1590909754
Junior Vs Senior Code - How To Write Better Code - Part 2
Writing code is easy. Writing clean code, though, is much harder. In this video I take a look at two different code examples from a beginner, intermediate, and advanced level. The goal of this is to show you how a senior developer will think while programming and how they will structure their code to be as clean and well-written as possible.
Part One: https://morioh.com/p/3b21318d5604
π§ Concepts Covered:
- How senior developers think
- How to manage async code
- The differences between senior and junior developers
- What to think about when programming
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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
1648900800
Plpgsql Check: Extension That Allows to Check Plpgsql Source Code.
plpgsql_check
I founded this project, because I wanted to publish the code I wrote in the last two years, when I tried to write enhanced checking for PostgreSQL upstream. It was not fully successful - integration into upstream requires some larger plpgsql refactoring - probably it will not be done in next years (now is Dec 2013). But written code is fully functional and can be used in production (and it is used in production). So, I created this extension to be available for all plpgsql developers.
If you like it and if you would to join to development of this extension, register yourself to postgresql extension hacking google group.
Features
- check fields of referenced database objects and types inside embedded SQL
- using correct types of function parameters
- unused variables and function argumens, unmodified OUT argumens
- partially detection of dead code (due RETURN command)
- detection of missing RETURN command in function
- try to identify unwanted hidden casts, that can be performance issue like unused indexes
- possibility to collect relations and functions used by function
- possibility to check EXECUTE stmt agaist SQL injection vulnerability
I invite any ideas, patches, bugreports.
plpgsql_check is next generation of plpgsql_lint. It allows to check source code by explicit call plpgsql_check_function.
PostgreSQL PostgreSQL 10, 11, 12, 13 and 14 are supported.
The SQL statements inside PL/pgSQL functions are checked by validator for semantic errors. These errors can be found by plpgsql_check_function:
Active mode
postgres=# CREATE EXTENSION plpgsql_check;
LOAD
postgres=# CREATE TABLE t1(a int, b int);
CREATE TABLE
postgres=#
CREATE OR REPLACE FUNCTION public.f1()
RETURNS void
LANGUAGE plpgsql
AS $function$
DECLARE r record;
BEGIN
FOR r IN SELECT * FROM t1
LOOP
RAISE NOTICE '%', r.c; -- there is bug - table t1 missing "c" column
END LOOP;
END;
$function$;
CREATE FUNCTION
postgres=# select f1(); -- execution doesn't find a bug due to empty table t1
f1
ββββ
(1 row)
postgres=# \x
Expanded display is on.
postgres=# select * from plpgsql_check_function_tb('f1()');
β[ RECORD 1 ]βββββββββββββββββββββββββββ
functionid β f1
lineno β 6
statement β RAISE
sqlstate β 42703
message β record "r" has no field "c"
detail β [null]
hint β [null]
level β error
position β 0
query β [null]
postgres=# \sf+ f1
CREATE OR REPLACE FUNCTION public.f1()
RETURNS void
LANGUAGE plpgsql
1 AS $function$
2 DECLARE r record;
3 BEGIN
4 FOR r IN SELECT * FROM t1
5 LOOP
6 RAISE NOTICE '%', r.c; -- there is bug - table t1 missing "c" column
7 END LOOP;
8 END;
9 $function$
Function plpgsql_check_function() has three possible formats: text, json or xml
select * from plpgsql_check_function('f1()', fatal_errors := false);
plpgsql_check_function
------------------------------------------------------------------------
error:42703:4:SQL statement:column "c" of relation "t1" does not exist
Query: update t1 set c = 30
-- ^
error:42P01:7:RAISE:missing FROM-clause entry for table "r"
Query: SELECT r.c
-- ^
error:42601:7:RAISE:too few parameters specified for RAISE
(7 rows)
postgres=# select * from plpgsql_check_function('fx()', format:='xml');
plpgsql_check_function
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
<Function oid="16400"> β΅
<Issue> β΅
<Level>error</level> β΅
<Sqlstate>42P01</Sqlstate> β΅
<Message>relation "foo111" does not exist</Message> β΅
<Stmt lineno="3">RETURN</Stmt> β΅
<Query position="23">SELECT (select a from foo111)</Query>β΅
</Issue> β΅
</Function>
(1 row)
Arguments
You can set level of warnings via function's parameters:
Mandatory arguments
- function name or function signature - these functions requires function specification. Any function in PostgreSQL can be specified by Oid or by name or by signature. When you know oid or complete function's signature, you can use a regprocedure type parameter like
'fx()'::regprocedureor16799::regprocedure. Possible alternative is using a name only, when function's name is unique - like'fx'. When the name is not unique or the function doesn't exists it raises a error.
Optional arguments
relid DEFAULT 0 - oid of relation assigned with trigger function. It is necessary for check of any trigger function.
fatal_errors boolean DEFAULT true - stop on first error
other_warnings boolean DEFAULT true - show warnings like different attributes number in assignmenet on left and right side, variable overlaps function's parameter, unused variables, unwanted casting, ..
extra_warnings boolean DEFAULT true - show warnings like missing RETURN, shadowed variables, dead code, never read (unused) function's parameter, unmodified variables, modified auto variables, ..
performance_warnings boolean DEFAULT false - performance related warnings like declared type with type modificator, casting, implicit casts in where clause (can be reason why index is not used), ..
security_warnings boolean DEFAULT false - security related checks like SQL injection vulnerability detection
anyelementtype regtype DEFAULT 'int' - a real type used instead anyelement type
anyenumtype regtype DEFAULT '-' - a real type used instead anyenum type
anyrangetype regtype DEFAULT 'int4range' - a real type used instead anyrange type
anycompatibletype DEFAULT 'int' - a real type used instead anycompatible type
anycompatiblerangetype DEFAULT 'int4range' - a real type used instead anycompatible range type
without_warnings DEFAULT false - disable all warnings
all_warnings DEFAULT false - enable all warnings
newtable DEFAULT NULL, oldtable DEFAULT NULL - the names of NEW or OLD transitive tables. These parameters are required when transitive tables are used.
Triggers
When you want to check any trigger, you have to enter a relation that will be used together with trigger function
CREATE TABLE bar(a int, b int);
postgres=# \sf+ foo_trg
CREATE OR REPLACE FUNCTION public.foo_trg()
RETURNS trigger
LANGUAGE plpgsql
1 AS $function$
2 BEGIN
3 NEW.c := NEW.a + NEW.b;
4 RETURN NEW;
5 END;
6 $function$
Missing relation specification
postgres=# select * from plpgsql_check_function('foo_trg()');
ERROR: missing trigger relation
HINT: Trigger relation oid must be valid
Correct trigger checking (with specified relation)
postgres=# select * from plpgsql_check_function('foo_trg()', 'bar');
plpgsql_check_function
--------------------------------------------------------
error:42703:3:assignment:record "new" has no field "c"
(1 row)
For triggers with transitive tables you can set a oldtable or newtable parameters:
create or replace function footab_trig_func()
returns trigger as $$
declare x int;
begin
if false then
-- should be ok;
select count(*) from newtab into x;
-- should fail;
select count(*) from newtab where d = 10 into x;
end if;
return null;
end;
$$ language plpgsql;
select * from plpgsql_check_function('footab_trig_func','footab', newtable := 'newtab');
Mass check
You can use the plpgsql_check_function for mass check functions and mass check triggers. Please, test following queries:
-- check all nontrigger plpgsql functions
SELECT p.oid, p.proname, plpgsql_check_function(p.oid)
FROM pg_catalog.pg_namespace n
JOIN pg_catalog.pg_proc p ON pronamespace = n.oid
JOIN pg_catalog.pg_language l ON p.prolang = l.oid
WHERE l.lanname = 'plpgsql' AND p.prorettype <> 2279;
or
SELECT p.proname, tgrelid::regclass, cf.*
FROM pg_proc p
JOIN pg_trigger t ON t.tgfoid = p.oid
JOIN pg_language l ON p.prolang = l.oid
JOIN pg_namespace n ON p.pronamespace = n.oid,
LATERAL plpgsql_check_function(p.oid, t.tgrelid) cf
WHERE n.nspname = 'public' and l.lanname = 'plpgsql'
or
-- check all plpgsql functions (functions or trigger functions with defined triggers)
SELECT
(pcf).functionid::regprocedure, (pcf).lineno, (pcf).statement,
(pcf).sqlstate, (pcf).message, (pcf).detail, (pcf).hint, (pcf).level,
(pcf)."position", (pcf).query, (pcf).context
FROM
(
SELECT
plpgsql_check_function_tb(pg_proc.oid, COALESCE(pg_trigger.tgrelid, 0)) AS pcf
FROM pg_proc
LEFT JOIN pg_trigger
ON (pg_trigger.tgfoid = pg_proc.oid)
WHERE
prolang = (SELECT lang.oid FROM pg_language lang WHERE lang.lanname = 'plpgsql') AND
pronamespace <> (SELECT nsp.oid FROM pg_namespace nsp WHERE nsp.nspname = 'pg_catalog') AND
-- ignore unused triggers
(pg_proc.prorettype <> (SELECT typ.oid FROM pg_type typ WHERE typ.typname = 'trigger') OR
pg_trigger.tgfoid IS NOT NULL)
OFFSET 0
) ss
ORDER BY (pcf).functionid::regprocedure::text, (pcf).lineno
Passive mode
Functions should be checked on start - plpgsql_check module must be loaded.
Configuration
plpgsql_check.mode = [ disabled | by_function | fresh_start | every_start ]
plpgsql_check.fatal_errors = [ yes | no ]
plpgsql_check.show_nonperformance_warnings = false
plpgsql_check.show_performance_warnings = false
Default mode is by_function, that means that the enhanced check is done only in active mode - by plpgsql_check_function. fresh_start means cold start.
You can enable passive mode by
load 'plpgsql'; -- 1.1 and higher doesn't need it
load 'plpgsql_check';
set plpgsql_check.mode = 'every_start';
SELECT fx(10); -- run functions - function is checked before runtime starts it
Limits
plpgsql_check should find almost all errors on really static code. When developer use some PLpgSQL's dynamic features like dynamic SQL or record data type, then false positives are possible. These should be rare - in well written code - and then the affected function should be redesigned or plpgsql_check should be disabled for this function.
CREATE OR REPLACE FUNCTION f1()
RETURNS void AS $$
DECLARE r record;
BEGIN
FOR r IN EXECUTE 'SELECT * FROM t1'
LOOP
RAISE NOTICE '%', r.c;
END LOOP;
END;
$$ LANGUAGE plpgsql SET plpgsql.enable_check TO false;
A usage of plpgsql_check adds a small overhead (in enabled passive mode) and you should use it only in develop or preprod environments.
Dynamic SQL
This module doesn't check queries that are assembled in runtime. It is not possible to identify results of dynamic queries - so plpgsql_check cannot to set correct type to record variables and cannot to check a dependent SQLs and expressions.
When type of record's variable is not know, you can assign it explicitly with pragma type:
DECLARE r record;
BEGIN
EXECUTE format('SELECT * FROM %I', _tablename) INTO r;
PERFORM plpgsql_check_pragma('type: r (id int, processed bool)');
IF NOT r.processed THEN
...
Attention: The SQL injection check can detect only some SQL injection vulnerabilities. This tool cannot be used for security audit! Some issues should not be detected. This check can raise false alarms too - probably when variable is sanitized by other command or when value is of some compose type.
Refcursors
plpgsql_check should not to detect structure of referenced cursors. A reference on cursor in PLpgSQL is implemented as name of global cursor. In check time, the name is not known (not in all possibilities), and global cursor doesn't exist. It is significant break for any static analyse. PLpgSQL cannot to set correct type for record variables and cannot to check a dependent SQLs and expressions. A solution is same like dynamic SQL. Don't use record variable as target when you use refcursor type or disable plpgsql_check for these functions.
CREATE OR REPLACE FUNCTION foo(refcur_var refcursor)
RETURNS void AS $$
DECLARE
rec_var record;
BEGIN
FETCH refcur_var INTO rec_var; -- this is STOP for plpgsql_check
RAISE NOTICE '%', rec_var; -- record rec_var is not assigned yet error
In this case a record type should not be used (use known rowtype instead):
CREATE OR REPLACE FUNCTION foo(refcur_var refcursor)
RETURNS void AS $$
DECLARE
rec_var some_rowtype;
BEGIN
FETCH refcur_var INTO rec_var;
RAISE NOTICE '%', rec_var;
Temporary tables
plpgsql_check cannot verify queries over temporary tables that are created in plpgsql's function runtime. For this use case it is necessary to create a fake temp table or disable plpgsql_check for this function.
In reality temp tables are stored in own (per user) schema with higher priority than persistent tables. So you can do (with following trick safetly):
CREATE OR REPLACE FUNCTION public.disable_dml()
RETURNS trigger
LANGUAGE plpgsql AS $function$
BEGIN
RAISE EXCEPTION SQLSTATE '42P01'
USING message = format('this instance of %I table doesn''t allow any DML operation', TG_TABLE_NAME),
hint = format('you should to run "CREATE TEMP TABLE %1$I(LIKE %1$I INCLUDING ALL);" statement',
TG_TABLE_NAME);
RETURN NULL;
END;
$function$;
CREATE TABLE foo(a int, b int); -- doesn't hold data ever
CREATE TRIGGER foo_disable_dml
BEFORE INSERT OR UPDATE OR DELETE ON foo
EXECUTE PROCEDURE disable_dml();
postgres=# INSERT INTO foo VALUES(10,20);
ERROR: this instance of foo table doesn't allow any DML operation
HINT: you should to run "CREATE TEMP TABLE foo(LIKE foo INCLUDING ALL);" statement
postgres=#
CREATE TABLE
postgres=# INSERT INTO foo VALUES(10,20);
INSERT 0 1
This trick emulates GLOBAL TEMP tables partially and it allows a statical validation. Other possibility is using a [template foreign data wrapper] (https://github.com/okbob/template_fdw)
You can use pragma table and create ephemeral table:
BEGIN
CREATE TEMP TABLE xxx(a int);
PERFORM plpgsql_check_pragma('table: xxx(a int)');
INSERT INTO xxx VALUES(10);
Dependency list
A function plpgsql_show_dependency_tb can show all functions, operators and relations used inside processed function:
postgres=# select * from plpgsql_show_dependency_tb('testfunc(int,float)');
ββββββββββββ¬ββββββββ¬βββββββββ¬ββββββββββ¬βββββββββββββββββββββββββββββ
β type β oid β schema β name β params β
ββββββββββββͺββββββββͺβββββββββͺββββββββββͺβββββββββββββββββββββββββββββ‘
β FUNCTION β 36008 β public β myfunc1 β (integer,double precision) β
β FUNCTION β 35999 β public β myfunc2 β (integer,double precision) β
β OPERATOR β 36007 β public β ** β (integer,integer) β
β RELATION β 36005 β public β myview β β
β RELATION β 36002 β public β mytable β β
ββββββββββββ΄ββββββββ΄βββββββββ΄ββββββββββ΄βββββββββββββββββββββββββββββ
(4 rows)
Profiler
The plpgsql_check contains simple profiler of plpgsql functions and procedures. It can work with/without a access to shared memory. It depends on shared_preload_libraries config. When plpgsql_check was initialized by shared_preload_libraries, then it can allocate shared memory, and function's profiles are stored there. When plpgsql_check cannot to allocate shared momory, the profile is stored in session memory.
Due dependencies, shared_preload_libraries should to contains plpgsql first
postgres=# show shared_preload_libraries ;
ββββββββββββββββββββββββββββ
β shared_preload_libraries β
ββββββββββββββββββββββββββββ‘
β plpgsql,plpgsql_check β
ββββββββββββββββββββββββββββ
(1 row)
The profiler is active when GUC plpgsql_check.profiler is on. The profiler doesn't require shared memory, but if there are not shared memory, then the profile is limmitted just to active session.
When plpgsql_check is initialized by shared_preload_libraries, another GUC is available to configure the amount of shared memory used by the profiler: plpgsql_check.profiler_max_shared_chunks. This defines the maximum number of statements chunk that can be stored in shared memory. For each plpgsql function (or procedure), the whole content is split into chunks of 30 statements. If needed, multiple chunks can be used to store the whole content of a single function. A single chunk is 1704 bytes. The default value for this GUC is 15000, which should be enough for big projects containing hundred of thousands of statements in plpgsql, and will consume about 24MB of memory. If your project doesn't require that much number of chunks, you can set this parameter to a smaller number in order to decrease the memory usage. The minimum value is 50 (which should consume about 83kB of memory), and the maximum value is 100000 (which should consume about 163MB of memory). Changing this parameter requires a PostgreSQL restart.
The profiler will also retrieve the query identifier for each instruction that contains an expression or optimizable statement. Note that this requires pg_stat_statements, or another similar third-party extension), to be installed. There are some limitations to the query identifier retrieval:
- if a plpgsql expression contains underlying statements, only the top level query identifier will be retrieved
- the profiler doesn't compute query identifier by itself but relies on external extension, such as pg_stat_statements, for that. It means that depending on the external extension behavior, you may not be able to see a query identifier for some statements. That's for instance the case with DDL statements, as pg_stat_statements doesn't expose the query identifier for such queries.
- a query identifier is retrieved only for instructions containing expressions. This means that plpgsql_profiler_function_tb() function can report less query identifier than instructions on a single line.
Attention: A update of shared profiles can decrease performance on servers under higher load.
The profile can be displayed by function plpgsql_profiler_function_tb:
postgres=# select lineno, avg_time, source from plpgsql_profiler_function_tb('fx(int)');
ββββββββββ¬βββββββββββ¬ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β lineno β avg_time β source β
ββββββββββͺβββββββββββͺββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ‘
β 1 β β β
β 2 β β declare result int = 0; β
β 3 β 0.075 β begin β
β 4 β 0.202 β for i in 1..$1 loop β
β 5 β 0.005 β select result + i into result; select result + i into result; β
β 6 β β end loop; β
β 7 β 0 β return result; β
β 8 β β end; β
ββββββββββ΄βββββββββββ΄ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
(9 rows)
The profile per statements (not per line) can be displayed by function plpgsql_profiler_function_statements_tb:
CREATE OR REPLACE FUNCTION public.fx1(a integer)
RETURNS integer
LANGUAGE plpgsql
1 AS $function$
2 begin
3 if a > 10 then
4 raise notice 'ahoj';
5 return -1;
6 else
7 raise notice 'nazdar';
8 return 1;
9 end if;
10 end;
11 $function$
postgres=# select stmtid, parent_stmtid, parent_note, lineno, exec_stmts, stmtname
from plpgsql_profiler_function_statements_tb('fx1');
ββββββββββ¬ββββββββββββββββ¬ββββββββββββββ¬βββββββββ¬βββββββββββββ¬ββββββββββββββββββ
β stmtid β parent_stmtid β parent_note β lineno β exec_stmts β stmtname β
ββββββββββͺββββββββββββββββͺββββββββββββββͺβββββββββͺβββββββββββββͺββββββββββββββββββ‘
β 0 β β
β β
β 2 β 0 β statement block β
β 1 β 0 β body β 3 β 0 β IF β
β 2 β 1 β then body β 4 β 0 β RAISE β
β 3 β 1 β then body β 5 β 0 β RETURN β
β 4 β 1 β else body β 7 β 0 β RAISE β
β 5 β 1 β else body β 8 β 0 β RETURN β
ββββββββββ΄ββββββββββββββββ΄ββββββββββββββ΄βββββββββ΄βββββββββββββ΄ββββββββββββββββββ
(6 rows)
All stored profiles can be displayed by calling function plpgsql_profiler_functions_all:
postgres=# select * from plpgsql_profiler_functions_all();
βββββββββββββββββββββββββ¬βββββββββββββ¬βββββββββββββ¬βββββββββββ¬ββββββββββββββ¬βββββββββββ¬βββββββββββ
β funcoid β exec_count β total_time β avg_time β stddev_time β min_time β max_time β
βββββββββββββββββββββββββͺβββββββββββββͺβββββββββββββͺβββββββββββͺββββββββββββββͺβββββββββββͺβββββββββββ‘
β fxx(double precision) β 1 β 0.01 β 0.01 β 0.00 β 0.01 β 0.01 β
βββββββββββββββββββββββββ΄βββββββββββββ΄βββββββββββββ΄βββββββββββ΄ββββββββββββββ΄βββββββββββ΄βββββββββββ
(1 row)
There are two functions for cleaning stored profiles: plpgsql_profiler_reset_all() and plpgsql_profiler_reset(regprocedure).
Coverage metrics
plpgsql_check provides two functions:
plpgsql_coverage_statements(name)plpgsql_coverage_branches(name)
Note
There is another very good PLpgSQL profiler - https://bitbucket.org/openscg/plprofiler
My extension is designed to be simple for use and practical. Nothing more or less.
plprofiler is more complex. It build call graphs and from this graph it can creates flame graph of execution times.
Both extensions can be used together with buildin PostgreSQL's feature - tracking functions.
set track_functions to 'pl';
...
select * from pg_stat_user_functions;
Tracer
plpgsql_check provides a tracing possibility - in this mode you can see notices on start or end functions (terse and default verbosity) and start or end statements (verbose verbosity). For default and verbose verbosity the content of function arguments is displayed. The content of related variables are displayed when verbosity is verbose.
postgres=# do $$ begin perform fx(10,null, 'now', e'stΔhule'); end; $$;
NOTICE: #0 ->> start of inline_code_block (Oid=0)
NOTICE: #2 ->> start of function fx(integer,integer,date,text) (Oid=16405)
NOTICE: #2 call by inline_code_block line 1 at PERFORM
NOTICE: #2 "a" => '10', "b" => null, "c" => '2020-08-03', "d" => 'stΔhule'
NOTICE: #4 ->> start of function fx(integer) (Oid=16404)
NOTICE: #4 call by fx(integer,integer,date,text) line 1 at PERFORM
NOTICE: #4 "a" => '10'
NOTICE: #4 <<- end of function fx (elapsed time=0.098 ms)
NOTICE: #2 <<- end of function fx (elapsed time=0.399 ms)
NOTICE: #0 <<- end of block (elapsed time=0.754 ms)
The number after # is a execution frame counter (this number is related to deep of error context stack). It allows to pair start end and of function.
Tracing is enabled by setting plpgsql_check.tracer to on. Attention - enabling this behaviour has significant negative impact on performance (unlike the profiler). You can set a level for output used by tracer plpgsql_check.tracer_errlevel (default is notice). The output content is limited by length specified by plpgsql_check.tracer_variable_max_length configuration variable.
In terse verbose mode the output is reduced:
postgres=# set plpgsql_check.tracer_verbosity TO terse;
SET
postgres=# do $$ begin perform fx(10,null, 'now', e'stΔhule'); end; $$;
NOTICE: #0 start of inline code block (oid=0)
NOTICE: #2 start of fx (oid=16405)
NOTICE: #4 start of fx (oid=16404)
NOTICE: #4 end of fx
NOTICE: #2 end of fx
NOTICE: #0 end of inline code block
In verbose mode the output is extended about statement details:
postgres=# do $$ begin perform fx(10,null, 'now', e'stΔhule'); end; $$;
NOTICE: #0 ->> start of block inline_code_block (oid=0)
NOTICE: #0.1 1 --> start of PERFORM
NOTICE: #2 ->> start of function fx(integer,integer,date,text) (oid=16405)
NOTICE: #2 call by inline_code_block line 1 at PERFORM
NOTICE: #2 "a" => '10', "b" => null, "c" => '2020-08-04', "d" => 'stΔhule'
NOTICE: #2.1 1 --> start of PERFORM
NOTICE: #2.1 "a" => '10'
NOTICE: #4 ->> start of function fx(integer) (oid=16404)
NOTICE: #4 call by fx(integer,integer,date,text) line 1 at PERFORM
NOTICE: #4 "a" => '10'
NOTICE: #4.1 6 --> start of assignment
NOTICE: #4.1 "a" => '10', "b" => '20'
NOTICE: #4.1 <-- end of assignment (elapsed time=0.076 ms)
NOTICE: #4.1 "res" => '130'
NOTICE: #4.2 7 --> start of RETURN
NOTICE: #4.2 "res" => '130'
NOTICE: #4.2 <-- end of RETURN (elapsed time=0.054 ms)
NOTICE: #4 <<- end of function fx (elapsed time=0.373 ms)
NOTICE: #2.1 <-- end of PERFORM (elapsed time=0.589 ms)
NOTICE: #2 <<- end of function fx (elapsed time=0.727 ms)
NOTICE: #0.1 <-- end of PERFORM (elapsed time=1.147 ms)
NOTICE: #0 <<- end of block (elapsed time=1.286 ms)
Special feature of tracer is tracing of ASSERT statement when plpgsql_check.trace_assert is on. When plpgsql_check.trace_assert_verbosity is DEFAULT, then all function's or procedure's variables are displayed when assert expression is false. When this configuration is VERBOSE then all variables from all plpgsql frames are displayed. This behaviour is independent on plpgsql.check_asserts value. It can be used, although the assertions are disabled in plpgsql runtime.
postgres=# set plpgsql_check.tracer to off;
postgres=# set plpgsql_check.trace_assert_verbosity TO verbose;
postgres=# do $$ begin perform fx(10,null, 'now', e'stΔhule'); end; $$;
NOTICE: #4 PLpgSQL assert expression (false) on line 12 of fx(integer) is false
NOTICE: "a" => '10', "res" => null, "b" => '20'
NOTICE: #2 PL/pgSQL function fx(integer,integer,date,text) line 1 at PERFORM
NOTICE: "a" => '10', "b" => null, "c" => '2020-08-05', "d" => 'stΔhule'
NOTICE: #0 PL/pgSQL function inline_code_block line 1 at PERFORM
ERROR: assertion failed
CONTEXT: PL/pgSQL function fx(integer) line 12 at ASSERT
SQL statement "SELECT fx(a)"
PL/pgSQL function fx(integer,integer,date,text) line 1 at PERFORM
SQL statement "SELECT fx(10,null, 'now', e'stΔhule')"
PL/pgSQL function inline_code_block line 1 at PERFORM
postgres=# set plpgsql.check_asserts to off;
SET
postgres=# do $$ begin perform fx(10,null, 'now', e'stΔhule'); end; $$;
NOTICE: #4 PLpgSQL assert expression (false) on line 12 of fx(integer) is false
NOTICE: "a" => '10', "res" => null, "b" => '20'
NOTICE: #2 PL/pgSQL function fx(integer,integer,date,text) line 1 at PERFORM
NOTICE: "a" => '10', "b" => null, "c" => '2020-08-05', "d" => 'stΔhule'
NOTICE: #0 PL/pgSQL function inline_code_block line 1 at PERFORM
DO
Attention - SECURITY
Tracer prints content of variables or function arguments. For security definer function, this content can hold security sensitive data. This is reason why tracer is disabled by default and should be enabled only with super user rights plpgsql_check.enable_tracer.
Pragma
You can configure plpgsql_check behave inside checked function with "pragma" function. This is a analogy of PL/SQL or ADA language of PRAGMA feature. PLpgSQL doesn't support PRAGMA, but plpgsql_check detects function named plpgsql_check_pragma and get options from parameters of this function. These plpgsql_check options are valid to end of group of statements.
CREATE OR REPLACE FUNCTION test()
RETURNS void AS $$
BEGIN
...
-- for following statements disable check
PERFORM plpgsql_check_pragma('disable:check');
...
-- enable check again
PERFORM plpgsql_check_pragma('enable:check');
...
END;
$$ LANGUAGE plpgsql;
The function plpgsql_check_pragma is immutable function that returns one. It is defined by plpgsql_check extension. You can declare alternative plpgsql_check_pragma function like:
CREATE OR REPLACE FUNCTION plpgsql_check_pragma(VARIADIC args[])
RETURNS int AS $$
SELECT 1
$$ LANGUAGE sql IMMUTABLE;
Using pragma function in declaration part of top block sets options on function level too.
CREATE OR REPLACE FUNCTION test()
RETURNS void AS $$
DECLARE
aux int := plpgsql_check_pragma('disable:extra_warnings');
...
Shorter syntax for pragma is supported too:
CREATE OR REPLACE FUNCTION test()
RETURNS void AS $$
DECLARE r record;
BEGIN
PERFORM 'PRAGMA:TYPE:r (a int, b int)';
PERFORM 'PRAGMA:TABLE: x (like pg_class)';
...
Supported pragmas
echo:str - print string (for testing)
status:check,status:tracer, status:other_warnings, status:performance_warnings, status:extra_warnings,status:security_warnings
enable:check,enable:tracer, enable:other_warnings, enable:performance_warnings, enable:extra_warnings,enable:security_warnings
disable:check,disable:tracer, disable:other_warnings, disable:performance_warnings, disable:extra_warnings,disable:security_warnings
type:varname typename or type:varname (fieldname type, ...) - set type to variable of record type
table: name (column_name type, ...) or table: name (like tablename) - create ephereal table
Pragmas enable:tracer and disable:tracerare active for Postgres 12 and higher
Compilation
You need a development environment for PostgreSQL extensions:
make clean
make install
result:
[pavel@localhost plpgsql_check]$ make USE_PGXS=1 clean
rm -f plpgsql_check.so libplpgsql_check.a libplpgsql_check.pc
rm -f plpgsql_check.o
rm -rf results/ regression.diffs regression.out tmp_check/ log/
[pavel@localhost plpgsql_check]$ make USE_PGXS=1 all
clang -O2 -Wall -Wmissing-prototypes -Wpointer-arith -Wdeclaration-after-statement -Wendif-labels -Wmissing-format-attribute -Wformat-security -fno-strict-aliasing -fwrapv -fpic -I/usr/local/pgsql/lib/pgxs/src/makefiles/../../src/pl/plpgsql/src -I. -I./ -I/usr/local/pgsql/include/server -I/usr/local/pgsql/include/internal -D_GNU_SOURCE -c -o plpgsql_check.o plpgsql_check.c
clang -O2 -Wall -Wmissing-prototypes -Wpointer-arith -Wdeclaration-after-statement -Wendif-labels -Wmissing-format-attribute -Wformat-security -fno-strict-aliasing -fwrapv -fpic -I/usr/local/pgsql/lib/pgxs/src/makefiles/../../src/pl/plpgsql/src -shared -o plpgsql_check.so plpgsql_check.o -L/usr/local/pgsql/lib -Wl,--as-needed -Wl,-rpath,'/usr/local/pgsql/lib',--enable-new-dtags
[pavel@localhost plpgsql_check]$ su root
Password: *******
[root@localhost plpgsql_check]# make USE_PGXS=1 install
/usr/bin/mkdir -p '/usr/local/pgsql/lib'
/usr/bin/mkdir -p '/usr/local/pgsql/share/extension'
/usr/bin/mkdir -p '/usr/local/pgsql/share/extension'
/usr/bin/install -c -m 755 plpgsql_check.so '/usr/local/pgsql/lib/plpgsql_check.so'
/usr/bin/install -c -m 644 plpgsql_check.control '/usr/local/pgsql/share/extension/'
/usr/bin/install -c -m 644 plpgsql_check--0.9.sql '/usr/local/pgsql/share/extension/'
[root@localhost plpgsql_check]# exit
[pavel@localhost plpgsql_check]$ make USE_PGXS=1 installcheck
/usr/local/pgsql/lib/pgxs/src/makefiles/../../src/test/regress/pg_regress --inputdir=./ --psqldir='/usr/local/pgsql/bin' --dbname=pl_regression --load-language=plpgsql --dbname=contrib_regression plpgsql_check_passive plpgsql_check_active plpgsql_check_active-9.5
(using postmaster on Unix socket, default port)
============== dropping database "contrib_regression" ==============
DROP DATABASE
============== creating database "contrib_regression" ==============
CREATE DATABASE
ALTER DATABASE
============== installing plpgsql ==============
CREATE LANGUAGE
============== running regression test queries ==============
test plpgsql_check_passive ... ok
test plpgsql_check_active ... ok
test plpgsql_check_active-9.5 ... ok
=====================
All 3 tests passed.
=====================
Compilation on Ubuntu
Sometimes successful compilation can require libicu-dev package (PostgreSQL 10 and higher - when pg was compiled with ICU support)
sudo apt install libicu-dev
Compilation plpgsql_check on Windows
You can check precompiled dll libraries http://okbob.blogspot.cz/2015/02/plpgsqlcheck-is-available-for-microsoft.html
or compile by self:
- Download and install PostgreSQL for Win32 from http://www.enterprisedb.com
- Download and install Microsoft Visual C++ Express
- Lern tutorial http://blog.2ndquadrant.com/compiling-postgresql-extensions-visual-studio-windows
- Build plpgsql_check.dll
- Install plugin
- copy
plpgsql_check.dlltoPostgreSQL\14\lib - copy
plpgsql_check.controlandplpgsql_check--2.1.sqltoPostgreSQL\14\share\extension
Checked on
- gcc on Linux (against all supported PostgreSQL)
- clang 3.4 on Linux (against PostgreSQL 10)
- for success regress tests the PostgreSQL 10 or higher is required
Compilation against PostgreSQL 10 requires libICU!
Licence
Copyright (c) Pavel Stehule (pavel.stehule@gmail.com)
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Note
If you like it, send a postcard to address
Pavel Stehule
Skalice 12
256 01 Benesov u Prahy
Czech Republic
I invite any questions, comments, bug reports, patches on mail address pavel.stehule@gmail.com
Author: okbob
Source Code: https://github.com/okbob/plpgsql_check
License: View license
1648803600
Plpgsql Check: Extension That Allows to Check Plpgsql Source Code.
plpgsql_check
I founded this project, because I wanted to publish the code I wrote in the last two years, when I tried to write enhanced checking for PostgreSQL upstream. It was not fully successful - integration into upstream requires some larger plpgsql refactoring - probably it will not be done in next years (now is Dec 2013). But written code is fully functional and can be used in production (and it is used in production). So, I created this extension to be available for all plpgsql developers.
If you like it and if you would to join to development of this extension, register yourself to postgresql extension hacking google group.
Features
- check fields of referenced database objects and types inside embedded SQL
- using correct types of function parameters
- unused variables and function argumens, unmodified OUT argumens
- partially detection of dead code (due RETURN command)
- detection of missing RETURN command in function
- try to identify unwanted hidden casts, that can be performance issue like unused indexes
- possibility to collect relations and functions used by function
- possibility to check EXECUTE stmt agaist SQL injection vulnerability
I invite any ideas, patches, bugreports.
plpgsql_check is next generation of plpgsql_lint. It allows to check source code by explicit call plpgsql_check_function.
PostgreSQL PostgreSQL 10, 11, 12, 13 and 14 are supported.
The SQL statements inside PL/pgSQL functions are checked by validator for semantic errors. These errors can be found by plpgsql_check_function:
Active mode
postgres=# CREATE EXTENSION plpgsql_check;
LOAD
postgres=# CREATE TABLE t1(a int, b int);
CREATE TABLE
postgres=#
CREATE OR REPLACE FUNCTION public.f1()
RETURNS void
LANGUAGE plpgsql
AS $function$
DECLARE r record;
BEGIN
FOR r IN SELECT * FROM t1
LOOP
RAISE NOTICE '%', r.c; -- there is bug - table t1 missing "c" column
END LOOP;
END;
$function$;
CREATE FUNCTION
postgres=# select f1(); -- execution doesn't find a bug due to empty table t1
f1
ββββ
(1 row)
postgres=# \x
Expanded display is on.
postgres=# select * from plpgsql_check_function_tb('f1()');
β[ RECORD 1 ]βββββββββββββββββββββββββββ
functionid β f1
lineno β 6
statement β RAISE
sqlstate β 42703
message β record "r" has no field "c"
detail β [null]
hint β [null]
level β error
position β 0
query β [null]
postgres=# \sf+ f1
CREATE OR REPLACE FUNCTION public.f1()
RETURNS void
LANGUAGE plpgsql
1 AS $function$
2 DECLARE r record;
3 BEGIN
4 FOR r IN SELECT * FROM t1
5 LOOP
6 RAISE NOTICE '%', r.c; -- there is bug - table t1 missing "c" column
7 END LOOP;
8 END;
9 $function$
Function plpgsql_check_function() has three possible formats: text, json or xml
select * from plpgsql_check_function('f1()', fatal_errors := false);
plpgsql_check_function
------------------------------------------------------------------------
error:42703:4:SQL statement:column "c" of relation "t1" does not exist
Query: update t1 set c = 30
-- ^
error:42P01:7:RAISE:missing FROM-clause entry for table "r"
Query: SELECT r.c
-- ^
error:42601:7:RAISE:too few parameters specified for RAISE
(7 rows)
postgres=# select * from plpgsql_check_function('fx()', format:='xml');
plpgsql_check_function
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
<Function oid="16400"> β΅
<Issue> β΅
<Level>error</level> β΅
<Sqlstate>42P01</Sqlstate> β΅
<Message>relation "foo111" does not exist</Message> β΅
<Stmt lineno="3">RETURN</Stmt> β΅
<Query position="23">SELECT (select a from foo111)</Query>β΅
</Issue> β΅
</Function>
(1 row)
Arguments
You can set level of warnings via function's parameters:
Mandatory arguments
- function name or function signature - these functions requires function specification. Any function in PostgreSQL can be specified by Oid or by name or by signature. When you know oid or complete function's signature, you can use a regprocedure type parameter like
'fx()'::regprocedureor16799::regprocedure. Possible alternative is using a name only, when function's name is unique - like'fx'. When the name is not unique or the function doesn't exists it raises a error.
Optional arguments
relid DEFAULT 0 - oid of relation assigned with trigger function. It is necessary for check of any trigger function.
fatal_errors boolean DEFAULT true - stop on first error
other_warnings boolean DEFAULT true - show warnings like different attributes number in assignmenet on left and right side, variable overlaps function's parameter, unused variables, unwanted casting, ..
extra_warnings boolean DEFAULT true - show warnings like missing RETURN, shadowed variables, dead code, never read (unused) function's parameter, unmodified variables, modified auto variables, ..
performance_warnings boolean DEFAULT false - performance related warnings like declared type with type modificator, casting, implicit casts in where clause (can be reason why index is not used), ..
security_warnings boolean DEFAULT false - security related checks like SQL injection vulnerability detection
anyelementtype regtype DEFAULT 'int' - a real type used instead anyelement type
anyenumtype regtype DEFAULT '-' - a real type used instead anyenum type
anyrangetype regtype DEFAULT 'int4range' - a real type used instead anyrange type
anycompatibletype DEFAULT 'int' - a real type used instead anycompatible type
anycompatiblerangetype DEFAULT 'int4range' - a real type used instead anycompatible range type
without_warnings DEFAULT false - disable all warnings
all_warnings DEFAULT false - enable all warnings
newtable DEFAULT NULL, oldtable DEFAULT NULL - the names of NEW or OLD transitive tables. These parameters are required when transitive tables are used.
Triggers
When you want to check any trigger, you have to enter a relation that will be used together with trigger function
CREATE TABLE bar(a int, b int);
postgres=# \sf+ foo_trg
CREATE OR REPLACE FUNCTION public.foo_trg()
RETURNS trigger
LANGUAGE plpgsql
1 AS $function$
2 BEGIN
3 NEW.c := NEW.a + NEW.b;
4 RETURN NEW;
5 END;
6 $function$
Missing relation specification
postgres=# select * from plpgsql_check_function('foo_trg()');
ERROR: missing trigger relation
HINT: Trigger relation oid must be valid
Correct trigger checking (with specified relation)
postgres=# select * from plpgsql_check_function('foo_trg()', 'bar');
plpgsql_check_function
--------------------------------------------------------
error:42703:3:assignment:record "new" has no field "c"
(1 row)
For triggers with transitive tables you can set a oldtable or newtable parameters:
create or replace function footab_trig_func()
returns trigger as $$
declare x int;
begin
if false then
-- should be ok;
select count(*) from newtab into x;
-- should fail;
select count(*) from newtab where d = 10 into x;
end if;
return null;
end;
$$ language plpgsql;
select * from plpgsql_check_function('footab_trig_func','footab', newtable := 'newtab');
Mass check
You can use the plpgsql_check_function for mass check functions and mass check triggers. Please, test following queries:
-- check all nontrigger plpgsql functions
SELECT p.oid, p.proname, plpgsql_check_function(p.oid)
FROM pg_catalog.pg_namespace n
JOIN pg_catalog.pg_proc p ON pronamespace = n.oid
JOIN pg_catalog.pg_language l ON p.prolang = l.oid
WHERE l.lanname = 'plpgsql' AND p.prorettype <> 2279;
or
SELECT p.proname, tgrelid::regclass, cf.*
FROM pg_proc p
JOIN pg_trigger t ON t.tgfoid = p.oid
JOIN pg_language l ON p.prolang = l.oid
JOIN pg_namespace n ON p.pronamespace = n.oid,
LATERAL plpgsql_check_function(p.oid, t.tgrelid) cf
WHERE n.nspname = 'public' and l.lanname = 'plpgsql'
or
-- check all plpgsql functions (functions or trigger functions with defined triggers)
SELECT
(pcf).functionid::regprocedure, (pcf).lineno, (pcf).statement,
(pcf).sqlstate, (pcf).message, (pcf).detail, (pcf).hint, (pcf).level,
(pcf)."position", (pcf).query, (pcf).context
FROM
(
SELECT
plpgsql_check_function_tb(pg_proc.oid, COALESCE(pg_trigger.tgrelid, 0)) AS pcf
FROM pg_proc
LEFT JOIN pg_trigger
ON (pg_trigger.tgfoid = pg_proc.oid)
WHERE
prolang = (SELECT lang.oid FROM pg_language lang WHERE lang.lanname = 'plpgsql') AND
pronamespace <> (SELECT nsp.oid FROM pg_namespace nsp WHERE nsp.nspname = 'pg_catalog') AND
-- ignore unused triggers
(pg_proc.prorettype <> (SELECT typ.oid FROM pg_type typ WHERE typ.typname = 'trigger') OR
pg_trigger.tgfoid IS NOT NULL)
OFFSET 0
) ss
ORDER BY (pcf).functionid::regprocedure::text, (pcf).lineno
Passive mode
Functions should be checked on start - plpgsql_check module must be loaded.
Configuration
plpgsql_check.mode = [ disabled | by_function | fresh_start | every_start ]
plpgsql_check.fatal_errors = [ yes | no ]
plpgsql_check.show_nonperformance_warnings = false
plpgsql_check.show_performance_warnings = false
Default mode is by_function, that means that the enhanced check is done only in active mode - by plpgsql_check_function. fresh_start means cold start.
You can enable passive mode by
load 'plpgsql'; -- 1.1 and higher doesn't need it
load 'plpgsql_check';
set plpgsql_check.mode = 'every_start';
SELECT fx(10); -- run functions - function is checked before runtime starts it
Limits
plpgsql_check should find almost all errors on really static code. When developer use some PLpgSQL's dynamic features like dynamic SQL or record data type, then false positives are possible. These should be rare - in well written code - and then the affected function should be redesigned or plpgsql_check should be disabled for this function.
CREATE OR REPLACE FUNCTION f1()
RETURNS void AS $$
DECLARE r record;
BEGIN
FOR r IN EXECUTE 'SELECT * FROM t1'
LOOP
RAISE NOTICE '%', r.c;
END LOOP;
END;
$$ LANGUAGE plpgsql SET plpgsql.enable_check TO false;
A usage of plpgsql_check adds a small overhead (in enabled passive mode) and you should use it only in develop or preprod environments.
Dynamic SQL
This module doesn't check queries that are assembled in runtime. It is not possible to identify results of dynamic queries - so plpgsql_check cannot to set correct type to record variables and cannot to check a dependent SQLs and expressions.
When type of record's variable is not know, you can assign it explicitly with pragma type:
DECLARE r record;
BEGIN
EXECUTE format('SELECT * FROM %I', _tablename) INTO r;
PERFORM plpgsql_check_pragma('type: r (id int, processed bool)');
IF NOT r.processed THEN
...
Attention: The SQL injection check can detect only some SQL injection vulnerabilities. This tool cannot be used for security audit! Some issues should not be detected. This check can raise false alarms too - probably when variable is sanitized by other command or when value is of some compose type.
Refcursors
plpgsql_check should not to detect structure of referenced cursors. A reference on cursor in PLpgSQL is implemented as name of global cursor. In check time, the name is not known (not in all possibilities), and global cursor doesn't exist. It is significant break for any static analyse. PLpgSQL cannot to set correct type for record variables and cannot to check a dependent SQLs and expressions. A solution is same like dynamic SQL. Don't use record variable as target when you use refcursor type or disable plpgsql_check for these functions.
CREATE OR REPLACE FUNCTION foo(refcur_var refcursor)
RETURNS void AS $$
DECLARE
rec_var record;
BEGIN
FETCH refcur_var INTO rec_var; -- this is STOP for plpgsql_check
RAISE NOTICE '%', rec_var; -- record rec_var is not assigned yet error
In this case a record type should not be used (use known rowtype instead):
CREATE OR REPLACE FUNCTION foo(refcur_var refcursor)
RETURNS void AS $$
DECLARE
rec_var some_rowtype;
BEGIN
FETCH refcur_var INTO rec_var;
RAISE NOTICE '%', rec_var;
Temporary tables
plpgsql_check cannot verify queries over temporary tables that are created in plpgsql's function runtime. For this use case it is necessary to create a fake temp table or disable plpgsql_check for this function.
In reality temp tables are stored in own (per user) schema with higher priority than persistent tables. So you can do (with following trick safetly):
CREATE OR REPLACE FUNCTION public.disable_dml()
RETURNS trigger
LANGUAGE plpgsql AS $function$
BEGIN
RAISE EXCEPTION SQLSTATE '42P01'
USING message = format('this instance of %I table doesn''t allow any DML operation', TG_TABLE_NAME),
hint = format('you should to run "CREATE TEMP TABLE %1$I(LIKE %1$I INCLUDING ALL);" statement',
TG_TABLE_NAME);
RETURN NULL;
END;
$function$;
CREATE TABLE foo(a int, b int); -- doesn't hold data ever
CREATE TRIGGER foo_disable_dml
BEFORE INSERT OR UPDATE OR DELETE ON foo
EXECUTE PROCEDURE disable_dml();
postgres=# INSERT INTO foo VALUES(10,20);
ERROR: this instance of foo table doesn't allow any DML operation
HINT: you should to run "CREATE TEMP TABLE foo(LIKE foo INCLUDING ALL);" statement
postgres=#
CREATE TABLE
postgres=# INSERT INTO foo VALUES(10,20);
INSERT 0 1
This trick emulates GLOBAL TEMP tables partially and it allows a statical validation. Other possibility is using a [template foreign data wrapper] (https://github.com/okbob/template_fdw)
You can use pragma table and create ephemeral table:
BEGIN
CREATE TEMP TABLE xxx(a int);
PERFORM plpgsql_check_pragma('table: xxx(a int)');
INSERT INTO xxx VALUES(10);
Dependency list
A function plpgsql_show_dependency_tb can show all functions, operators and relations used inside processed function:
postgres=# select * from plpgsql_show_dependency_tb('testfunc(int,float)');
ββββββββββββ¬ββββββββ¬βββββββββ¬ββββββββββ¬βββββββββββββββββββββββββββββ
β type β oid β schema β name β params β
ββββββββββββͺββββββββͺβββββββββͺββββββββββͺβββββββββββββββββββββββββββββ‘
β FUNCTION β 36008 β public β myfunc1 β (integer,double precision) β
β FUNCTION β 35999 β public β myfunc2 β (integer,double precision) β
β OPERATOR β 36007 β public β ** β (integer,integer) β
β RELATION β 36005 β public β myview β β
β RELATION β 36002 β public β mytable β β
ββββββββββββ΄ββββββββ΄βββββββββ΄ββββββββββ΄βββββββββββββββββββββββββββββ
(4 rows)
Profiler
The plpgsql_check contains simple profiler of plpgsql functions and procedures. It can work with/without a access to shared memory. It depends on shared_preload_libraries config. When plpgsql_check was initialized by shared_preload_libraries, then it can allocate shared memory, and function's profiles are stored there. When plpgsql_check cannot to allocate shared momory, the profile is stored in session memory.
Due dependencies, shared_preload_libraries should to contains plpgsql first
postgres=# show shared_preload_libraries ;
ββββββββββββββββββββββββββββ
β shared_preload_libraries β
ββββββββββββββββββββββββββββ‘
β plpgsql,plpgsql_check β
ββββββββββββββββββββββββββββ
(1 row)
The profiler is active when GUC plpgsql_check.profiler is on. The profiler doesn't require shared memory, but if there are not shared memory, then the profile is limmitted just to active session.
When plpgsql_check is initialized by shared_preload_libraries, another GUC is available to configure the amount of shared memory used by the profiler: plpgsql_check.profiler_max_shared_chunks. This defines the maximum number of statements chunk that can be stored in shared memory. For each plpgsql function (or procedure), the whole content is split into chunks of 30 statements. If needed, multiple chunks can be used to store the whole content of a single function. A single chunk is 1704 bytes. The default value for this GUC is 15000, which should be enough for big projects containing hundred of thousands of statements in plpgsql, and will consume about 24MB of memory. If your project doesn't require that much number of chunks, you can set this parameter to a smaller number in order to decrease the memory usage. The minimum value is 50 (which should consume about 83kB of memory), and the maximum value is 100000 (which should consume about 163MB of memory). Changing this parameter requires a PostgreSQL restart.
The profiler will also retrieve the query identifier for each instruction that contains an expression or optimizable statement. Note that this requires pg_stat_statements, or another similar third-party extension), to be installed. There are some limitations to the query identifier retrieval:
- if a plpgsql expression contains underlying statements, only the top level query identifier will be retrieved
- the profiler doesn't compute query identifier by itself but relies on external extension, such as pg_stat_statements, for that. It means that depending on the external extension behavior, you may not be able to see a query identifier for some statements. That's for instance the case with DDL statements, as pg_stat_statements doesn't expose the query identifier for such queries.
- a query identifier is retrieved only for instructions containing expressions. This means that plpgsql_profiler_function_tb() function can report less query identifier than instructions on a single line.
Attention: A update of shared profiles can decrease performance on servers under higher load.
The profile can be displayed by function plpgsql_profiler_function_tb:
postgres=# select lineno, avg_time, source from plpgsql_profiler_function_tb('fx(int)');
ββββββββββ¬βββββββββββ¬ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β lineno β avg_time β source β
ββββββββββͺβββββββββββͺββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ‘
β 1 β β β
β 2 β β declare result int = 0; β
β 3 β 0.075 β begin β
β 4 β 0.202 β for i in 1..$1 loop β
β 5 β 0.005 β select result + i into result; select result + i into result; β
β 6 β β end loop; β
β 7 β 0 β return result; β
β 8 β β end; β
ββββββββββ΄βββββββββββ΄ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
(9 rows)
The profile per statements (not per line) can be displayed by function plpgsql_profiler_function_statements_tb:
CREATE OR REPLACE FUNCTION public.fx1(a integer)
RETURNS integer
LANGUAGE plpgsql
1 AS $function$
2 begin
3 if a > 10 then
4 raise notice 'ahoj';
5 return -1;
6 else
7 raise notice 'nazdar';
8 return 1;
9 end if;
10 end;
11 $function$
postgres=# select stmtid, parent_stmtid, parent_note, lineno, exec_stmts, stmtname
from plpgsql_profiler_function_statements_tb('fx1');
ββββββββββ¬ββββββββββββββββ¬ββββββββββββββ¬βββββββββ¬βββββββββββββ¬ββββββββββββββββββ
β stmtid β parent_stmtid β parent_note β lineno β exec_stmts β stmtname β
ββββββββββͺββββββββββββββββͺββββββββββββββͺβββββββββͺβββββββββββββͺββββββββββββββββββ‘
β 0 β β
β β
β 2 β 0 β statement block β
β 1 β 0 β body β 3 β 0 β IF β
β 2 β 1 β then body β 4 β 0 β RAISE β
β 3 β 1 β then body β 5 β 0 β RETURN β
β 4 β 1 β else body β 7 β 0 β RAISE β
β 5 β 1 β else body β 8 β 0 β RETURN β
ββββββββββ΄ββββββββββββββββ΄ββββββββββββββ΄βββββββββ΄βββββββββββββ΄ββββββββββββββββββ
(6 rows)
All stored profiles can be displayed by calling function plpgsql_profiler_functions_all:
postgres=# select * from plpgsql_profiler_functions_all();
βββββββββββββββββββββββββ¬βββββββββββββ¬βββββββββββββ¬βββββββββββ¬ββββββββββββββ¬βββββββββββ¬βββββββββββ
β funcoid β exec_count β total_time β avg_time β stddev_time β min_time β max_time β
βββββββββββββββββββββββββͺβββββββββββββͺβββββββββββββͺβββββββββββͺββββββββββββββͺβββββββββββͺβββββββββββ‘
β fxx(double precision) β 1 β 0.01 β 0.01 β 0.00 β 0.01 β 0.01 β
βββββββββββββββββββββββββ΄βββββββββββββ΄βββββββββββββ΄βββββββββββ΄ββββββββββββββ΄βββββββββββ΄βββββββββββ
(1 row)
There are two functions for cleaning stored profiles: plpgsql_profiler_reset_all() and plpgsql_profiler_reset(regprocedure).
Coverage metrics
plpgsql_check provides two functions:
plpgsql_coverage_statements(name)plpgsql_coverage_branches(name)
Note
There is another very good PLpgSQL profiler - https://bitbucket.org/openscg/plprofiler
My extension is designed to be simple for use and practical. Nothing more or less.
plprofiler is more complex. It build call graphs and from this graph it can creates flame graph of execution times.
Both extensions can be used together with buildin PostgreSQL's feature - tracking functions.
set track_functions to 'pl';
...
select * from pg_stat_user_functions;
Tracer
plpgsql_check provides a tracing possibility - in this mode you can see notices on start or end functions (terse and default verbosity) and start or end statements (verbose verbosity). For default and verbose verbosity the content of function arguments is displayed. The content of related variables are displayed when verbosity is verbose.
postgres=# do $$ begin perform fx(10,null, 'now', e'stΔhule'); end; $$;
NOTICE: #0 ->> start of inline_code_block (Oid=0)
NOTICE: #2 ->> start of function fx(integer,integer,date,text) (Oid=16405)
NOTICE: #2 call by inline_code_block line 1 at PERFORM
NOTICE: #2 "a" => '10', "b" => null, "c" => '2020-08-03', "d" => 'stΔhule'
NOTICE: #4 ->> start of function fx(integer) (Oid=16404)
NOTICE: #4 call by fx(integer,integer,date,text) line 1 at PERFORM
NOTICE: #4 "a" => '10'
NOTICE: #4 <<- end of function fx (elapsed time=0.098 ms)
NOTICE: #2 <<- end of function fx (elapsed time=0.399 ms)
NOTICE: #0 <<- end of block (elapsed time=0.754 ms)
The number after # is a execution frame counter (this number is related to deep of error context stack). It allows to pair start end and of function.
Tracing is enabled by setting plpgsql_check.tracer to on. Attention - enabling this behaviour has significant negative impact on performance (unlike the profiler). You can set a level for output used by tracer plpgsql_check.tracer_errlevel (default is notice). The output content is limited by length specified by plpgsql_check.tracer_variable_max_length configuration variable.
In terse verbose mode the output is reduced:
postgres=# set plpgsql_check.tracer_verbosity TO terse;
SET
postgres=# do $$ begin perform fx(10,null, 'now', e'stΔhule'); end; $$;
NOTICE: #0 start of inline code block (oid=0)
NOTICE: #2 start of fx (oid=16405)
NOTICE: #4 start of fx (oid=16404)
NOTICE: #4 end of fx
NOTICE: #2 end of fx
NOTICE: #0 end of inline code block
In verbose mode the output is extended about statement details:
postgres=# do $$ begin perform fx(10,null, 'now', e'stΔhule'); end; $$;
NOTICE: #0 ->> start of block inline_code_block (oid=0)
NOTICE: #0.1 1 --> start of PERFORM
NOTICE: #2 ->> start of function fx(integer,integer,date,text) (oid=16405)
NOTICE: #2 call by inline_code_block line 1 at PERFORM
NOTICE: #2 "a" => '10', "b" => null, "c" => '2020-08-04', "d" => 'stΔhule'
NOTICE: #2.1 1 --> start of PERFORM
NOTICE: #2.1 "a" => '10'
NOTICE: #4 ->> start of function fx(integer) (oid=16404)
NOTICE: #4 call by fx(integer,integer,date,text) line 1 at PERFORM
NOTICE: #4 "a" => '10'
NOTICE: #4.1 6 --> start of assignment
NOTICE: #4.1 "a" => '10', "b" => '20'
NOTICE: #4.1 <-- end of assignment (elapsed time=0.076 ms)
NOTICE: #4.1 "res" => '130'
NOTICE: #4.2 7 --> start of RETURN
NOTICE: #4.2 "res" => '130'
NOTICE: #4.2 <-- end of RETURN (elapsed time=0.054 ms)
NOTICE: #4 <<- end of function fx (elapsed time=0.373 ms)
NOTICE: #2.1 <-- end of PERFORM (elapsed time=0.589 ms)
NOTICE: #2 <<- end of function fx (elapsed time=0.727 ms)
NOTICE: #0.1 <-- end of PERFORM (elapsed time=1.147 ms)
NOTICE: #0 <<- end of block (elapsed time=1.286 ms)
Special feature of tracer is tracing of ASSERT statement when plpgsql_check.trace_assert is on. When plpgsql_check.trace_assert_verbosity is DEFAULT, then all function's or procedure's variables are displayed when assert expression is false. When this configuration is VERBOSE then all variables from all plpgsql frames are displayed. This behaviour is independent on plpgsql.check_asserts value. It can be used, although the assertions are disabled in plpgsql runtime.
postgres=# set plpgsql_check.tracer to off;
postgres=# set plpgsql_check.trace_assert_verbosity TO verbose;
postgres=# do $$ begin perform fx(10,null, 'now', e'stΔhule'); end; $$;
NOTICE: #4 PLpgSQL assert expression (false) on line 12 of fx(integer) is false
NOTICE: "a" => '10', "res" => null, "b" => '20'
NOTICE: #2 PL/pgSQL function fx(integer,integer,date,text) line 1 at PERFORM
NOTICE: "a" => '10', "b" => null, "c" => '2020-08-05', "d" => 'stΔhule'
NOTICE: #0 PL/pgSQL function inline_code_block line 1 at PERFORM
ERROR: assertion failed
CONTEXT: PL/pgSQL function fx(integer) line 12 at ASSERT
SQL statement "SELECT fx(a)"
PL/pgSQL function fx(integer,integer,date,text) line 1 at PERFORM
SQL statement "SELECT fx(10,null, 'now', e'stΔhule')"
PL/pgSQL function inline_code_block line 1 at PERFORM
postgres=# set plpgsql.check_asserts to off;
SET
postgres=# do $$ begin perform fx(10,null, 'now', e'stΔhule'); end; $$;
NOTICE: #4 PLpgSQL assert expression (false) on line 12 of fx(integer) is false
NOTICE: "a" => '10', "res" => null, "b" => '20'
NOTICE: #2 PL/pgSQL function fx(integer,integer,date,text) line 1 at PERFORM
NOTICE: "a" => '10', "b" => null, "c" => '2020-08-05', "d" => 'stΔhule'
NOTICE: #0 PL/pgSQL function inline_code_block line 1 at PERFORM
DO
Attention - SECURITY
Tracer prints content of variables or function arguments. For security definer function, this content can hold security sensitive data. This is reason why tracer is disabled by default and should be enabled only with super user rights plpgsql_check.enable_tracer.
Pragma
You can configure plpgsql_check behave inside checked function with "pragma" function. This is a analogy of PL/SQL or ADA language of PRAGMA feature. PLpgSQL doesn't support PRAGMA, but plpgsql_check detects function named plpgsql_check_pragma and get options from parameters of this function. These plpgsql_check options are valid to end of group of statements.
CREATE OR REPLACE FUNCTION test()
RETURNS void AS $$
BEGIN
...
-- for following statements disable check
PERFORM plpgsql_check_pragma('disable:check');
...
-- enable check again
PERFORM plpgsql_check_pragma('enable:check');
...
END;
$$ LANGUAGE plpgsql;
The function plpgsql_check_pragma is immutable function that returns one. It is defined by plpgsql_check extension. You can declare alternative plpgsql_check_pragma function like:
CREATE OR REPLACE FUNCTION plpgsql_check_pragma(VARIADIC args[])
RETURNS int AS $$
SELECT 1
$$ LANGUAGE sql IMMUTABLE;
Using pragma function in declaration part of top block sets options on function level too.
CREATE OR REPLACE FUNCTION test()
RETURNS void AS $$
DECLARE
aux int := plpgsql_check_pragma('disable:extra_warnings');
...
Shorter syntax for pragma is supported too:
CREATE OR REPLACE FUNCTION test()
RETURNS void AS $$
DECLARE r record;
BEGIN
PERFORM 'PRAGMA:TYPE:r (a int, b int)';
PERFORM 'PRAGMA:TABLE: x (like pg_class)';
...
Supported pragmas
echo:str - print string (for testing)
status:check,status:tracer, status:other_warnings, status:performance_warnings, status:extra_warnings,status:security_warnings
enable:check,enable:tracer, enable:other_warnings, enable:performance_warnings, enable:extra_warnings,enable:security_warnings
disable:check,disable:tracer, disable:other_warnings, disable:performance_warnings, disable:extra_warnings,disable:security_warnings
type:varname typename or type:varname (fieldname type, ...) - set type to variable of record type
table: name (column_name type, ...) or table: name (like tablename) - create ephereal table
Pragmas enable:tracer and disable:tracerare active for Postgres 12 and higher
Compilation
You need a development environment for PostgreSQL extensions:
make clean
make install
result:
[pavel@localhost plpgsql_check]$ make USE_PGXS=1 clean
rm -f plpgsql_check.so libplpgsql_check.a libplpgsql_check.pc
rm -f plpgsql_check.o
rm -rf results/ regression.diffs regression.out tmp_check/ log/
[pavel@localhost plpgsql_check]$ make USE_PGXS=1 all
clang -O2 -Wall -Wmissing-prototypes -Wpointer-arith -Wdeclaration-after-statement -Wendif-labels -Wmissing-format-attribute -Wformat-security -fno-strict-aliasing -fwrapv -fpic -I/usr/local/pgsql/lib/pgxs/src/makefiles/../../src/pl/plpgsql/src -I. -I./ -I/usr/local/pgsql/include/server -I/usr/local/pgsql/include/internal -D_GNU_SOURCE -c -o plpgsql_check.o plpgsql_check.c
clang -O2 -Wall -Wmissing-prototypes -Wpointer-arith -Wdeclaration-after-statement -Wendif-labels -Wmissing-format-attribute -Wformat-security -fno-strict-aliasing -fwrapv -fpic -I/usr/local/pgsql/lib/pgxs/src/makefiles/../../src/pl/plpgsql/src -shared -o plpgsql_check.so plpgsql_check.o -L/usr/local/pgsql/lib -Wl,--as-needed -Wl,-rpath,'/usr/local/pgsql/lib',--enable-new-dtags
[pavel@localhost plpgsql_check]$ su root
Password: *******
[root@localhost plpgsql_check]# make USE_PGXS=1 install
/usr/bin/mkdir -p '/usr/local/pgsql/lib'
/usr/bin/mkdir -p '/usr/local/pgsql/share/extension'
/usr/bin/mkdir -p '/usr/local/pgsql/share/extension'
/usr/bin/install -c -m 755 plpgsql_check.so '/usr/local/pgsql/lib/plpgsql_check.so'
/usr/bin/install -c -m 644 plpgsql_check.control '/usr/local/pgsql/share/extension/'
/usr/bin/install -c -m 644 plpgsql_check--0.9.sql '/usr/local/pgsql/share/extension/'
[root@localhost plpgsql_check]# exit
[pavel@localhost plpgsql_check]$ make USE_PGXS=1 installcheck
/usr/local/pgsql/lib/pgxs/src/makefiles/../../src/test/regress/pg_regress --inputdir=./ --psqldir='/usr/local/pgsql/bin' --dbname=pl_regression --load-language=plpgsql --dbname=contrib_regression plpgsql_check_passive plpgsql_check_active plpgsql_check_active-9.5
(using postmaster on Unix socket, default port)
============== dropping database "contrib_regression" ==============
DROP DATABASE
============== creating database "contrib_regression" ==============
CREATE DATABASE
ALTER DATABASE
============== installing plpgsql ==============
CREATE LANGUAGE
============== running regression test queries ==============
test plpgsql_check_passive ... ok
test plpgsql_check_active ... ok
test plpgsql_check_active-9.5 ... ok
=====================
All 3 tests passed.
=====================
Compilation on Ubuntu
Sometimes successful compilation can require libicu-dev package (PostgreSQL 10 and higher - when pg was compiled with ICU support)
sudo apt install libicu-dev
Compilation plpgsql_check on Windows
You can check precompiled dll libraries http://okbob.blogspot.cz/2015/02/plpgsqlcheck-is-available-for-microsoft.html
or compile by self:
- Download and install PostgreSQL for Win32 from http://www.enterprisedb.com
- Download and install Microsoft Visual C++ Express
- Lern tutorial http://blog.2ndquadrant.com/compiling-postgresql-extensions-visual-studio-windows
- Build plpgsql_check.dll
- Install plugin
- copy
plpgsql_check.dlltoPostgreSQL\14\lib - copy
plpgsql_check.controlandplpgsql_check--2.1.sqltoPostgreSQL\14\share\extension
Checked on
- gcc on Linux (against all supported PostgreSQL)
- clang 3.4 on Linux (against PostgreSQL 10)
- for success regress tests the PostgreSQL 10 or higher is required
Compilation against PostgreSQL 10 requires libICU!
Licence
Copyright (c) Pavel Stehule (pavel.stehule@gmail.com)
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Note
If you like it, send a postcard to address
Pavel Stehule
Skalice 12
256 01 Benesov u Prahy
Czech Republic
I invite any questions, comments, bug reports, patches on mail address pavel.stehule@gmail.com
Author: okbob
Source Code: https://github.com/okbob/plpgsql_check
License: View license
1675304280
How to Use Hotwire Rails
Introduction
We are back with another exciting and much-talked-about Rails tutorial on how to use Hotwire with the Rails application. This Hotwire Rails tutorial is an alternate method for building modern web applications that consume a pinch of JavaScript.
Rails 7 Hotwire is the default front-end framework shipped with Rails 7 after it was launched. It is used to represent HTML over the wire in the Rails application. Previously, we used to add a hotwire-rails gem in our gem file and then run rails hotwire: install. However, with the introduction of Rails 7, the gem got deprecated. Now, we use turbo-rails and stimulus rails directly, which work as Hotwireβs SPA-like page accelerator and Hotwireβs modest JavaScript framework.
What is Hotwire?
Hotwire is a package of different frameworks that help to build applications. It simplifies the developerβs work for writing web pages without the need to write JavaScript, and instead sending HTML code over the wire.
Introduction to The Hotwire Framework:
1. Turbo:
It uses simplified techniques to build web applications while decreasing the usage of JavaScript in the application. Turbo offers numerous handling methods for the HTML data sent over the wire and displaying the applicationβs data without actually loading the entire page. It helps to maintain the simplicity of web applications without destroying the single-page application experience by using the below techniques:
Turbo Frames: Turbo Frames help to load the different sections of our markup without any dependency as it divides the page into different contexts separately called frames and updates these frames individually.
Turbo Drive: Every link doesnβt have to make the entire page reload when clicked. Only the HTML contained within the tag will be displayed.
Turbo Streams: To add real-time features to the application, this technique is used. It helps to bring real-time data to the application using CRUD actions.
2. Stimulus
It represents the JavaScript framework, which is required when JS is a requirement in the application. The interaction with the HTML is possible with the help of a stimulus, as the controllers that help those interactions are written by a stimulus.
3. Strada
Not much information is available about Strada as it has not been officially released yet. However, it works with native applications, and by using HTML bridge attributes, interaction is made possible between web applications and native apps.
Simple diagrammatic representation of Hotwire Stack:
Prerequisites For Hotwire Rails Tutorial
As we are implementing the Ruby on Rails Hotwire tutorial, make sure about the following installations before you can get started.
- Ruby on Rails
- Hotwire gem
- PostgreSQL/SQLite (choose any one database)
- Turbo Rails
- Stimulus.js
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Create a new Rails Project
Find the following commands to create a rails application.
mkdir ~/projects/railshotwire
cd ~/projects/railshotwire
echo "source 'https://rubygems.org'" > Gemfile
echo "gem 'rails', '~> 7.0.0'" >> Gemfile
bundle install
bundle exec rails new . --force -d=postgresqlNow create some files for the project, up till now no usage of Rails Hotwire can be seen.
Fire the following command in your terminal.
- For creating a default controller for the application
echo "class HomeController < ApplicationController" > app/controllers/home_controller.rb
echo "end" >> app/controllers/home_controller.rb- For creating another controller for the application
echo "class OtherController < ApplicationController" > app/controllers/other_controller.rb
echo "end" >> app/controllers/home_controller.rb- For creating routes for the application
echo "Rails.application.routes.draw do" > config/routes.rb
echo ' get "home/index"' >> config/routes.rb
echo ' get "other/index"' >> config/routes.rb
echo ' root to: "home#index"' >> config/routes.rb
echo 'end' >> config/routes.rb- For creating a default view for the application
mkdir app/views/home
echo '<h1>This is Rails Hotwire homepage</h1>' > app/views/home/index.html.erb
echo '<div><%= link_to "Enter to other page", other_index_path %></div>' >> app/views/home/index.html.erb
- For creating another view for the application
mkdir app/views/other
echo '<h1>This is Another page</h1>' > app/views/other/index.html.erb
echo '<div><%= link_to "Enter to home page", root_path %></div>' >> app/views/other/index.html.erb
- For creating a database and schema.rb file for the application
bin/rails db:create
bin/rails db:migrate- For checking the application run bin/rails s and open your browser, your running application will have the below view.
Additionally, you can clone the code and browse through the project. Hereβs the source code of the repository: Rails 7 Hotwire application
Now, letβs see how Hotwire Rails can work its magic with various Turbo techniques.
Hotwire Rails: Turbo Drive
Go to your localhost:3000 on your web browser and right-click on the Inspect and open a Network tab of the DevTools of the browser.
Now click on go to another page link that appears on the home page to redirect from the home page to another page. In our Network tab, we can see that this action of navigation is achieved via XHR. It appears only the part inside HTML is reloaded, here neither the CSS is reloaded nor the JS is reloaded when the navigation action is performed.
By performing this action we can see that Turbo Drive helps to represent the HTML response without loading the full page and only follows redirect and reindeer HTML responses which helps to make the application faster to access.
Hotwire Rails: Turbo Frame
This technique helps to divide the current page into different sections called frames that can be updated separately independently when new data is added from the server.
Below we discuss the different use cases of Turbo frame like inline edition, sorting, searching, and filtering of data.
Letβs perform some practical actions to see the example of these use cases.
Make changes in the app/controllers/home_controller.rb file
#CODE
class HomeController < ApplicationController
def turbo_frame_form
end
def turbo_frame submit
extracted_anynumber = params[:any][:anynumber]
render :turbo_frame_form, status: :ok, locals: {anynumber: extracted_anynumber, comment: 'turbo_frame_submit ok' }
end
end
Add app/views/home/turbo_frame_form.html.erb file to the application and add this content inside the file.
#CODE
<section>
<%= turbo_frame_tag 'anyframe' do %>
<div>
<h2>Frame view</h2>
<%= form_with scope: :any, url: turbo_frame_submit_path, local: true do |form| %>
<%= form.label :anynumber, 'Type an integer (odd or even)', 'class' => 'my-0 d-inline' %>
<%= form.text_field :anynumber, type: 'number', 'required' => 'true', 'value' => "#{local_assigns[:anynumber] || 0}", 'aria-describedby' => 'anynumber' %>
<%= form.submit 'Submit this number', 'id' => 'submit-number' %>
<% end %>
</div>
<div>
<h2>Data of the view</h2>
<pre style="font-size: .7rem;"><%= JSON.pretty_generate(local_assigns) %></pre>
</div>
<% end %>
</section>
Make some adjustments in routes.rb
#CODE
Rails.application.routes.draw do
get 'home/index'
get 'other/index'
get '/home/turbo_frame_form' => 'home#turbo_frame_form', as: 'turbo_frame_form'
post '/home/turbo_frame_submit' => 'home#turbo_frame_submit', as: 'turbo_frame_submit'
root to: "home#index"
end- Next step is to change homepage view in app/views/home/index.html.erb
#CODE
<h1>This is Rails Hotwire home page</h1>
<div><%= link_to "Enter to other page", other_index_path %></div>
<%= turbo_frame_tag 'anyframe' do %>
<div>
<h2>Home view</h2>
<%= form_with scope: :any, url: turbo_frame_submit_path, local: true do |form| %>
<%= form.label :anynumber, 'Type an integer (odd or even)', 'class' => 'my-0 d-inline' %>
<%= form.text_field :anynumber, type: 'number', 'required' => 'true', 'value' => "#{local_assigns[:anynumber] || 0}", 'aria-describedby' => 'anynumber' %>
<%= form.submit 'Submit this number', 'id' => 'submit-number' %>
<% end %>
<div>
<% end %>
After making all the changes, restart the rails server and refresh the browser, the default view will appear on the browser.
Now in the field enter any digit, after entering the digit click on submit button, and as the submit button is clicked we can see the Turbo Frame in action in the below screen, we can observe that the frame part changed, the first title and first link didnβt move.
Hotwire Rails: Turbo Streams
Turbo Streams deliver page updates over WebSocket, SSE or in response to form submissions by only using HTML and a series of CRUD-like operations, you are free to say that either
- Update the piece of HTML while responding to all the other actions like the post, put, patch, and delete except the GET action.
- Transmit a change to all users, without reloading the browser page.
This transmit can be represented by a simple example.
- Make changes in app/controllers/other_controller.rb file of rails application
#CODE
class OtherController < ApplicationController
def post_something
respond_to do |format|
format.turbo_stream { }
end
end
end
Add the below line in routes.rb file of the application
#CODE
post '/other/post_something' => 'other#post_something', as: 'post_something'
Superb! Rails will now attempt to locate the app/views/other/post_something.turbo_stream.erb template at any moment the β/other/post_somethingβ endpoint is reached.
For this, we need to add app/views/other/post_something.turbo_stream.erb template in the rails application.
#CODE
<turbo-stream action="append" target="messages">
<template>
<div id="message_1">This changes the existing message!</div>
</template>
</turbo-stream>
This states that the response will try to append the template of the turbo frame with ID βmessagesβ.
Now change the index.html.erb file in app/views/other paths with the below content.
#CODE
<h1>This is Another page</h1>
<div><%= link_to "Enter to home page", root_path %></div>
<div style="margin-top: 3rem;">
<%= form_with scope: :any, url: post_something_path do |form| %>
<%= form.submit 'Post any message %>
<% end %>
<turbo-frame id="messages">
<div>An empty message</div>
</turbo-frame>
</div>
- After making all the changes, restart the rails server and refresh the browser, and go to the other page.
- Once the above screen appears, click on the Post any message button
This action shows that after submitting the response, the Turbo Streams help the developer to append the message, without reloading the page.
Another use case we can test is that rather than appending the message, the developer replaces the message. For that, we need to change the content of app/views/other/post_something.turbo_stream.erb template file and change the value of the action attribute from append to replace and check the changes in the browser.
#CODE
<turbo-stream action="replace" target="messages">
<template>
<div id="message_1">This changes the existing message!</div>
</template>
</turbo-stream>
When we click on Post any message button, the message that appear below that button will get replaced with the message that is mentioned in the app/views/other/post_something.turbo_stream.erb template
Stimulus
There are some cases in an application where JS is needed, therefore to cover those scenarios we require Hotwire JS tool. Hotwire has a JS tool because in some scenarios Turbo-* tools are not sufficient. But as we know that Hotwire is used to reduce the usage of JS in an application, Stimulus considers HTML as the single source of truth. Consider the case where we have to give elements on a page some JavaScript attributes, such as data controller, data-action, and data target. For that, a stimulus controller that can access elements and receive events based on those characteristics will be created.
Make a change in app/views/other/index.html.erb template file in rails application
#CODE
<h1>This is Another page</h1>
<div><%= link_to "Enter to home page", root_path %></div>
<div style="margin-top: 2rem;">
<%= form_with scope: :any, url: post_something_path do |form| %>
<%= form.submit 'Post something' %>
<% end %>
<turbo-frame id="messages">
<div>An empty message</div>
</turbo-frame>
</div>
<div style="margin-top: 2rem;">
<h2>Stimulus</h2>
<div data-controller="hello">
<input data-hello-target="name" type="text">
<button data-action="click->hello#greet">
Greet
</button>
<span data-hello-target="output">
</span>
</div>
</div>
Make changes in the hello_controller.js in path app/JavaScript/controllers and add a stimulus controller in the file, which helps to bring the HTML into life.
#CODE
import { Controller } from "@hotwired/stimulus"
export default class extends Controller {
static targets = [ "name", "output" ]
greet() {
this.outputTarget.textContent =
`Hello, ${this.nameTarget.value}!`
}
}
Go to your browser after making the changes in the code and click on Enter to other page link which will navigate to the localhost:3000/other/index page there you can see the changes implemented by the stimulus controller that is designed to augment your HTML with just enough behavior to make it more responsive.
With just a little bit of work, Turbo and Stimulus together offer a complete answer for applications that are quick and compelling.
Using Rails 7 Hotwire helps to load the pages at a faster speed and allows you to render templates on the server, where you have access to your whole domain model. It is a productive development experience in ROR, without compromising any of the speed or responsiveness associated with SPA.
Conclusion
We hope you were satisfied with our Rails Hotwire tutorial. Write to us at service@bacancy.com for any query that you want to resolve, or if you want us to share a tutorial on your query.
For more such solutions on RoR, check out our Ruby on Rails Tutorials. We will always strive to amaze you and cater to your needs.
Original article source at: https://www.bacancytechnology.com/
1669952228
Dijkstra's Algorithm Explained with Examples
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.
How Does Dijkstraβs Algorithm Work?
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 β 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.
Dijkstra's Algorithm Example
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 | β |
| B | β |
| C | β |
| D | β |
| E | β |
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 (β). This is because we don't know the shortest distance yet.
We also have two arrays β 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.
Iteration #1
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 | β |
| C | β |
| D | β |
| E | β |
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 | β |
| E | β |
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:
- Once a node has been visited, it cannot be linked to the current node. Refer to step #2 in the iteration above and step #2 in the next iteration.
- A node cannot be visited twice.
- You can only update the shortest known distance if you get a value smaller than the recorded distance.
Iteration #2
Step #1 - Pick an unvisited node
We have four unvisited nodes β [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 | β |
| E | β |
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,
- The green color denotes the current node.
- The blue color denotes the visited nodes. We cannot link to them or visit them again.
- The red color shows the link from the unvisited nodes to the current node.
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 | β |
| E | β |
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]
Iteration #3
Step #1 - Pick an unvisited node
We're down to three unvisited nodes β [B,D,E]. From the array, B has the shortest known distance.
To restate what is going on in the diagram above:
- The green color denotes the current node.
- The blue color denotes the visited nodes. We cannot link to them or visit them again.
- The red color shows the link from the unvisited nodes to the current node.
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]
Iteration #4
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]
Iteration #5
Step #1 - Pick an unvisited node
We're currently left with one node in the unvisited array β 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.
Dijkstra's Algorithm Pseudocode Example
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] β INFINITY
5 prev[v] β UNDEFINED
6 add v to Q
7 dist[source] β 0
8
9 while Q is not empty:
10 u β 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 β dist[u] + Graph.Edges(u, v)
15 if alt < dist[v]:
16 dist[v] β alt
17 prev[v] β u
18
19 return dist[], prev[]Applications of Dijkstra's Algorithm
Here are some of the common applications of Dijkstra's algorithm:
- In maps to get the shortest distance between locations. An example is Google Maps.
- In telecommunications to determine transmission rate.
- In robotic design to determine shortest path for automated robots.
Summary
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
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