1656571938
What is Coin Cloud ATM Machine? - +1(888)-678-4583
What Is Coincloud Bitcoin ATM Machine?
The world is currently going towards cryptocurrency because digital currency has become a vital asset. Because of the increasing demand and popularity, many people want to purchase the cryptocurrencies such as Bitcoin, Ethereum, Bitcoin Cash, and much more. Unlike before, you do not require to reach the crypto exchange to make the transaction. You can now use the cryptocurrency ATM to quickly buy and sell crypto coins. At present, Coincloud ATM is highly accessed by crypto users.
It is similar to the bitcoin ATM, but it does many things beyond the regular crypto ATMs. This kiosk lets the users purchase and sell the cryptocurrency of their choice straight on the machine with cash. You can consider the ATM as the currency exchange kiosk. It renders ultimate power and flexibility to go from fiat to digital currency and vice versa. As said earlier, Coin Cloud Bitcoin ATM is one of the majorly used cryptocurrency ATMs for buying and selling bitcoin.
Even though many types of cryptocurrencies are in use now, bitcoin is beneficial and valuable. The value of bitcoin has been sky-rocketing in recent times. The money you invest in this coin will give you tons of profits in the future. So, when you decide to buy bitcoin, you have to look for the bitcoin ATM in your nearby location. It helps you to complete the transaction without confronting hassles.
Scroll down the page to know more about the Coin Cloud Bitcoin ATM and its features!
Before getting into the topic, it is necessary to know major information about the Coin Cloud. It is the popular bitcoin ATM Company headquartered in Las Vegas. This brand has located its ATM in more than 650 locations nationwide. It has one of the fastest and largest growing networks of two-way bitcoin ATMs throughout the world. Yes! This ATM lets you sell and purchase bitcoin as per your requirements.
So far, the Coin Cloud network has helped over 144000 customers to purchase and sell cryptocurrency. The company started its service in 2004. If you want to find the CoinCloud ATM Near me, you can visit the website at CoinCloudATM.com. So, you will find and access the reliable bitcoin ATM quickly.
How To Find a CoinCloud ATM?
There are so many places in the USA where you can find a coincloud ATM. There are more than 12000 ATMs available in the USA, Where you can find an ATM and do transactions. If you want to find a ATM machine near your location, Then you need to follow some steps so, that you can find an ATM near your location very easily.
Steps To Follow:-
First, you need to open your map and search for the nearest coincloud ATM, Then you’ll be able to check how many ATMs are near to your location.
While finding the nearest ATM to your location make sure that the ATM which you’ve found is licensed and legal. As there are many ATMs who don’t have licenses.
Along with it, if you don’t want to find a ATM through Google map, Then you can visit a retail store, shop, restaurant, mall, or airport near to your place. You’ll definitely find a crypto ATM and you can do transactions hassle-free.
These are some places where you can find a ATM and you can easily find an ATM. As there are many ATMs near your place, you don’t need to do any hassle to find them.
How do We Use Coin Cloud ATM Machine?
- You have to create an account to purchase the bitcoin in the coincloud atm to get started. Ensure you have a mobile number and cash.
- Once you enter the mobile number, you will get the verification text message.
- It is just for verifying your identity. So, when you do it correctly, you can complete the transaction easily.
- Your account will be called unverified if you access only your phone number. In this case, you get the lifetime transaction limit of $100 – $1999.
- Verifying your account will maximize your daily and lifetime transaction limits. It gives you the limit of $2999/transaction and $10000/day. It also renders no lifetime limit, so you can trade the bitcoin as much as you want.
- Scanning your valid ID proof and taking a photo of yourself at the machine is enough to verify your account. Coin Cloud has designed the whole process straightforward and easier to process.
- It allows the users to exchange a single type of currency for another without getting into the hassle of setting up the account and waiting longer for completing the transactions.
What are the Features of Coin Cloud Bitcoin ATM?
The coincloud atm is more than the bitcoin ATMs due to the following great features.
User-friendly touch screen Like your mobile, Bitcoin ATMs have touchscreen interfaces. So, you are no longer worrying about accessing the buttons because it does not work properly many times. This touchscreen interface is easier to use and navigate for all users.
In the modern age, many viruses are spreading throughout the world. So, keeping yourself safe is mandatory. This machine is extremely easier to clean, and thus you will not think much about accessing this ATM.
- Bill dispenser
Did you know that only 20% of the bitcoin ATMs have the bill dispenser? Coin Cloud ATM is one among them. It lets you cash out the bitcoin any time you wish. So, you will buy and sell whenever you want. This ATM has many advance and innovative features. It makes your bitcoin buying and selling experience worthy.
- Presence of a multi-function camera
Every atm machine has a camera, which performs two important things: taking your picture and scanning your mobile use coin cloud wallet QR code. You must need a wallet to perform the bitcoin ATM to buy or sell the cryptocurrencies because it acts as the storage place to keep your coins safe.
The availability of the multi-function camera on the machine maximizes your security. It minimizes the chance of stealing your ID and helps you interact with the machine easily. It also eradicates the need to find the code scanner. Hold your mobile near the camera. Within a few seconds, the high-quality camera will find the code automatically.
- Companion app
This feature is available in almost all the large bitcoin ATMs. Many bitcoin ATM companies have their app. Similarly, Coin Cloud has the Coin Cloud wallet app, making purchasing and selling at this machine much easier and quicker. You should get this wallet before starting your transaction.
With the Coin Cloud ATM machine, you can use any mobile wallet as per your needs. It does not restrict you regarding this. But, accessing the Coin Cloud Wallet makes everything goes smoother and faster. So, you will save more of your time and effort in many ways. It is especially true when you decide to sell the bitcoins on this machine.
While using this wallet, you can discover the machines easily, set up the sell transaction in advance, and reserve your cash for up to 48hours. Then, you can withdraw the money immediately. A single confirmation with both machine and wallet is enough. It takes about 10minutes for every transaction.
Content Source: https://bitcoinatmsupportus.org/coincloud-atm/
What is GEEK
Buddha Community
1653475560
A Pure PHP Implementation Of The MessagePack Serialization Format
msgpack.php
A pure PHP implementation of the MessagePack serialization format.
Features
- Fully compliant with the latest MessagePack specification
- Supports streaming unpacking
- Supports unsigned 64-bit integers handling
- Supports object serialization
- Fully tested
- Relatively fast
Installation
The recommended way to install the library is through Composer:
composer require rybakit/msgpack
Usage
Packing
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.
Packing options
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,MapandBin. 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);
Unpacking
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
Unpacking options
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) {...}
Custom types
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.
Type objects
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.
Type transformers
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.
Extensions
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.
Exceptions
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.
Tests
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
Fuzzing
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
Performance
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.
License
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
1648641360
Treebender: A Symbolic Natural Language Parsing Library for Rust
Treebender
A symbolic natural language parsing library for Rust, inspired by HDPSG.
What is this?
This is a library for parsing natural or constructed languages into syntax trees and feature structures. There's no machine learning or probabilistic models, everything is hand-crafted and deterministic.
You can find out more about the motivations of this project in this blog post.
But what are you using it for?
I'm using this to parse a constructed language for my upcoming xenolinguistics game, Themengi.
Motivation
Using a simple 80-line grammar, introduced in the tutorial below, we can parse a simple subset of English, checking reflexive pronoun binding, case, and number agreement.
$ cargo run --bin cli examples/reflexives.fgr
> she likes himself
Parsed 0 trees
> her likes herself
Parsed 0 trees
> she like herself
Parsed 0 trees
> she likes herself
Parsed 1 tree
(0..3: S
(0..1: N (0..1: she))
(1..2: TV (1..2: likes))
(2..3: N (2..3: herself)))
[
child-2: [
case: acc
pron: ref
needs_pron: #0 she
num: sg
child-0: [ word: herself ]
]
child-1: [
tense: nonpast
child-0: [ word: likes ]
num: #1 sg
]
child-0: [
child-0: [ word: she ]
case: nom
pron: #0
num: #1
]
]
Low resource language? Low problem! No need to train on gigabytes of text, just write a grammar using your brain. Let's hypothesize that in American Sign Language, topicalized nouns (expressed with raised eyebrows) must appear first in the sentence. We can write a small grammar (18 lines), and plug in some sentences:
$ cargo run --bin cli examples/asl-wordorder.fgr -n
> boy sit
Parsed 1 tree
(0..2: S
(0..1: NP ((0..1: N (0..1: boy))))
(1..2: IV (1..2: sit)))
> boy throw ball
Parsed 1 tree
(0..3: S
(0..1: NP ((0..1: N (0..1: boy))))
(1..2: TV (1..2: throw))
(2..3: NP ((2..3: N (2..3: ball)))))
> ball nm-raised-eyebrows boy throw
Parsed 1 tree
(0..4: S
(0..2: NP
(0..1: N (0..1: ball))
(1..2: Topic (1..2: nm-raised-eyebrows)))
(2..3: NP ((2..3: N (2..3: boy))))
(3..4: TV (3..4: throw)))
> boy throw ball nm-raised-eyebrows
Parsed 0 trees
Tutorial
As an example, let's say we want to build a parser for English reflexive pronouns (himself, herself, themselves, themself, itself). We'll also support number ("He likes X" v.s. "They like X") and simple embedded clauses ("He said that they like X").
Grammar files are written in a custom language, similar to BNF, called Feature GRammar (.fgr). There's a VSCode syntax highlighting extension for these files available as fgr-syntax.
We'll start by defining our lexicon. The lexicon is the set of terminal symbols (symbols in the actual input) that the grammar will match. Terminal symbols must start with a lowercase letter, and non-terminal symbols must start with an uppercase letter.
// pronouns
N -> he
N -> him
N -> himself
N -> she
N -> her
N -> herself
N -> they
N -> them
N -> themselves
N -> themself
// names, lowercase as they are terminals
N -> mary
N -> sue
N -> takeshi
N -> robert
// complementizer
Comp -> that
// verbs -- intransitive, transitive, and clausal
IV -> falls
IV -> fall
IV -> fell
TV -> likes
TV -> like
TV -> liked
CV -> says
CV -> say
CV -> said
Next, we can add our sentence rules (they must be added at the top, as the first rule in the file is assumed to be the top-level rule):
// sentence rules
S -> N IV
S -> N TV N
S -> N CV Comp S
// ... previous lexicon ...
Assuming this file is saved as examples/no-features.fgr (which it is :wink:), we can test this file with the built-in CLI:
$ cargo run --bin cli examples/no-features.fgr
> he falls
Parsed 1 tree
(0..2: S
(0..1: N (0..1: he))
(1..2: IV (1..2: falls)))
[
child-1: [ child-0: [ word: falls ] ]
child-0: [ child-0: [ word: he ] ]
]
> he falls her
Parsed 0 trees
> he likes her
Parsed 1 tree
(0..3: S
(0..1: N (0..1: he))
(1..2: TV (1..2: likes))
(2..3: N (2..3: her)))
[
child-2: [ child-0: [ word: her ] ]
child-1: [ child-0: [ word: likes ] ]
child-0: [ child-0: [ word: he ] ]
]
> he likes
Parsed 0 trees
> he said that he likes her
Parsed 1 tree
(0..6: S
(0..1: N (0..1: he))
(1..2: CV (1..2: said))
(2..3: Comp (2..3: that))
(3..6: S
(3..4: N (3..4: he))
(4..5: TV (4..5: likes))
(5..6: N (5..6: her))))
[
child-0: [ child-0: [ word: he ] ]
child-2: [ child-0: [ word: that ] ]
child-1: [ child-0: [ word: said ] ]
child-3: [
child-2: [ child-0: [ word: her ] ]
child-1: [ child-0: [ word: likes ] ]
child-0: [ child-0: [ word: he ] ]
]
]
> he said that he
Parsed 0 trees
This grammar already parses some correct sentences, and blocks some trivially incorrect ones. However, it doesn't care about number, case, or reflexives right now:
> she likes himself // unbound reflexive pronoun
Parsed 1 tree
(0..3: S
(0..1: N (0..1: she))
(1..2: TV (1..2: likes))
(2..3: N (2..3: himself)))
[
child-0: [ child-0: [ word: she ] ]
child-2: [ child-0: [ word: himself ] ]
child-1: [ child-0: [ word: likes ] ]
]
> him like her // incorrect case on the subject pronoun, should be nominative
// (he) instead of accusative (him)
Parsed 1 tree
(0..3: S
(0..1: N (0..1: him))
(1..2: TV (1..2: like))
(2..3: N (2..3: her)))
[
child-0: [ child-0: [ word: him ] ]
child-1: [ child-0: [ word: like ] ]
child-2: [ child-0: [ word: her ] ]
]
> he like her // incorrect verb number agreement
Parsed 1 tree
(0..3: S
(0..1: N (0..1: he))
(1..2: TV (1..2: like))
(2..3: N (2..3: her)))
[
child-2: [ child-0: [ word: her ] ]
child-1: [ child-0: [ word: like ] ]
child-0: [ child-0: [ word: he ] ]
]
To fix this, we need to add features to our lexicon, and restrict the sentence rules based on features.
Features are added with square brackets, and are key: value pairs separated by commas. **top** is a special feature value, which basically means "unspecified" -- we'll come back to it later. Features that are unspecified are also assumed to have a **top** value, but sometimes explicitly stating top is more clear.
/// Pronouns
// The added features are:
// * num: sg or pl, whether this noun wants a singular verb (likes) or
// a plural verb (like). note this is grammatical number, so for example
// singular they takes plural agreement ("they like X", not *"they likes X")
// * case: nom or acc, whether this noun is nominative or accusative case.
// nominative case goes in the subject, and accusative in the object.
// e.g., "he fell" and "she likes him", not *"him fell" and *"her likes he"
// * pron: he, she, they, or ref -- what type of pronoun this is
// * needs_pron: whether this is a reflexive that needs to bind to another
// pronoun.
N[ num: sg, case: nom, pron: he ] -> he
N[ num: sg, case: acc, pron: he ] -> him
N[ num: sg, case: acc, pron: ref, needs_pron: he ] -> himself
N[ num: sg, case: nom, pron: she ] -> she
N[ num: sg, case: acc, pron: she ] -> her
N[ num: sg, case: acc, pron: ref, needs_pron: she] -> herself
N[ num: pl, case: nom, pron: they ] -> they
N[ num: pl, case: acc, pron: they ] -> them
N[ num: pl, case: acc, pron: ref, needs_pron: they ] -> themselves
N[ num: sg, case: acc, pron: ref, needs_pron: they ] -> themself
// Names
// The added features are:
// * num: sg, as people are singular ("mary likes her" / *"mary like her")
// * case: **top**, as names can be both subjects and objects
// ("mary likes her" / "she likes mary")
// * pron: whichever pronoun the person uses for reflexive agreement
// mary pron: she => mary likes herself
// sue pron: they => sue likes themself
// takeshi pron: he => takeshi likes himself
N[ num: sg, case: **top**, pron: she ] -> mary
N[ num: sg, case: **top**, pron: they ] -> sue
N[ num: sg, case: **top**, pron: he ] -> takeshi
N[ num: sg, case: **top**, pron: he ] -> robert
// Complementizer doesn't need features
Comp -> that
// Verbs -- intransitive, transitive, and clausal
// The added features are:
// * num: sg, pl, or **top** -- to match the noun numbers.
// **top** will match either sg or pl, as past-tense verbs in English
// don't agree in number: "he fell" and "they fell" are both fine
// * tense: past or nonpast -- this won't be used for agreement, but will be
// copied into the final feature structure, and the client code could do
// something with it
IV[ num: sg, tense: nonpast ] -> falls
IV[ num: pl, tense: nonpast ] -> fall
IV[ num: **top**, tense: past ] -> fell
TV[ num: sg, tense: nonpast ] -> likes
TV[ num: pl, tense: nonpast ] -> like
TV[ num: **top**, tense: past ] -> liked
CV[ num: sg, tense: nonpast ] -> says
CV[ num: pl, tense: nonpast ] -> say
CV[ num: **top**, tense: past ] -> said
Now that our lexicon is updated with features, we can update our sentence rules to constrain parsing based on those features. This uses two new features, tags and unification. Tags allow features to be associated between nodes in a rule, and unification controls how those features are compatible. The rules for unification are:
- A string feature can unify with a string feature with the same value
- A top feature can unify with anything, and the nodes are merged
- A complex feature ([ ... ] structure) is recursively unified with another complex feature.
If unification fails anywhere, the parse is aborted and the tree is discarded. This allows the programmer to discard trees if features don't match.
// Sentence rules
// Intransitive verb:
// * Subject must be nominative case
// * Subject and verb must agree in number (copied through #1)
S -> N[ case: nom, num: #1 ] IV[ num: #1 ]
// Transitive verb:
// * Subject must be nominative case
// * Subject and verb must agree in number (copied through #2)
// * If there's a reflexive in the object position, make sure its `needs_pron`
// feature matches the subject's `pron` feature. If the object isn't a
// reflexive, then its `needs_pron` feature will implicitly be `**top**`, so
// will unify with anything.
S -> N[ case: nom, pron: #1, num: #2 ] TV[ num: #2 ] N[ case: acc, needs_pron: #1 ]
// Clausal verb:
// * Subject must be nominative case
// * Subject and verb must agree in number (copied through #1)
// * Reflexives can't cross clause boundaries (*"He said that she likes himself"),
// so we can ignore reflexives and delegate to inner clause rule
S -> N[ case: nom, num: #1 ] CV[ num: #1 ] Comp S
Now that we have this augmented grammar (available as examples/reflexives.fgr), we can try it out and see that it rejects illicit sentences that were previously accepted, while still accepting valid ones:
> he fell
Parsed 1 tree
(0..2: S
(0..1: N (0..1: he))
(1..2: IV (1..2: fell)))
[
child-1: [
child-0: [ word: fell ]
num: #0 sg
tense: past
]
child-0: [
pron: he
case: nom
num: #0
child-0: [ word: he ]
]
]
> he like him
Parsed 0 trees
> he likes himself
Parsed 1 tree
(0..3: S
(0..1: N (0..1: he))
(1..2: TV (1..2: likes))
(2..3: N (2..3: himself)))
[
child-1: [
num: #0 sg
child-0: [ word: likes ]
tense: nonpast
]
child-2: [
needs_pron: #1 he
num: sg
child-0: [ word: himself ]
pron: ref
case: acc
]
child-0: [
child-0: [ word: he ]
pron: #1
num: #0
case: nom
]
]
> he likes herself
Parsed 0 trees
> mary likes herself
Parsed 1 tree
(0..3: S
(0..1: N (0..1: mary))
(1..2: TV (1..2: likes))
(2..3: N (2..3: herself)))
[
child-0: [
pron: #0 she
num: #1 sg
case: nom
child-0: [ word: mary ]
]
child-1: [
tense: nonpast
child-0: [ word: likes ]
num: #1
]
child-2: [
child-0: [ word: herself ]
num: sg
pron: ref
case: acc
needs_pron: #0
]
]
> mary likes themself
Parsed 0 trees
> sue likes themself
Parsed 1 tree
(0..3: S
(0..1: N (0..1: sue))
(1..2: TV (1..2: likes))
(2..3: N (2..3: themself)))
[
child-0: [
pron: #0 they
child-0: [ word: sue ]
case: nom
num: #1 sg
]
child-1: [
tense: nonpast
num: #1
child-0: [ word: likes ]
]
child-2: [
needs_pron: #0
case: acc
pron: ref
child-0: [ word: themself ]
num: sg
]
]
> sue likes himself
Parsed 0 trees
If this is interesting to you and you want to learn more, you can check out my blog series, the excellent textbook Syntactic Theory: A Formal Introduction (2nd ed.), and the DELPH-IN project, whose work on the LKB inspired this simplified version.
Using from code
I need to write this section in more detail, but if you're comfortable with Rust, I suggest looking through the codebase. It's not perfect, it started as one of my first Rust projects (after migrating through F# -> TypeScript -> C in search of the right performance/ergonomics tradeoff), and it could use more tests, but overall it's not too bad.
Basically, the processing pipeline is:
- Make a
Grammarstruct
Grammaris defined inrules.rs.- The easiest way to make a
GrammarisGrammar::parse_from_file, which is mostly a hand-written recusive descent parser inparse_grammar.rs. Yes, I recognize the irony here.
- It takes input (in
Grammar::parse, which does everything for you, orGrammar::parse_chart, which just does the chart) - The input is first chart-parsed in
earley.rs - Then, a forest is built from the chart, in
forest.rs, using an algorithm I found in a very useful blog series I forget the URL for, because the algorithms in the academic literature for this are... weird. - Finally, the feature unification is used to prune the forest down to only valid trees. It would be more efficient to do this during parsing, but meh.
The most interesting thing you can do via code and not via the CLI is probably getting at the raw feature DAG, as that would let you do things like pronoun coreference. The DAG code is in featurestructure.rs, and should be fairly approachable -- there's a lot of Rust ceremony around Rc<RefCell<...>> because using an arena allocation crate seemed too harlike overkill, but that is somewhat mitigated by the NodeRef type alias. Hit me up at https://vgel.me/contact if you need help with anything here!
Download Details:
Author: vgel
Source Code: https://github.com/vgel/treebender
License: MIT License
1667488080
Py Rouge: A Full Python Implementation Of The ROUGE Metric
Py-rouge
A full Python implementation of the ROUGE metric, producing same results as in the official perl implementation.
Important remarks
- The original Porter stemmer in NLTK is slightly different than the one use in the official ROUGE perl script as it has been written by end. Therefore, there might be slightly different stems for certain words. For DUC2004 dataset, I have identified these words and this script produces same stems.
- The official ROUGE perl script use resampling strategy to compute the average with confidence intervals. Therefore, we might have a difference
<3e-5for ROUGE-L as well as ROUGE-W and<4e-5for ROUGE-N. - Finally, ROUGE-1.5.5. has a bug: should have $tmpTextLen += $sLen at line 2101. Here, the last sentence, $limitBytes is taken instead of $limitBytes-$tmpTextLen (as $tmpTextLen is never updated with bytes length limit). It has been fixed in this code. This bug does not have a consequence for the default evaluation
-b 665.
In case of doubts, please see all the implemented tests to compare outputs between the official ROUGE-1.5.5 and this script.
Installation
Package is uploaded on PyPI <https://pypi.org/project/py-rouge>_.
You can install it with pip:
pip install py-rouge
or do it manually:
git clone https://github.com/Diego999/py-rouge
cd py-rouge
python setup.py install
Issues/Pull Requests/Feedbacks
Don't hesitate to contact for any feedback or create issues/pull requests (especially if you want to rewrite the stemmer implemented in ROUGE-1.5.5 in python ;)).
Example
import rouge
def prepare_results(m, p, r, f):
return '\t{}:\t{}: {:5.2f}\t{}: {:5.2f}\t{}: {:5.2f}'.format(m, 'P', 100.0 * p, 'R', 100.0 * r, 'F1', 100.0 * f)
for aggregator in ['Avg', 'Best', 'Individual']:
print('Evaluation with {}'.format(aggregator))
apply_avg = aggregator == 'Avg'
apply_best = aggregator == 'Best'
evaluator = rouge.Rouge(metrics=['rouge-n', 'rouge-l', 'rouge-w'],
max_n=4,
limit_length=True,
length_limit=100,
length_limit_type='words',
apply_avg=apply_avg,
apply_best=apply_best,
alpha=0.5, # Default F1_score
weight_factor=1.2,
stemming=True)
hypothesis_1 = "King Norodom Sihanouk has declined requests to chair a summit of Cambodia 's top political leaders , saying the meeting would not bring any progress in deadlocked negotiations to form a government .\nGovernment and opposition parties have asked King Norodom Sihanouk to host a summit meeting after a series of post-election negotiations between the two opposition groups and Hun Sen 's party to form a new government failed .\nHun Sen 's ruling party narrowly won a majority in elections in July , but the opposition _ claiming widespread intimidation and fraud _ has denied Hun Sen the two-thirds vote in parliament required to approve the next government .\n"
references_1 = ["Prospects were dim for resolution of the political crisis in Cambodia in October 1998.\nPrime Minister Hun Sen insisted that talks take place in Cambodia while opposition leaders Ranariddh and Sam Rainsy, fearing arrest at home, wanted them abroad.\nKing Sihanouk declined to chair talks in either place.\nA U.S. House resolution criticized Hun Sen's regime while the opposition tried to cut off his access to loans.\nBut in November the King announced a coalition government with Hun Sen heading the executive and Ranariddh leading the parliament.\nLeft out, Sam Rainsy sought the King's assurance of Hun Sen's promise of safety and freedom for all politicians.",
"Cambodian prime minister Hun Sen rejects demands of 2 opposition parties for talks in Beijing after failing to win a 2/3 majority in recent elections.\nSihanouk refuses to host talks in Beijing.\nOpposition parties ask the Asian Development Bank to stop loans to Hun Sen's government.\nCCP defends Hun Sen to the US Senate.\nFUNCINPEC refuses to share the presidency.\nHun Sen and Ranariddh eventually form a coalition at summit convened by Sihanouk.\nHun Sen remains prime minister, Ranariddh is president of the national assembly, and a new senate will be formed.\nOpposition leader Rainsy left out.\nHe seeks strong assurance of safety should he return to Cambodia.\n",
]
hypothesis_2 = "China 's government said Thursday that two prominent dissidents arrested this week are suspected of endangering national security _ the clearest sign yet Chinese leaders plan to quash a would-be opposition party .\nOne leader of a suppressed new political party will be tried on Dec. 17 on a charge of colluding with foreign enemies of China '' to incite the subversion of state power , '' according to court documents given to his wife on Monday .\nWith attorneys locked up , harassed or plain scared , two prominent dissidents will defend themselves against charges of subversion Thursday in China 's highest-profile dissident trials in two years .\n"
references_2 = "Hurricane Mitch, category 5 hurricane, brought widespread death and destruction to Central American.\nEspecially hard hit was Honduras where an estimated 6,076 people lost their lives.\nThe hurricane, which lingered off the coast of Honduras for 3 days before moving off, flooded large areas, destroying crops and property.\nThe U.S. and European Union were joined by Pope John Paul II in a call for money and workers to help the stricken area.\nPresident Clinton sent Tipper Gore, wife of Vice President Gore to the area to deliver much needed supplies to the area, demonstrating U.S. commitment to the recovery of the region.\n"
all_hypothesis = [hypothesis_1, hypothesis_2]
all_references = [references_1, references_2]
scores = evaluator.get_scores(all_hypothesis, all_references)
for metric, results in sorted(scores.items(), key=lambda x: x[0]):
if not apply_avg and not apply_best: # value is a type of list as we evaluate each summary vs each reference
for hypothesis_id, results_per_ref in enumerate(results):
nb_references = len(results_per_ref['p'])
for reference_id in range(nb_references):
print('\tHypothesis #{} & Reference #{}: '.format(hypothesis_id, reference_id))
print('\t' + prepare_results(metric,results_per_ref['p'][reference_id], results_per_ref['r'][reference_id], results_per_ref['f'][reference_id]))
print()
else:
print(prepare_results(metric, results['p'], results['r'], results['f']))
print()
It produces the following output:
Evaluation with Avg
rouge-1: P: 28.62 R: 26.46 F1: 27.49
rouge-2: P: 4.21 R: 3.92 F1: 4.06
rouge-3: P: 0.80 R: 0.74 F1: 0.77
rouge-4: P: 0.00 R: 0.00 F1: 0.00
rouge-l: P: 30.52 R: 28.57 F1: 29.51
rouge-w: P: 15.85 R: 8.28 F1: 10.87
Evaluation with Best
rouge-1: P: 30.44 R: 28.36 F1: 29.37
rouge-2: P: 4.74 R: 4.46 F1: 4.59
rouge-3: P: 1.06 R: 0.98 F1: 1.02
rouge-4: P: 0.00 R: 0.00 F1: 0.00
rouge-l: P: 31.54 R: 29.71 F1: 30.60
rouge-w: P: 16.42 R: 8.82 F1: 11.47
Evaluation with Individual
Hypothesis #0 & Reference #0:
rouge-1: P: 38.54 R: 35.58 F1: 37.00
Hypothesis #0 & Reference #1:
rouge-1: P: 45.83 R: 43.14 F1: 44.44
Hypothesis #1 & Reference #0:
rouge-1: P: 15.05 R: 13.59 F1: 14.29
Hypothesis #0 & Reference #0:
rouge-2: P: 7.37 R: 6.80 F1: 7.07
Hypothesis #0 & Reference #1:
rouge-2: P: 9.47 R: 8.91 F1: 9.18
Hypothesis #1 & Reference #0:
rouge-2: P: 0.00 R: 0.00 F1: 0.00
Hypothesis #0 & Reference #0:
rouge-3: P: 2.13 R: 1.96 F1: 2.04
Hypothesis #0 & Reference #1:
rouge-3: P: 1.06 R: 1.00 F1: 1.03
Hypothesis #1 & Reference #0:
rouge-3: P: 0.00 R: 0.00 F1: 0.00
Hypothesis #0 & Reference #0:
rouge-4: P: 0.00 R: 0.00 F1: 0.00
Hypothesis #0 & Reference #1:
rouge-4: P: 0.00 R: 0.00 F1: 0.00
Hypothesis #1 & Reference #0:
rouge-4: P: 0.00 R: 0.00 F1: 0.00
Hypothesis #0 & Reference #0:
rouge-l: P: 42.11 R: 39.39 F1: 40.70
Hypothesis #0 & Reference #1:
rouge-l: P: 46.19 R: 43.92 F1: 45.03
Hypothesis #1 & Reference #0:
rouge-l: P: 16.88 R: 15.50 F1: 16.16
Hypothesis #0 & Reference #0:
rouge-w: P: 22.27 R: 11.49 F1: 15.16
Hypothesis #0 & Reference #1:
rouge-w: P: 24.56 R: 13.60 F1: 17.51
Hypothesis #1 & Reference #0:
rouge-w: P: 8.29 R: 4.04 F1: 5.43Download Details:
Author: Diego999
Source Code: https://github.com/Diego999/py-rouge
License: Apache-2.0 license
1656856140
A Plugin for D3.js That Allows You to Easy Use Context-menus
d3-context-menu
This is a plugin for d3.js that allows you to easy use context-menus in your visualizations. It's 100% d3 based and done in the "d3 way", so you don't need to worry about including additional frameworks.
Install with Bower
bower install d3-context-menu
Basic usage:
// Define your menu
var menu = [
{
title: 'Item #1',
action: function(d) {
console.log('Item #1 clicked!');
console.log('The data for this circle is: ' + d);
},
disabled: false // optional, defaults to false
},
{
title: 'Item #2',
action: function(d) {
console.log('You have clicked the second item!');
console.log('The data for this circle is: ' + d);
}
}
]
var data = [1, 2, 3];
var g = d3.select('body').append('svg')
.attr('width', 200)
.attr('height', 400)
.append('g');
g.selectAll('circles')
.data(data)
.enter()
.append('circle')
.attr('r', 30)
.attr('fill', 'steelblue')
.attr('cx', function(d) {
return 100;
})
.attr('cy', function(d) {
return d * 100;
})
.on('contextmenu', d3.contextMenu(menu)); // attach menu to element
});
Advanced usage:
Headers and Dividers
Menus can have Headers and Dividers. To specify a header simply don't define an "action" property. To specify a divider, simply add a "divider: true" property to the menu item, and it'll be considered a divider. Example menu definition:
var menu = [
{
title: 'Header',
},
{
title: 'Normal item',
action: function() {}
},
{
divider: true
},
{
title: 'Last item',
action: function() {}
}
];
Nested Menu
Menus can have Nested Menu. To specify a nested menu, simply add "children" property. Children has item of array.
var menu = [
{
title: 'Parent',
children: [
{
title: 'Child',
children: [
{
// header
title: 'Grand-Child1'
},
{
// normal
title: 'Grand-Child2',
action: function() {}
},
{
// divider
divider: true
},
{
// disable
title: 'Grand-Child3',
action: function() {}
}
]
}
]
},
];
See the index.htm file in the example folder to see this in action.
Pre-show callback
You can pass in a callback that will be executed before the context menu appears. This can be useful if you need something to close tooltips or perform some other task before the menu appears:
...
.on('contextmenu', d3.contextMenu(menu, function() {
console.log('Quick! Before the menu appears!');
})); // attach menu to element
Post-show callback
You can pass in a callback that will be executed after the context menu appears using the onClose option:
...
.on('contextmenu', d3.contextMenu(menu, {
onOpen: function() {
console.log('Quick! Before the menu appears!');
},
onClose: function() {
console.log('Menu has been closed.');
}
})); // attach menu to element
Context-sensitive menu items
You can use information from your context in menu names, simply specify a function for title which returns a string:
var menu = [
{
title: function(d) {
return 'Delete circle '+d.circleName;
},
action: function(d) {
// delete it
}
},
{
title: function(d) {
return 'Item 2';
},
action: function(d) {
// do nothing interesting
}
}
];
// Menu shown is:
[Delete Circle MyCircle]
[Item 2]
Dynamic menu list
You can also have different lists of menu items for different nodes if menu is a function:
var menu = function(data) {
if (data.x > 100) {
return [{
title: 'Item #1',
action: function(d) {
console.log('Item #1 clicked!');
console.log('The data for this circle is: ' + d);
}
}];
} else {
return [{
title: 'Item #1',
action: function(d) {
console.log('Item #1 clicked!');
console.log('The data for this circle is: ' + d);
}
}, {
title: 'Item #2',
action: function(d) {
console.log('Item #2 clicked!');
console.log('The data for this circle is: ' + d);
}
}];
}
};
// Menu shown for nodes with x < 100 contains 1 item, while other nodes have 2 menu items
Deleting Nodes Example
The following example shows how to add a right click menu to a tree diagram:
http://plnkr.co/edit/bDBe0xGX1mCLzqYGOqOS?p=info
Explicitly set menu position
Default position can be overwritten by providing a position option (either object or function returning an object):
...
.on('contextmenu', d3.contextMenu(menu, {
onOpen: function() {
...
},
onClose: function() {
...
},
position: {
top: 100,
left: 200
}
})); // attach menu to element
or
...
.on('contextmenu', d3.contextMenu(menu, {
onOpen: function() {
...
},
onClose: function() {
...
},
position: function(d) {
var elm = this;
var bounds = elm.getBoundingClientRect();
// eg. align bottom-left
return {
top: bounds.top + bounds.height,
left: bounds.left
}
}
})); // attach menu to element
Set your own CSS class as theme (make sure to style it)
d3.contextMenu(menu, {
...
theme: 'my-awesome-theme'
});
or
d3.contextMenu(menu, {
...
theme: function () {
if (foo) {
return 'my-foo-theme';
}
else {
return 'my-awesome-theme';
}
}
});
Close the context menu programatically (can be used as cleanup, as well)
d3.contextMenu('close');
The following example shows how to add a right click menu to a tree diagram:
http://plnkr.co/edit/bDBe0xGX1mCLzqYGOqOS?p=info
Additional callback arguments
Depending on the D3 library version used the callback functions can provide an additional argument:
- for D3 6.x or above it will be the event, since the global d3.event is not available.
var menu = [
{
title: 'Item #1',
action: function(d, event) {
console.log('Item #1 clicked!');
console.log('The data for this circle is: ' + d);
console.log('The event is: ' + event);
}
}
]
- for D3 5.x or below it will be the index, for backward compatibility reasons.
var menu = [
{
title: 'Item #1',
action: function(d, index) {
console.log('Item #1 clicked!');
console.log('The data for this circle is: ' + d);
console.log('The index is: ' + index);
}
}
]
What's new in version 2.1.0
- Added support for accessing event information in with D3 6.x.
What's new in version 2.0.0
- Added support for D3 6.x
- The
indexparameter of callbacks are undefined when using D3 6.x or above. See the index.htm file in the example folder to see how to get the properindexvalue in that case. - Added class property for menu items that allows specifying CSS classes (see: https://github.com/patorjk/d3-context-menu/pull/56).
What's new in version 1.1.2
- Menu updated so it wont go off bottom or right of screen when window is smaller.
What's new in version 1.1.1
- Menu close bug fix.
What's new in version 1.1.0
- Nested submenus are now supported.
What's new in version 1.0.1
- Default theme styles extracted to their own CSS class (
d3-context-menu-theme) - Ability to specify own theme css class via the
themeconfiguration option (as string or function returning string) - onOpen/onClose callbacks now have consistent signature (they receive
dataandindex, andthisargument refers to the DOM element the context menu is related to) - all other functions (eg.
position,menu) have the same signature andthisobject asonClose/onOpen - Context menu now closes on
mousedownoutside of the menu, instead ofclickoutside (to mimic behaviour of the native context menu) disabledanddividercan now be functions as well and have the same signature andthisobject as explained above- Close the context menu programatically using
d3.contextMenu('close');
What's new in version 0.2.1
- Ability to set menu position
- Minified css and js versions
What's new in version 0.1.3
- Fixed issue where context menu element is never removed from DOM
- Fixed issue where
<body>click event is never removed - Fixed issue where the incorrect
onClosecallback was called when menu was closed as a result of clicking outside
What's new in version 0.1.2
- If contextmenu is clicked twice it will close rather than open the browser's context menu.
What's new in version 0.1.1
- Header and Divider items.
- Ability to disable items.
It's written to be very light weight and customizable. You can see it in action here:
http://plnkr.co/edit/hAx36JQhb0RsvVn7TomS?p=info
Author: Patorjk
Source Code: https://github.com/patorjk/d3-context-menu
License: MIT license
1594162500
Multi-cloud Spending: 8 Tips To Lower Cost
A multi-cloud approach is nothing but leveraging two or more cloud platforms for meeting the various business requirements of an enterprise. The multi-cloud IT environment incorporates different clouds from multiple vendors and negates the dependence on a single public cloud service provider. Thus enterprises can choose specific services from multiple public clouds and reap the benefits of each.
Given its affordability and agility, most enterprises opt for a multi-cloud approach in cloud computing now. A 2018 survey on the public cloud services market points out that 81% of the respondents use services from two or more providers. Subsequently, the cloud computing services market has reported incredible growth in recent times. The worldwide public cloud services market is all set to reach $500 billion in the next four years, according to IDC.
By choosing multi-cloud solutions strategically, enterprises can optimize the benefits of cloud computing and aim for some key competitive advantages. They can avoid the lengthy and cumbersome processes involved in buying, installing and testing high-priced systems. The IaaS and PaaS solutions have become a windfall for the enterprise’s budget as it does not incur huge up-front capital expenditure.
However, cost optimization is still a challenge while facilitating a multi-cloud environment and a large number of enterprises end up overpaying with or without realizing it. The below-mentioned tips would help you ensure the money is spent wisely on cloud computing services.
- Deactivate underused or unattached resources
Most organizations tend to get wrong with simple things which turn out to be the root cause for needless spending and resource wastage. The first step to cost optimization in your cloud strategy is to identify underutilized resources that you have been paying for.
Enterprises often continue to pay for resources that have been purchased earlier but are no longer useful. Identifying such unused and unattached resources and deactivating it on a regular basis brings you one step closer to cost optimization. If needed, you can deploy automated cloud management tools that are largely helpful in providing the analytics needed to optimize the cloud spending and cut costs on an ongoing basis.
- Figure out idle instances
Another key cost optimization strategy is to identify the idle computing instances and consolidate them into fewer instances. An idle computing instance may require a CPU utilization level of 1-5%, but you may be billed by the service provider for 100% for the same instance.
Every enterprise will have such non-production instances that constitute unnecessary storage space and lead to overpaying. Re-evaluating your resource allocations regularly and removing unnecessary storage may help you save money significantly. Resource allocation is not only a matter of CPU and memory but also it is linked to the storage, network, and various other factors.
- Deploy monitoring mechanisms
The key to efficient cost reduction in cloud computing technology lies in proactive monitoring. A comprehensive view of the cloud usage helps enterprises to monitor and minimize unnecessary spending. You can make use of various mechanisms for monitoring computing demand.
For instance, you can use a heatmap to understand the highs and lows in computing visually. This heat map indicates the start and stop times which in turn lead to reduced costs. You can also deploy automated tools that help organizations to schedule instances to start and stop. By following a heatmap, you can understand whether it is safe to shut down servers on holidays or weekends.
#cloud computing services #all #hybrid cloud #cloud #multi-cloud strategy #cloud spend #multi-cloud spending #multi cloud adoption #why multi cloud #multi cloud trends #multi cloud companies #multi cloud research #multi cloud market