MessagePack\Tests\Perf\Filter\ListFilter
Rounds: 3
Iterations: 100000
===========================================================================
Test/Target Packer BufferUnpacker msgpack_pack msgpack_unpack
---------------------------------------------------------------------------
nil .................. 0.0031 ........ 0.0141 ...... 0.0055 ........ 0.0064
false ................ 0.0039 ........ 0.0154 ...... 0.0056 ........ 0.0053
true ................. 0.0038 ........ 0.0139 ...... 0.0056 ........ 0.0044
7-bit uint #1 ........ 0.0061 ........ 0.0110 ...... 0.0059 ........ 0.0046
7-bit uint #2 ........ 0.0065 ........ 0.0119 ...... 0.0042 ........ 0.0029
7-bit uint #3 ........ 0.0054 ........ 0.0117 ...... 0.0045 ........ 0.0025
5-bit sint #1 ........ 0.0047 ........ 0.0103 ...... 0.0038 ........ 0.0022
5-bit sint #2 ........ 0.0048 ........ 0.0117 ...... 0.0038 ........ 0.0022
5-bit sint #3 ........ 0.0046 ........ 0.0102 ...... 0.0038 ........ 0.0023
8-bit uint #1 ........ 0.0063 ........ 0.0174 ...... 0.0039 ........ 0.0031
8-bit uint #2 ........ 0.0063 ........ 0.0167 ...... 0.0040 ........ 0.0029
8-bit uint #3 ........ 0.0063 ........ 0.0168 ...... 0.0039 ........ 0.0030
16-bit uint #1 ....... 0.0092 ........ 0.0222 ...... 0.0049 ........ 0.0030
16-bit uint #2 ....... 0.0096 ........ 0.0227 ...... 0.0042 ........ 0.0046
16-bit uint #3 ....... 0.0123 ........ 0.0274 ...... 0.0059 ........ 0.0051
32-bit uint #1 ....... 0.0136 ........ 0.0331 ...... 0.0060 ........ 0.0048
32-bit uint #2 ....... 0.0130 ........ 0.0336 ...... 0.0070 ........ 0.0048
32-bit uint #3 ....... 0.0127 ........ 0.0329 ...... 0.0051 ........ 0.0048
64-bit uint #1 ....... 0.0126 ........ 0.0268 ...... 0.0055 ........ 0.0049
64-bit uint #2 ....... 0.0135 ........ 0.0281 ...... 0.0052 ........ 0.0046
64-bit uint #3 ....... 0.0131 ........ 0.0274 ...... 0.0069 ........ 0.0044
8-bit int #1 ......... 0.0077 ........ 0.0236 ...... 0.0058 ........ 0.0044
8-bit int #2 ......... 0.0087 ........ 0.0244 ...... 0.0058 ........ 0.0048
8-bit int #3 ......... 0.0084 ........ 0.0241 ...... 0.0055 ........ 0.0049
16-bit int #1 ........ 0.0112 ........ 0.0271 ...... 0.0048 ........ 0.0045
16-bit int #2 ........ 0.0124 ........ 0.0292 ...... 0.0057 ........ 0.0049
16-bit int #3 ........ 0.0118 ........ 0.0270 ...... 0.0058 ........ 0.0050
32-bit int #1 ........ 0.0137 ........ 0.0366 ...... 0.0058 ........ 0.0051
32-bit int #2 ........ 0.0133 ........ 0.0366 ...... 0.0056 ........ 0.0049
32-bit int #3 ........ 0.0129 ........ 0.0350 ...... 0.0052 ........ 0.0048
64-bit int #1 ........ 0.0145 ........ 0.0254 ...... 0.0034 ........ 0.0025
64-bit int #2 ........ 0.0097 ........ 0.0214 ...... 0.0034 ........ 0.0025
64-bit int #3 ........ 0.0096 ........ 0.0287 ...... 0.0059 ........ 0.0050
64-bit int #4 ........ 0.0143 ........ 0.0277 ...... 0.0059 ........ 0.0046
64-bit float #1 ...... 0.0134 ........ 0.0281 ...... 0.0057 ........ 0.0052
64-bit float #2 ...... 0.0141 ........ 0.0281 ...... 0.0057 ........ 0.0050
64-bit float #3 ...... 0.0144 ........ 0.0282 ...... 0.0057 ........ 0.0050
fix string #1 ........ 0.0036 ........ 0.0143 ...... 0.0066 ........ 0.0053
fix string #2 ........ 0.0107 ........ 0.0222 ...... 0.0065 ........ 0.0068
fix string #3 ........ 0.0116 ........ 0.0245 ...... 0.0063 ........ 0.0069
fix string #4 ........ 0.0105 ........ 0.0253 ...... 0.0083 ........ 0.0077
8-bit string #1 ...... 0.0126 ........ 0.0318 ...... 0.0075 ........ 0.0088
8-bit string #2 ...... 0.0121 ........ 0.0295 ...... 0.0076 ........ 0.0086
8-bit string #3 ...... 0.0125 ........ 0.0293 ...... 0.0130 ........ 0.0093
16-bit string #1 ..... 0.0159 ........ 0.0368 ...... 0.0117 ........ 0.0086
16-bit string #2 ..... 0.1547 ........ 0.1686 ...... 0.1516 ........ 0.1373
32-bit string ........ 0.1558 ........ 0.1729 ...... 0.1511 ........ 0.1396
wide char string #1 .. 0.0098 ........ 0.0237 ...... 0.0066 ........ 0.0065
wide char string #2 .. 0.0128 ........ 0.0291 ...... 0.0061 ........ 0.0082
8-bit binary #1 ........... I ............. I ........... F ............. I
8-bit binary #2 ........... I ............. I ........... F ............. I
8-bit binary #3 ........... I ............. I ........... F ............. I
16-bit binary ............. I ............. I ........... F ............. I
32-bit binary ............. I ............. I ........... F ............. I
fix array #1 ......... 0.0040 ........ 0.0129 ...... 0.0120 ........ 0.0058
fix array #2 ......... 0.0279 ........ 0.0390 ...... 0.0143 ........ 0.0165
fix array #3 ......... 0.0415 ........ 0.0463 ...... 0.0162 ........ 0.0187
16-bit array #1 ...... 0.1349 ........ 0.1628 ...... 0.0334 ........ 0.0341
16-bit array #2 ........... S ............. S ........... S ............. S
32-bit array .............. S ............. S ........... S ............. S
complex array ............. I ............. I ........... F ............. F
fix map #1 ................ I ............. I ........... F ............. I
fix map #2 ........... 0.0345 ........ 0.0391 ...... 0.0143 ........ 0.0168
fix map #3 ................ I ............. I ........... F ............. I
fix map #4 ........... 0.0459 ........ 0.0473 ...... 0.0151 ........ 0.0163
16-bit map #1 ........ 0.2518 ........ 0.2962 ...... 0.0400 ........ 0.0490
16-bit map #2 ............. S ............. S ........... S ............. S
32-bit map ................ S ............. S ........... S ............. S
complex map .......... 0.2380 ........ 0.2682 ...... 0.0545 ........ 0.0579
fixext 1 .................. I ............. I ........... F ............. F
fixext 2 .................. I ............. I ........... F ............. F
fixext 4 .................. I ............. I ........... F ............. F
fixext 8 .................. I ............. I ........... F ............. F
fixext 16 ................. I ............. I ........... F ............. F
8-bit ext ................. I ............. I ........... F ............. F
16-bit ext ................ I ............. I ........... F ............. F
32-bit ext ................ I ............. I ........... F ............. F
32-bit timestamp #1 ....... I ............. I ........... F ............. F
32-bit timestamp #2 ....... I ............. I ........... F ............. F
64-bit timestamp #1 ....... I ............. I ........... F ............. F
64-bit timestamp #2 ....... I ............. I ........... F ............. F
64-bit timestamp #3 ....... I ............. I ........... F ............. F
96-bit timestamp #1 ....... I ............. I ........... F ............. F
96-bit timestamp #2 ....... I ............. I ........... F ............. F
96-bit timestamp #3 ....... I ............. I ........... F ............. F
===========================================================================
Total 1.5625 2.3866 0.7735 0.7243
Skipped 4 4 4 4
Failed 0 0 24 17
Ignored 24 24 0 7
With JIT:
MP_BENCH_TARGETS=pure_p,pure_u,pecl_p,pecl_u \
php -n -dextension=msgpack.so -dzend_extension=opcache.so \
-dpcre.jit=1 -dopcache.jit_buffer_size=64M -dopcache.jit=tracing -dopcache.enable=1 -dopcache.enable_cli=1 \
tests/bench.php
Example output
Filter: MessagePack\Tests\Perf\Filter\ListFilter
Rounds: 3
Iterations: 100000
===========================================================================
Test/Target Packer BufferUnpacker msgpack_pack msgpack_unpack
---------------------------------------------------------------------------
nil .................. 0.0001 ........ 0.0052 ...... 0.0053 ........ 0.0042
false ................ 0.0007 ........ 0.0060 ...... 0.0057 ........ 0.0043
true ................. 0.0008 ........ 0.0060 ...... 0.0056 ........ 0.0041
7-bit uint #1 ........ 0.0031 ........ 0.0046 ...... 0.0062 ........ 0.0041
7-bit uint #2 ........ 0.0021 ........ 0.0043 ...... 0.0062 ........ 0.0041
7-bit uint #3 ........ 0.0022 ........ 0.0044 ...... 0.0061 ........ 0.0040
5-bit sint #1 ........ 0.0030 ........ 0.0048 ...... 0.0062 ........ 0.0040
5-bit sint #2 ........ 0.0032 ........ 0.0046 ...... 0.0062 ........ 0.0040
5-bit sint #3 ........ 0.0031 ........ 0.0046 ...... 0.0062 ........ 0.0040
8-bit uint #1 ........ 0.0054 ........ 0.0079 ...... 0.0062 ........ 0.0050
8-bit uint #2 ........ 0.0051 ........ 0.0079 ...... 0.0064 ........ 0.0044
8-bit uint #3 ........ 0.0051 ........ 0.0082 ...... 0.0062 ........ 0.0044
16-bit uint #1 ....... 0.0077 ........ 0.0094 ...... 0.0065 ........ 0.0045
16-bit uint #2 ....... 0.0077 ........ 0.0094 ...... 0.0063 ........ 0.0045
16-bit uint #3 ....... 0.0077 ........ 0.0095 ...... 0.0064 ........ 0.0047
32-bit uint #1 ....... 0.0088 ........ 0.0119 ...... 0.0063 ........ 0.0043
32-bit uint #2 ....... 0.0089 ........ 0.0117 ...... 0.0062 ........ 0.0039
32-bit uint #3 ....... 0.0089 ........ 0.0118 ...... 0.0063 ........ 0.0044
64-bit uint #1 ....... 0.0097 ........ 0.0155 ...... 0.0063 ........ 0.0045
64-bit uint #2 ....... 0.0095 ........ 0.0153 ...... 0.0061 ........ 0.0045
64-bit uint #3 ....... 0.0096 ........ 0.0156 ...... 0.0063 ........ 0.0047
8-bit int #1 ......... 0.0053 ........ 0.0083 ...... 0.0062 ........ 0.0044
8-bit int #2 ......... 0.0052 ........ 0.0080 ...... 0.0062 ........ 0.0044
8-bit int #3 ......... 0.0052 ........ 0.0080 ...... 0.0062 ........ 0.0043
16-bit int #1 ........ 0.0089 ........ 0.0097 ...... 0.0069 ........ 0.0046
16-bit int #2 ........ 0.0075 ........ 0.0093 ...... 0.0063 ........ 0.0043
16-bit int #3 ........ 0.0075 ........ 0.0094 ...... 0.0062 ........ 0.0046
32-bit int #1 ........ 0.0086 ........ 0.0122 ...... 0.0063 ........ 0.0044
32-bit int #2 ........ 0.0087 ........ 0.0120 ...... 0.0066 ........ 0.0046
32-bit int #3 ........ 0.0086 ........ 0.0121 ...... 0.0060 ........ 0.0044
64-bit int #1 ........ 0.0096 ........ 0.0149 ...... 0.0060 ........ 0.0045
64-bit int #2 ........ 0.0096 ........ 0.0157 ...... 0.0062 ........ 0.0044
64-bit int #3 ........ 0.0096 ........ 0.0160 ...... 0.0063 ........ 0.0046
64-bit int #4 ........ 0.0097 ........ 0.0157 ...... 0.0061 ........ 0.0044
64-bit float #1 ...... 0.0079 ........ 0.0153 ...... 0.0056 ........ 0.0044
64-bit float #2 ...... 0.0079 ........ 0.0152 ...... 0.0057 ........ 0.0045
64-bit float #3 ...... 0.0079 ........ 0.0155 ...... 0.0057 ........ 0.0044
fix string #1 ........ 0.0010 ........ 0.0045 ...... 0.0071 ........ 0.0044
fix string #2 ........ 0.0048 ........ 0.0075 ...... 0.0070 ........ 0.0060
fix string #3 ........ 0.0048 ........ 0.0086 ...... 0.0068 ........ 0.0060
fix string #4 ........ 0.0050 ........ 0.0088 ...... 0.0070 ........ 0.0059
8-bit string #1 ...... 0.0081 ........ 0.0129 ...... 0.0069 ........ 0.0062
8-bit string #2 ...... 0.0086 ........ 0.0128 ...... 0.0069 ........ 0.0065
8-bit string #3 ...... 0.0086 ........ 0.0126 ...... 0.0115 ........ 0.0065
16-bit string #1 ..... 0.0105 ........ 0.0137 ...... 0.0128 ........ 0.0068
16-bit string #2 ..... 0.1510 ........ 0.1486 ...... 0.1526 ........ 0.1391
32-bit string ........ 0.1517 ........ 0.1475 ...... 0.1504 ........ 0.1370
wide char string #1 .. 0.0044 ........ 0.0085 ...... 0.0067 ........ 0.0057
wide char string #2 .. 0.0081 ........ 0.0125 ...... 0.0069 ........ 0.0063
8-bit binary #1 ........... I ............. I ........... F ............. I
8-bit binary #2 ........... I ............. I ........... F ............. I
8-bit binary #3 ........... I ............. I ........... F ............. I
16-bit binary ............. I ............. I ........... F ............. I
32-bit binary ............. I ............. I ........... F ............. I
fix array #1 ......... 0.0014 ........ 0.0059 ...... 0.0132 ........ 0.0055
fix array #2 ......... 0.0146 ........ 0.0156 ...... 0.0155 ........ 0.0148
fix array #3 ......... 0.0211 ........ 0.0229 ...... 0.0179 ........ 0.0180
16-bit array #1 ...... 0.0673 ........ 0.0498 ...... 0.0343 ........ 0.0388
16-bit array #2 ........... S ............. S ........... S ............. S
32-bit array .............. S ............. S ........... S ............. S
complex array ............. I ............. I ........... F ............. F
fix map #1 ................ I ............. I ........... F ............. I
fix map #2 ........... 0.0148 ........ 0.0180 ...... 0.0156 ........ 0.0179
fix map #3 ................ I ............. I ........... F ............. I
fix map #4 ........... 0.0252 ........ 0.0201 ...... 0.0214 ........ 0.0167
16-bit map #1 ........ 0.1027 ........ 0.0836 ...... 0.0388 ........ 0.0510
16-bit map #2 ............. S ............. S ........... S ............. S
32-bit map ................ S ............. S ........... S ............. S
complex map .......... 0.1104 ........ 0.1010 ...... 0.0556 ........ 0.0602
fixext 1 .................. I ............. I ........... F ............. F
fixext 2 .................. I ............. I ........... F ............. F
fixext 4 .................. I ............. I ........... F ............. F
fixext 8 .................. I ............. I ........... F ............. F
fixext 16 ................. I ............. I ........... F ............. F
8-bit ext ................. I ............. I ........... F ............. F
16-bit ext ................ I ............. I ........... F ............. F
32-bit ext ................ I ............. I ........... F ............. F
32-bit timestamp #1 ....... I ............. I ........... F ............. F
32-bit timestamp #2 ....... I ............. I ........... F ............. F
64-bit timestamp #1 ....... I ............. I ........... F ............. F
64-bit timestamp #2 ....... I ............. I ........... F ............. F
64-bit timestamp #3 ....... I ............. I ........... F ............. F
96-bit timestamp #1 ....... I ............. I ........... F ............. F
96-bit timestamp #2 ....... I ............. I ........... F ............. F
96-bit timestamp #3 ....... I ............. I ........... F ............. F
===========================================================================
Total 0.9642 1.0909 0.8224 0.7213
Skipped 4 4 4 4
Failed 0 0 24 17
Ignored 24 24 0 7
Note that the msgpack extension (v2.1.2) doesn't support ext, bin and UTF-8 str types.
The library is released under the MIT License. See the bundled LICENSE file for details.
Author: rybakit
Source Code: https://github.com/rybakit/msgpack.php
License: MIT License
1671543249
February 15, 2022 marked a significant milestone in Atlassian’s Server EOL (End Of Life) roadmap. This was not the final step. We still have two major milestones ahead of us: end of new app sales in Feb 2023, and end of support in Feb 2024. In simpler words, businesses still have enough time to migrate their Jira Server to one of the two available products – Atlassian Cloud or Atlassian DC. But the clock is ticking.
If we were to go by Atlassian numbers, 95% of their new customers choose cloud.
“About 80% of Fortune 500 companies have an Atlassian Cloud license. More than 90% of new customers choose cloud first.” – Daniel Scott, Product Marketing Director, Tempo
So that’s settled, right? We are migrating from Server to Cloud? And what about the solution fewer people talk about yet many users rely on – Jira DC?
Both are viable options and your choice will depend greatly on the needs of your business, your available resources, and operational processes.
Let’s start by taking a look at the functionality offered by Atlassian Cloud and Atlassian DC.
Feature | Atlassian Cloud | Atlassian Data Center |
Product Plans | Multiple plans | One plan |
Billing | Monthly and annual | Annual only |
Pricing model | Per user or tiered | Tiered only |
Support | Varying support levels depending on your plan: Enterprise support coverage is equivalent to Atlassian’s Data Center Premier Support offering | Varying support levels depending on the package: Priority Support or Premier Support (purchased separately) |
Total Cost of Ownership | TCO includes your subscription fee, plus product administration time | TCO includes your subscription fee and product administration time, plus: costs related to infrastructure provisioning or IaaS fees (for example, AWS costs) planned downtime time and resources needed for software upgrades |
Data encryption services | ||
Data residency services | ||
Audit logging | Organization-level audit logging available via Atlassian Access (Jira Software, Confluence) Product-level audit logs (Jira Software, Confluence) | Advanced audit logging |
Device security | Mobile device management support (Jira Software, Confluence, Jira Service Management) Mobile application management (currently on the roadmap) | Mobile device management support (Jira Software, Confluence, Jira Service Management) |
Content security | ||
Data Storage limits | 2 GB (Free) 250 GB (Standard) Unlimited storage (Premium and Enterprise) | No limits |
Performance | Continuous performance updates to improve load times, search responsiveness, and attachments Cloud infrastructure hosted in six geographic regions to reduce latency | Rate limitingCDN supports Smart mirrors and mirror farms (Bitbucket) |
Backup and data disaster recovery | Jira leverages multiple geographically diverse data centers, has a comprehensive backup program, and gains assurance by regularly testing their disaster recovery and business continuity plans. Backups are generated daily and retained for 30 days to allow for point-in-time data restoration | |
Containerization and orchestration | Docker images Kubernetes support (on the roadmap for now) | |
Change management and upgrades | Atlassian automatically handles software and security upgrades for you Sandbox instance to test changes (Premium and Enterprise) Release track options for Premium and Enterprise (Jira Software, Jira Service Management, Confluence) | |
Direct access to the database | No direct access to change the database structure, file system, or other server infrastructure Extensive REST APIs for programmatic data access | Direct database access |
Insights and reporting | Organization and admin insights to track adoption of Atlassian products, and evaluate the security of your organization. | Data Pipeline for advanced insightsConfluence analytics |
When talking about pros and cons, there’s always a chance that a competitive advantage for some is a dealbreaker for others. That’s why I decided to talk about pros and cons in matching pairs.
Pro: Scalability is one of the primary reasons businesses are choosing Jira Cloud. DC is technically also scalable, but you’ll need to scale on your own whereas the cloud version allows for the infrastructure to scale with your business.
Con: Despite the cloud’s ability to grow with your business, there is still a user limit of 35k users. In addition to that, the costs will grow alongside your needs. New users, licenses, storage, and computing power – all come at an additional cost. So, when your organization reaches a certain size, migrating to Jira DC becomes more cost-efficient.
Pro: Jira takes care of maintenance and support for you.
Con: Your business can suffer from unpredicted downtime. And there are certain security risks.
Pro: Extra bells and whistles:
Con: Most of these features are locked behind a paywall and are only available to either Premium and Enterprise or only Enterprise licenses (either fully or through addition of functionality. For example, Release tracks are only available to Enterprise customers.) In addition, the costs will grow as you scale the offering to fit your growing needs.
I’ll be taking the same approach to talking about the pros and cons as I did when writing about Atlassian Cloud. Pros and cons are paired.
Pro: Hosting your own system means you can scale horizontally and vertically through additional hardware. Extension of your systems is seamless, and there is no downtime (if you do everything correctly). Lastly, you don’t have to worry about the user limit – there is none.
Con: While having more control over your systems is great, it implies a dedicated staff of engineers, additional expenses on software licensing, hardware, and physical space. Moreover, seamless extension and 0% downtime are entirely on you.
Pro: Atlassian has updated the DC offering with native bundled applications such as Advanced Roadmaps, team calendars and analytics for confluence, insight asset management, and insight discovery in Jira Service Management DC.
Con: Atlassian has updated their pricing to reflect these changes. And you are still getting fewer “bells and whistles” than Jira Cloud users (as we can see from the feature comparison).
Pro: You are technically safer as the system is supported on your hardware by your specialists. Any and all Jira server issues, poor updates, and downtime are simply not your concern.
Con: Atlassian offers excellent security options: data encryption in transit and rest, to mobile app management, to audit offerings and API token controls. In their absence, your team company has to dedicate additional resources to security.
Pro: Additional benefits from Atlassian, such as the Priority Support bundle (all DC subscriptions have this option), and the Data center loyalty discount (more on that in the pricing section.)
Talking about pricing of SaaS products is always a challenge as there are always multiple tiers and various pay-as-you go features. Barebones Jira Cloud, for instance, is completely free of charge, yet there are a series of serious limitations.
Standard Jira Cloud will cost you an average of $7.50 per user per month while premium cranks that price up to $14.50. The Enterprise plan is billed annually and the cost is determined on a case-by-case basis. You can see the full comparison of Jira Cloud plans here. And you can use this online calculator to learn the cost of ownership in your particular case.
50 Users | Standard (Monthly/Annually) | Premium (Monthly/Annually) |
Jira Software | $387.50 / $3,900 | $762.50 / $7,650 |
Jira Work Management | $250 / $2,500 | |
Jira Service Management | $866.25 / $8,650 | $2,138.25 / $21,500 |
Confluence | $287.50 / $2,900 | $550 / $5,500 |
100 Users | Standard (Monthly/Annually) | Premium (Monthly/Annually) |
Jira Software | $775 / $7,750 | $1,525 / $15,250 |
Jira Work Management | $500 / $5,000 | |
Jira Service Management | $1,653.75 / $16,550 | $4,185.75 / $42,000 |
Confluence | $575 / $5,750 | $1,100 / $11,000 |
500 Users | Standard (Monthly/Annually) | Premium (Monthly/Annually) |
Jira Software | $3,140 / $31,500 | $5,107.50 / $51,000 |
Jira Work Management | $1,850 / $18,500 | |
Jira Service Management | $4,541.25 / $45,400 | $11,693.25 / $117,000 |
Confluence | $2,060 / $20,500 | $3,780 / $37,800 |
Please note that these prices were calculated without any apps included.
Jira Data Center starts at $42,000 per year and the plan includes up to 500 users. If you are a new client and are not eligible for any discounts*, here’s a chart that should give you an idea as to the cost of ownership of Jira DC. You can find more information regarding your specific case here.
Users | Commercial Annual Plan | Academic Annual Plan |
1-500 | USD 42,000 | USD 21,000 |
501-1000 | USD 72,000 | USD 36,000 |
1001-2000 | USD 120,000 | USD 60,000 |
Confluence for Data Center | ||
1-500 | USD 27,000 | USD 13,500 |
501-1000 | USD 48,000 | USD 24,000 |
1001-2000 | USD 84,000 | USD 42,000 |
Bitbucket for Data Center | ||
1-25 | USD 2,300 | USD 1,150 |
26-50 | USD 4,200 | USD 2,100 |
51-100 | USD 7,600 | USD 3,800 |
Jira Service Management for Data Center | ||
1-50 | USD 17,200 | USD 8,600 |
51-100 | USD 28,600 | USD 14,300 |
101-250 | USD 51,500 | USD 25,750 |
*Discounts:
Originally, there were several migration methods: Jira Cloud Migration Assistant, Jira Cloud Site Import, and there was an option to migrate via CSV export (though Jira actively discourages you from using this method). However, Jira’s team has focused their efforts on improving the Migration Assistant and have chosen to discontinue Cloud Site Import support.
Thanks to the broadened functionality of the assistant, it is now the only go-to method for migration with just one exception. If you are migrating over 1000 users and you absolutely need to migrate advanced roadmaps – you’ll need to rely on Site Import. At least for now, as Jira is actively working on implementing this feature in their assistant.
Here’s a quick comparison of the options and their limitations.
Features | Limitations | |
Cloud Migration Assistant | App migration Existing data on a Cloud Site is not overwritten You choose the projects, users, and groups you want to migrate Jira Service Management customer account migration Better UI to guide you through the migration Potential migration errors are displayed in advance Migration can be done in phases reducing the downtime Pre- and post-migration reports | You must be on a supported self-managed version of Jira |
Site Export | Can migrate Advanced Roadmaps | App data is not migrated Migration overrides existing data on the Cloud site Separate user importUsers from external directories are not migrated No choice of data you want or don’t want migrated There’s a need to split attachments into up to 5GB chunks Higher risks of downtime due to the “all or nothing” approach You must be on a supported self-managed version of Jira |
Pro tip: If you have a large base of users (above 2000), migrate them before you migrate projects and spaces. This way, you will not disrupt the workflow as users are still working on Server and the latter migration of data will take less time.
Now that we have settled on one particular offering based on available pricing models as well as the pros and the cons that matter the most to your organization, let’s talk about the “how”.
How does one migrate from Jira Server to Jira Cloud?
Jira’s Cloud Migration Assistant is a handy tool. It will automatically review your data for common errors. But it is incapable of doing all of the work for you. That’s why we – and Atlassian for that matter – recommend creating a pre-migration checklist.
Smart Checklist will help you craft an actionable, context-rich checklist directly inside a Jira ticket. This way, none of the tasks will be missed, lost, or abandoned.
Below is an example of how your migration checklist will look like in Jira.
Feel free to copy the code and paste it into your Smart Checklist editor and you’ll have the checklist at the ready.
# Create a user migration plan #must
> Please keep in mind that Jira Cloud Migration Assistant migrates all users and groups as well as users and groups related to selected projects
- Sync your user base
- Verify synchronization
- External users sync verification
- Active external directory verification
## Check your Jira Server version #must
- Verify via user interface or Support Zip Product Version Verification
> Jira Migration Assistant will not work unless Jira is running on a supported version
## Fix any duplicate email addresses #must
- Verify using SQL
> Duplicate email addresses are not supported by Jira Cloud and therefore can't be migrated with the Jira Cloud Migration Assistant. To avoid errors, you should find and fix any duplicate email addresses before migration. If user information is managed in an LDAP Server, you will need to update emails there and sync with Jira before the migration. If user information is managed locally, you can fix them through the Jira Server or Data Center user interface.
## Make sure you have the necessary permissions #must
- System Admin global permissions on the Server instance
- Exists in the target Cloud site
- Site Administrator Permission in the cloud
## Check for conflicts with group names #must
- Make sure that the groups in your Cloud Site don't have the same names as groups in Server
> Unless you are actively trying to merge them
- Delete or update add-on users so not to cause migration issues
- Verify via SQL
## Update firewall allowance rules #must
- None of the domains should be blocked by firewall or proxy
## Find a way to migrate apps #must
- Contact app vendors
## Check public access settings #must
- Projects
- Filters
- Filters
- Boards
- Dashboards
## Review server setup #mst
- at least 4gb Heap Allocation
- Open Files limit review
- Verify via support zip
## Check Server timezone #must for merging Cloud sites
- Switch to UTC is using any other timezone
> Add a system flag to the Jira Server instance -Duser.timezone=UTC as outlined in this article about updating documentation to include timezone details.
## Fix any duplicate shared configuration
## Storage limits
## Prepare the server instance
- Check data status
- All fields have value and are not null
-Any archived projects you wish to migrate are activated
## Prepare your cloud site
- Same Jira products enabled
- Same language
- User migration strategy
## Data backup
- Backup Jira Server site
- Backup Cloud site
## Run a test migration
- Done
## Notify Jira support
- Get in touch with Jira migration support
On the one hand, having all of your Jira products on a server may seem like a backup in and of itself. On the other hand, there are data migration best practices we should follow even if it’s just a precaution. No one has ever felt sorry for their data being too safe.
In addition, there are certain types of migration errors that can be resolved much faster with having a backup at hand.
Jira Cloud Migration Assistant is a free add-on Atlassian recommends using when migrating to the cloud. It accesses and evaluates your apps and helps migrate multiple projects.
Overall, the migration assistant offers a more stable and reliable migration experience. It automatically checks for certain errors. It makes sure all users have unique and valid emails, and makes sure that none of the project names and keys conflict with one another.
This is a step-by-step guide for importing your Jira Server data backup file into Jira Cloud.
Before we can proceed with the migration process, please make sure you meet the following prerequisites:
Once you are certain you are ready to migrate your Jira Server to Jira Data Center, you can proceed with an installation that’s much simpler than one would expect.
That’s it. You are all set. Well, unless your organization has specific needs such as continuous uptime, performance under heavy loads, and scalability, in which case you will need to set up a server cluster. You can find out more about setting up server clusters in this guide.
1595059664
With more of us using smartphones, the popularity of mobile applications has exploded. In the digital era, the number of people looking for products and services online is growing rapidly. Smartphone owners look for mobile applications that give them quick access to companies’ products and services. As a result, mobile apps provide customers with a lot of benefits in just one device.
Likewise, companies use mobile apps to increase customer loyalty and improve their services. Mobile Developers are in high demand as companies use apps not only to create brand awareness but also to gather information. For that reason, mobile apps are used as tools to collect valuable data from customers to help companies improve their offer.
There are many types of mobile applications, each with its own advantages. For example, native apps perform better, while web apps don’t need to be customized for the platform or operating system (OS). Likewise, hybrid apps provide users with comfortable user experience. However, you may be wondering how long it takes to develop an app.
To give you an idea of how long the app development process takes, here’s a short guide.
_Average time spent: two to five weeks _
This is the initial stage and a crucial step in setting the project in the right direction. In this stage, you brainstorm ideas and select the best one. Apart from that, you’ll need to do some research to see if your idea is viable. Remember that coming up with an idea is easy; the hard part is to make it a reality.
All your ideas may seem viable, but you still have to run some tests to keep it as real as possible. For that reason, when Web Developers are building a web app, they analyze the available ideas to see which one is the best match for the targeted audience.
Targeting the right audience is crucial when you are developing an app. It saves time when shaping the app in the right direction as you have a clear set of objectives. Likewise, analyzing how the app affects the market is essential. During the research process, App Developers must gather information about potential competitors and threats. This helps the app owners develop strategies to tackle difficulties that come up after the launch.
The research process can take several weeks, but it determines how successful your app can be. For that reason, you must take your time to know all the weaknesses and strengths of the competitors, possible app strategies, and targeted audience.
The outcomes of this stage are app prototypes and the minimum feasible product.
#android app #frontend #ios app #minimum viable product (mvp) #mobile app development #web development #android app development #app development #app development for ios and android #app development process #ios and android app development #ios app development #stages in app development
1669952228
In this tutorial, you'll learn: What is Dijkstra's Algorithm and how Dijkstra's algorithm works with the help of visual guides.
You can use algorithms in programming to solve specific problems through a set of precise instructions or procedures.
Dijkstra's algorithm is one of many graph algorithms you'll come across. It is used to find the shortest path from a fixed node to all other nodes in a graph.
There are different representations of Dijkstra's algorithm. You can either find the shortest path between two nodes, or the shortest path from a fixed node to the rest of the nodes in a graph.
In this article, you'll learn how Dijkstra's algorithm works with the help of visual guides.
Before we dive into more detailed visual examples, you need to understand how Dijkstra's algorithm works.
Although the theoretical explanation may seem a bit abstract, it'll help you understand the practical aspect better.
In a given graph containing different nodes, we are required to get the shortest path from a given node to the rest of the nodes.
These nodes can represent any object like the names of cities, letters, and so on.
Between each node is a number denoting the distance between two nodes, as you can see in the image below:
We usually work with two arrays – one for visited nodes, and another for unvisited nodes. You'll learn more about the arrays in the next section.
When a node is visited, the algorithm calculates how long it took to get to the node and stores the distance. If a shorter path to a node is found, the initial value assigned for the distance is updated.
Note that a node cannot be visited twice.
The algorithm runs recursively until all the nodes have been visited.
In this section, we'll take a look at a practical example that shows how Dijkstra's algorithm works.
Here's the graph we'll be working with:
We'll use the table below to put down the visited nodes and their distance from the fixed node:
NODE | SHORTEST DISTANCE FROM FIXED NODE |
---|---|
A | ∞ |
B | ∞ |
C | ∞ |
D | ∞ |
E | ∞ |
Visited nodes = []
Unvisited nodes = [A,B,C,D,E]
Above, we have a table showing each node and the shortest distance from the that node to the fixed node. We are yet to choose the fixed node.
Note that the distance for each node in the table is currently denoted as infinity (∞). This is because we don't know the shortest distance yet.
We also have two arrays – visited and unvisited. Whenever a node is visited, it is added to the visited nodes array.
Let's get started!
To simplify things, I'll break the process down into iterations. You'll see what happens in each step with the aid of diagrams.
The first iteration might seem confusing, but that's totally fine. Once we start repeating the process in each iteration, you'll have a clearer picture of how the algorithm works.
Step #1 - Pick an unvisited node
We'll choose A as the fixed node. So we'll find the shortest distance from A to every other node in the graph.
We're going to give A a distance of 0 because it is the initial node. So the table would look like this:
NODE | SHORTEST DISTANCE FROM FIXED NODE |
---|---|
A | 0 |
B | ∞ |
C | ∞ |
D | ∞ |
E | ∞ |
Step #2 - Find the distance from current node
The next thing to do after choosing a node is to find the distance from it to the unvisited nodes around it.
The two unvisited nodes directly linked to A are B and C.
To get the distance from A to B:
0 + 4 = 4
0 being the value of the current node (A), and 4 being the distance between A and B in the graph.
To get the distance from A to C:
0 + 2 = 2
Step #3 - Update table with known distances
In the last step, we got 4 and 2 as the values of B and C respectively. So we'll update the table with those values:
NODE | SHORTEST DISTANCE FROM FIXED NODE |
---|---|
A | 0 |
B | 4 |
C | 2 |
D | ∞ |
E | ∞ |
Step #4 - Update arrays
At this point, the first iteration is complete. We'll move node A to the visited nodes array:
Visited nodes = [A]
Unvisited nodes = [B,C,D,E]
Before we proceed to the next iteration, you should know the following:
Step #1 - Pick an unvisited node
We have four unvisited nodes — [B,C,D,E]. So how do you know which node to pick for the next iteration?
Well, we pick the node with the smallest known distance recorded in the table. Here's the table:
NODE | SHORTEST DISTANCE FROM FIXED NODE |
---|---|
A | 0 |
B | 4 |
C | 2 |
D | ∞ |
E | ∞ |
So we're going with node C.
Step #2 - Find the distance from current node
To find the distance from the current node to the fixed node, we have to consider the nodes linked to the current node.
The nodes linked to the current node are A and B.
But A has been visited in the previous iteration so it will not be linked to the current node. That is:
From the diagram above,
To find the distance from C to B:
2 + 1 = 3
2 above is recorded distance for node C while 1 is the distance between C and B in the graph.
Step #3 - Update table with known distances
In the last step, we got the value of B to be 3. In the first iteration, it was 4.
We're going to update the distance in the table to 3.
NODE | SHORTEST DISTANCE FROM FIXED NODE |
---|---|
A | 0 |
B | 3 |
C | 2 |
D | ∞ |
E | ∞ |
So, A --> B = 4 (First iteration).
A --> C --> B = 3 (Second iteration).
The algorithm has helped us find the shortest path to B from A.
Step #4 - Update arrays
We're done with the last visited node. Let's add it to the visited nodes array:
Visited nodes = [A,C]
Unvisited nodes = [B,D,E]
Step #1 - Pick an unvisited node
We're down to three unvisited nodes — [B,D,E]. From the array, B has the shortest known distance.
To restate what is going on in the diagram above:
Step #2 - Find the distance from current node
The nodes linked to the current node are D and E.
B (the current node) has a value of 3. Therefore,
For node D, 3 + 3 = 6.
For node E, 3 + 2 = 5.
Step #3 - Update table with known distances
NODE | SHORTEST DISTANCE FROM FIXED NODE |
---|---|
A | 0 |
B | 3 |
C | 2 |
D | 6 |
E | 5 |
Step #4 - Update arrays
Visited nodes = [A,C,B]
Unvisited nodes = [D,E]
Step #1 - Pick an unvisited node
Like other iterations, we'll go with the unvisited node with the shortest known distance. That is E.
Step #2 - Find the distance from current node
According to our table, E has a value of 5.
For D in the current iteration,
5 + 5 = 10.
The value gotten for D here is 10, which is greater than the recorded value of 6 in the previous iteration. For this reason, we'll not update the table.
Step #3 - Update table with known distances
Our table remains the same:
NODE | SHORTEST DISTANCE FROM FIXED NODE |
---|---|
A | 0 |
B | 3 |
C | 2 |
D | 6 |
E | 5 |
Step #4 - Update arrays
Visited nodes = [A,C,B,E]
Unvisited nodes = [D]
Step #1 - Pick an unvisited node
We're currently left with one node in the unvisited array — D.
Step #2 - Find the distance from current node
The algorithm has gotten to the last iteration. This is because all nodes linked to the current node have been visited already so we can't link to them.
Step #3 - Update table with known distances
Our table remains the same:
NODE | SHORTEST DISTANCE FROM FIXED NODE |
---|---|
A | 0 |
B | 3 |
C | 2 |
D | 6 |
E | 5 |
At this point, we have updated the table with the shortest distance from the fixed node to every other node in the graph.
Step #4 - Update arrays
Visited nodes = [A,C,B,E,D]
Unvisited nodes = []
As can be seen above, we have no nodes left to visit. Using Dijkstra's algorithm, we've found the shortest distance from the fixed node to others nodes in the graph.
The pseudocode example in this section was gotten from Wikipedia. Here it is:
1 function Dijkstra(Graph, source):
2
3 for each vertex v in Graph.Vertices:
4 dist[v] ← INFINITY
5 prev[v] ← UNDEFINED
6 add v to Q
7 dist[source] ← 0
8
9 while Q is not empty:
10 u ← vertex in Q with min dist[u]
11 remove u from Q
12
13 for each neighbor v of u still in Q:
14 alt ← dist[u] + Graph.Edges(u, v)
15 if alt < dist[v]:
16 dist[v] ← alt
17 prev[v] ← u
18
19 return dist[], prev[]
Here are some of the common applications of Dijkstra's algorithm:
In this article, we talked about Dijkstra's algorithm. It is used to find the shortest distance from a fixed node to all other nodes in a graph.
We started by giving a brief summary of how the algorithm works.
We then had a look at an example that further explained Dijkstra's algorithm in steps using visual guides.
We concluded with a pseudocode example and some of the applications of Dijkstra's algorithm.
Happy coding!
Original article source at https://www.freecodecamp.org
#algorithm #datastructures
1677907260
Node.js client for the official ChatGPT API.
This package is a Node.js wrapper around ChatGPT by OpenAI. TS batteries included. ✨
March 1, 2023
The official OpenAI chat completions API has been released, and it is now the default for this package! 🔥
Method | Free? | Robust? | Quality? |
---|---|---|---|
ChatGPTAPI | ❌ No | ✅ Yes | ✅️ Real ChatGPT models |
ChatGPTUnofficialProxyAPI | ✅ Yes | ☑️ Maybe | ✅ Real ChatGPT |
Note: We strongly recommend using ChatGPTAPI
since it uses the officially supported API from OpenAI. We may remove support for ChatGPTUnofficialProxyAPI
in a future release.
ChatGPTAPI
- Uses the gpt-3.5-turbo-0301
model with the official OpenAI chat completions API (official, robust approach, but it's not free)ChatGPTUnofficialProxyAPI
- Uses an unofficial proxy server to access ChatGPT's backend API in a way that circumvents Cloudflare (uses the real ChatGPT and is pretty lightweight, but relies on a third-party server and is rate-limited)To run the CLI, you'll need an OpenAI API key:
export OPENAI_API_KEY="sk-TODO"
npx chatgpt "your prompt here"
By default, the response is streamed to stdout, the results are stored in a local config file, and every invocation starts a new conversation. You can use -c
to continue the previous conversation and --no-stream
to disable streaming.
Under the hood, the CLI uses ChatGPTAPI
with text-davinci-003
to mimic ChatGPT.
Usage:
$ chatgpt <prompt>
Commands:
<prompt> Ask ChatGPT a question
rm-cache Clears the local message cache
ls-cache Prints the local message cache path
For more info, run any command with the `--help` flag:
$ chatgpt --help
$ chatgpt rm-cache --help
$ chatgpt ls-cache --help
Options:
-c, --continue Continue last conversation (default: false)
-d, --debug Enables debug logging (default: false)
-s, --stream Streams the response (default: true)
-s, --store Enables the local message cache (default: true)
-t, --timeout Timeout in milliseconds
-k, --apiKey OpenAI API key
-n, --conversationName Unique name for the conversation
-h, --help Display this message
-v, --version Display version number
npm install chatgpt
Make sure you're using node >= 18
so fetch
is available (or node >= 14
if you install a fetch polyfill).
To use this module from Node.js, you need to pick between two methods:
Method | Free? | Robust? | Quality? |
---|---|---|---|
ChatGPTAPI | ❌ No | ✅ Yes | ✅️ Real ChatGPT models |
ChatGPTUnofficialProxyAPI | ✅ Yes | ☑️ Maybe | ✅ Real ChatGPT |
ChatGPTAPI
- Uses the gpt-3.5-turbo-0301
model with the official OpenAI chat completions API (official, robust approach, but it's not free). You can override the model, completion params, and system message to fully customize your assistant.
ChatGPTUnofficialProxyAPI
- Uses an unofficial proxy server to access ChatGPT's backend API in a way that circumvents Cloudflare (uses the real ChatGPT and is pretty lightweight, but relies on a third-party server and is rate-limited)
Both approaches have very similar APIs, so it should be simple to swap between them.
Note: We strongly recommend using ChatGPTAPI
since it uses the officially supported API from OpenAI. We may remove support for ChatGPTUnofficialProxyAPI
in a future release.
Sign up for an OpenAI API key and store it in your environment.
import { ChatGPTAPI } from 'chatgpt'
async function example() {
const api = new ChatGPTAPI({
apiKey: process.env.OPENAI_API_KEY
})
const res = await api.sendMessage('Hello World!')
console.log(res.text)
}
You can override the default model
(gpt-3.5-turbo-0301
) and any OpenAI chat completion params using completionParams
:
const api = new ChatGPTAPI({
apiKey: process.env.OPENAI_API_KEY,
completionParams: {
temperature: 0.5,
top_p: 0.8
}
})
If you want to track the conversation, you'll need to pass the parentMessageId
like this:
const api = new ChatGPTAPI({ apiKey: process.env.OPENAI_API_KEY })
// send a message and wait for the response
let res = await api.sendMessage('What is OpenAI?')
console.log(res.text)
// send a follow-up
res = await api.sendMessage('Can you expand on that?', {
parentMessageId: res.id
})
console.log(res.text)
// send another follow-up
res = await api.sendMessage('What were we talking about?', {
parentMessageId: res.id
})
console.log(res.text)
You can add streaming via the onProgress
handler:
const res = await api.sendMessage('Write a 500 word essay on frogs.', {
// print the partial response as the AI is "typing"
onProgress: (partialResponse) => console.log(partialResponse.text)
})
// print the full text at the end
console.log(res.text)
You can add a timeout using the timeoutMs
option:
// timeout after 2 minutes (which will also abort the underlying HTTP request)
const response = await api.sendMessage(
'write me a really really long essay on frogs',
{
timeoutMs: 2 * 60 * 1000
}
)
If you want to see more info about what's actually being sent to OpenAI's chat completions API, set the debug: true
option in the ChatGPTAPI
constructor:
const api = new ChatGPTAPI({
apiKey: process.env.OPENAI_API_KEY,
debug: true
})
We default to a basic systemMessage
. You can override this in either the ChatGPTAPI
constructor or sendMessage
:
const res = await api.sendMessage('what is the answer to the universe?', {
systemMessage: `You are ChatGPT, a large language model trained by OpenAI. You answer as concisely as possible for each responseIf you are generating a list, do not have too many items.
Current date: ${new Date().toISOString()}\n\n`
})
Note that we automatically handle appending the previous messages to the prompt and attempt to optimize for the available tokens (which defaults to 4096
).
Usage in CommonJS (Dynamic import)
async function example() {
// To use ESM in CommonJS, you can use a dynamic import
const { ChatGPTAPI } = await import('chatgpt')
const api = new ChatGPTAPI({ apiKey: process.env.OPENAI_API_KEY })
const res = await api.sendMessage('Hello World!')
console.log(res.text)
}
The API for ChatGPTUnofficialProxyAPI
is almost exactly the same. You just need to provide a ChatGPT accessToken
instead of an OpenAI API key.
import { ChatGPTUnofficialProxyAPI } from 'chatgpt'
async function example() {
const api = new ChatGPTUnofficialProxyAPI({
accessToken: process.env.OPENAI_ACCESS_TOKEN
})
const res = await api.sendMessage('Hello World!')
console.log(res.text)
}
See demos/demo-reverse-proxy for a full example:
npx tsx demos/demo-reverse-proxy.ts
ChatGPTUnofficialProxyAPI
messages also contain a conversationid
in addition to parentMessageId
, since the ChatGPT webapp can't reference messages across
You can override the reverse proxy by passing apiReverseProxyUrl
:
const api = new ChatGPTUnofficialProxyAPI({
accessToken: process.env.OPENAI_ACCESS_TOKEN,
apiReverseProxyUrl: 'https://your-example-server.com/api/conversation'
})
Known reverse proxies run by community members include:
Reverse Proxy URL | Author | Rate Limits | Last Checked |
---|---|---|---|
https://chat.duti.tech/api/conversation | @acheong08 | 120 req/min by IP | 2/19/2023 |
https://gpt.pawan.krd/backend-api/conversation | @PawanOsman | ? | 2/19/2023 |
Note: info on how the reverse proxies work is not being published at this time in order to prevent OpenAI from disabling access.
To use ChatGPTUnofficialProxyAPI
, you'll need an OpenAI access token from the ChatGPT webapp. To do this, you can use any of the following methods which take an email
and password
and return an access token:
These libraries work with email + password accounts (e.g., they do not support accounts where you auth via Microsoft / Google).
Alternatively, you can manually get an accessToken
by logging in to the ChatGPT webapp and then opening https://chat.openai.com/api/auth/session
, which will return a JSON object containing your accessToken
string.
Access tokens last for days.
Note: using a reverse proxy will expose your access token to a third-party. There shouldn't be any adverse effects possible from this, but please consider the risks before using this method.
See the auto-generated docs for more info on methods and parameters.
Most of the demos use ChatGPTAPI
. It should be pretty easy to convert them to use ChatGPTUnofficialProxyAPI
if you'd rather use that approach. The only thing that needs to change is how you initialize the api with an accessToken
instead of an apiKey
.
To run the included demos:
OPENAI_API_KEY
in .envA basic demo is included for testing purposes:
npx tsx demos/demo.ts
A demo showing on progress handler:
npx tsx demos/demo-on-progress.ts
The on progress demo uses the optional onProgress
parameter to sendMessage
to receive intermediary results as ChatGPT is "typing".
npx tsx demos/demo-conversation.ts
A persistence demo shows how to store messages in Redis for persistence:
npx tsx demos/demo-persistence.ts
Any keyv adaptor is supported for persistence, and there are overrides if you'd like to use a different way of storing / retrieving messages.
Note that persisting message is required for remembering the context of previous conversations beyond the scope of the current Node.js process, since by default, we only store messages in memory. Here's an external demo of using a completely custom database solution to persist messages.
Note: Persistence is handled automatically when using ChatGPTUnofficialProxyAPI
because it is connecting indirectly to ChatGPT.
All of these awesome projects are built using the chatgpt
package. 🤯
If you create a cool integration, feel free to open a PR and add it to the list.
node >= 14
.fetch
is installed.chatgpt
, we recommend using it only from your backend APIPrevious Updates
Feb 19, 2023
We now provide three ways of accessing the unofficial ChatGPT API, all of which have tradeoffs:
Method | Free? | Robust? | Quality? |
---|---|---|---|
ChatGPTAPI | ❌ No | ✅ Yes | ☑️ Mimics ChatGPT |
ChatGPTUnofficialProxyAPI | ✅ Yes | ☑️ Maybe | ✅ Real ChatGPT |
ChatGPTAPIBrowser (v3) | ✅ Yes | ❌ No | ✅ Real ChatGPT |
Note: I recommend that you use either ChatGPTAPI
or ChatGPTUnofficialProxyAPI
.
ChatGPTAPI
- Uses text-davinci-003
to mimic ChatGPT via the official OpenAI completions API (most robust approach, but it's not free and doesn't use a model fine-tuned for chat)ChatGPTUnofficialProxyAPI
- Uses an unofficial proxy server to access ChatGPT's backend API in a way that circumvents Cloudflare (uses the real ChatGPT and is pretty lightweight, but relies on a third-party server and is rate-limited)ChatGPTAPIBrowser
- (deprecated; v3.5.1 of this package) Uses Puppeteer to access the official ChatGPT webapp (uses the real ChatGPT, but very flaky, heavyweight, and error prone)Feb 5, 2023
OpenAI has disabled the leaked chat model we were previously using, so we're now defaulting to text-davinci-003
, which is not free.
We've found several other hidden, fine-tuned chat models, but OpenAI keeps disabling them, so we're searching for alternative workarounds.
Feb 1, 2023
This package no longer requires any browser hacks – it is now using the official OpenAI completions API with a leaked model that ChatGPT uses under the hood. 🔥
import { ChatGPTAPI } from 'chatgpt'
const api = new ChatGPTAPI({
apiKey: process.env.OPENAI_API_KEY
})
const res = await api.sendMessage('Hello World!')
console.log(res.text)
Please upgrade to chatgpt@latest
(at least v4.0.0). The updated version is significantly more lightweight and robust compared with previous versions. You also don't have to worry about IP issues or rate limiting.
Huge shoutout to @waylaidwanderer for discovering the leaked chat model!
If you run into any issues, we do have a pretty active Discord with a bunch of ChatGPT hackers from the Node.js & Python communities.
Lastly, please consider starring this repo and following me on twitter to help support the project.
Thanks && cheers, Travis
Author: Transitive-bullshit
Source Code: https://github.com/transitive-bullshit/chatgpt-api
License: MIT license