1648079400
This is a general purpose OpenAPI code generator. It is currently used to completely generate the HTTP code in the Java SDK, and generate some of the HTTP code in our Golang SDK.
We currently have two HTTP endpoints. One for algod and one for indexer, so in most cases, this tool would be run once with each OpenAPI spec.
~$ mvn package -DskipTests
~$ java -jar target/generator-*-jar-with-dependencies.jar -h
You'll see that there are a number of subcommands:
The command line interface uses JCommander to define the command line interface. See Main.java.
The main code involves an OpenAPI parser / event generator and several listeners for the actual generation.
The template subcommand is using Apache Velocity as the underlying template engine. Things like variables, loops, and statements are all supported. So business logic can technically be implemented in the template if it's actually necessary.
There are three phases: client, query, and model. Each phase must provide two templates, one for the file generation and one to specify the filename to be used. If all results should go to the same file. For query and model generation the template will be executed once for each query / model. If you want to put everything in one file return the same filename twice in a row and the processing will exit early.
phase | filename | purpose |
---|---|---|
client | client.vm | Client class with functions to call each query. |
client | client_filename.vm | File to write to the client output directory. |
query | query.vm | Template to use for generating query files. |
query | query_filename.vm | File to write to the query output directory. |
model | model.vm | Template to use for generating model files. |
model | model_filename.vm | File to write to the model output directory. |
The template command will only run the templates which have an output directory is provided. So if you just want to regenerate models, only use the -m option.
-c, --clientOutputDir
Directory to write client file(s).
-m, --modelsOutputDir
Directory to write model file(s).
-q, --queryOutputDir
Directory to write query file(s).
The template subcommand accepts a --propertyFiles option. It can be provided multiple times, or as a comma separated list of files. Property files will be processed and bound to a velocity variable available to templates.
For details on a type you can put it directly into your template. It will be serialized along with its fields for your reference. Here is a high level description of what is available:
template | variable | type | purpose |
---|---|---|---|
all | str | StringHelpers.java | Some string utilities are available. See StringHelpers.java for details. There are simple things like $str.capitalize("someData") -> SomeData , and also some more complex helpers like $str.formatDoc($query.doc, "// ") which will split the document at the word boundary nearest to 80 characters without going over, and add a prefix to each new line. |
all | order | OrderHelpers.java | Some ordering utilities available. See OrderHelpers.java for details. An example utility function is $order.propertiesWithOrdering($props, $preferred_order) , where $props is a list of properties and $preferred_order is a string list to use when ordering the properties list. |
all | propFile | Properties | The contents of all property files are available with this variable. For example if package=com.algorand.v2.algod is in the property file, the template may use ${propFile.package} . |
all | models | HashMap<StructDef, List<TypeDef>> | A list of all models. |
all | queries | List<QueryDef> | A list of all queries. |
query | q | QueryDef | The current query definition. |
model | def | StructDef | The current model definition if multiple files are being generated. |
model | props | List<TypeDef> | A list of properties for the current model. |
In the following example, we are careful to generate the algod code first because the algod models are a strict subset of the indexer models. For that reason, we are able to reuse some overlapping models from indexer in algod.
~$ java -jar generator*jar template
-s algod.oas2.json
-t go_templates
-c algodClient
-m allModels
-q algodQueries
-p common_config.properties,algod_config.properties
~$ java -jar generator*jar template
-s indexer.oas2.json
-t go_templates
-c indexerClient
-m allModels
-q indexerQueries
-p common_config.properties,indexer_config.properties
There is a test template that gives you some basic usage in the test_templates directory.
You can generate the test code in the output directory with the following commands:
~$ mkdir output
~$ java -jar target/generator-*-jar-with-dependencies.jar \
template \
-s /path/to/a/spec/file/indexer.oas2.json \
-t test_templates/ \
-m output \
-q output \
-c output \
-p test_templates/my.properties
The Golang templates are in the go_templates directory.
The Golang HTTP API is only partially generated. The hand written parts were not totally consistent with the spec and that makes it difficult to regenerate them. Regardless, an attempt has been made. In the templates there are some macros which map "generated" values to the hand written ones. For example the query types have this mapping:
#macro ( queryType )
#if ( ${str.capitalize($q.name)} == "SearchForAccounts" )
SearchAccounts## The hand written client doesn't quite match the spec...
#elseif ( ${str.capitalize($q.name)} == "GetStatus" )
Status##
#elseif ( ${str.capitalize($q.name)} == "GetPendingTransactionsByAddress" )
PendingTransactionInformationByAddress##
#elseif ( ${str.capitalize($q.name)} == "GetPendingTransactions" )
PendingTransactions##
#else
${str.capitalize($q.name)}##
#end
#end
Other mappings are more specific to the language, such as the OpenAPI type to SDK type:
#macro ( toQueryType $param )##
#if ( $param.algorandFormat == "RFC3339 String" )
string##
#elseif ( $param.type == "integer" )
uint64##
#elseif ( $param.type == "string" )
string##
#elseif ( $param.type == "boolean" )
bool##
#elseif( $param.type == "binary" )
string##
#else
UNHANDLED TYPE
- ref: $!param.refType
- type: $!param.type
- array type: $!param.arrayType
- algorand format: $!param.algorandFormat
- format: $!param.format
##$unknown.type ## force a template failure because $unknown.type does not exist.
#end
#end
Because of this, we are phasing in code generation gradually by skipping some types. The skipped types are specified in the property files:
common_config.properties
model_skip=AccountParticipation,AssetParams,RawBlockJson,etc,...
algod_config.properties
query_skip=Block,BlockRaw,SendRawTransaction,SuggestedParams,etc,...
indexer_config.properties
query_skip=LookupAssetByID,LookupAccountTransactions,SearchForAssets,LookupAssetBalances,LookupAssetTransactions,LookupBlock,LookupTransactions,SearchForTransactions
The Java templates are in the java_templates directory.
These are not used yet, they are the initial experiments for the template engine. Since the Java SDK has used code generation from the beginning, we should be able to fully migrate to the template engine eventually.
In general, the automation pipeline will build and run whatever Dockerfile
is found in a repository's templates
directory. For instructions on how to configure the templates
directory, look at the repository template directory example.
If you are trying to verify that automatic code generation works as intended, we recommend creating a testing branch from that repository and using the SKIP_PR=true
environment variable to avoid creating pull requests. If all goes according to plan, generated files should be available in the container's /repo
directory.
The automatic generator scripts depend on certain prerequisites that are listed in automation/REQUIREMENTS.md. Once those conditions have been satisfied, automatically generating code for external repositories should be as easy as building and running a particular SDK's templates/Dockerfile
file.
Download Details:
Author: algorand
Source Code: https://github.com/algorand/generator
License:
#algorand #blockchain #cryptocurrency #java #golang #openapi
1648079400
This is a general purpose OpenAPI code generator. It is currently used to completely generate the HTTP code in the Java SDK, and generate some of the HTTP code in our Golang SDK.
We currently have two HTTP endpoints. One for algod and one for indexer, so in most cases, this tool would be run once with each OpenAPI spec.
~$ mvn package -DskipTests
~$ java -jar target/generator-*-jar-with-dependencies.jar -h
You'll see that there are a number of subcommands:
The command line interface uses JCommander to define the command line interface. See Main.java.
The main code involves an OpenAPI parser / event generator and several listeners for the actual generation.
The template subcommand is using Apache Velocity as the underlying template engine. Things like variables, loops, and statements are all supported. So business logic can technically be implemented in the template if it's actually necessary.
There are three phases: client, query, and model. Each phase must provide two templates, one for the file generation and one to specify the filename to be used. If all results should go to the same file. For query and model generation the template will be executed once for each query / model. If you want to put everything in one file return the same filename twice in a row and the processing will exit early.
phase | filename | purpose |
---|---|---|
client | client.vm | Client class with functions to call each query. |
client | client_filename.vm | File to write to the client output directory. |
query | query.vm | Template to use for generating query files. |
query | query_filename.vm | File to write to the query output directory. |
model | model.vm | Template to use for generating model files. |
model | model_filename.vm | File to write to the model output directory. |
The template command will only run the templates which have an output directory is provided. So if you just want to regenerate models, only use the -m option.
-c, --clientOutputDir
Directory to write client file(s).
-m, --modelsOutputDir
Directory to write model file(s).
-q, --queryOutputDir
Directory to write query file(s).
The template subcommand accepts a --propertyFiles option. It can be provided multiple times, or as a comma separated list of files. Property files will be processed and bound to a velocity variable available to templates.
For details on a type you can put it directly into your template. It will be serialized along with its fields for your reference. Here is a high level description of what is available:
template | variable | type | purpose |
---|---|---|---|
all | str | StringHelpers.java | Some string utilities are available. See StringHelpers.java for details. There are simple things like $str.capitalize("someData") -> SomeData , and also some more complex helpers like $str.formatDoc($query.doc, "// ") which will split the document at the word boundary nearest to 80 characters without going over, and add a prefix to each new line. |
all | order | OrderHelpers.java | Some ordering utilities available. See OrderHelpers.java for details. An example utility function is $order.propertiesWithOrdering($props, $preferred_order) , where $props is a list of properties and $preferred_order is a string list to use when ordering the properties list. |
all | propFile | Properties | The contents of all property files are available with this variable. For example if package=com.algorand.v2.algod is in the property file, the template may use ${propFile.package} . |
all | models | HashMap<StructDef, List<TypeDef>> | A list of all models. |
all | queries | List<QueryDef> | A list of all queries. |
query | q | QueryDef | The current query definition. |
model | def | StructDef | The current model definition if multiple files are being generated. |
model | props | List<TypeDef> | A list of properties for the current model. |
In the following example, we are careful to generate the algod code first because the algod models are a strict subset of the indexer models. For that reason, we are able to reuse some overlapping models from indexer in algod.
~$ java -jar generator*jar template
-s algod.oas2.json
-t go_templates
-c algodClient
-m allModels
-q algodQueries
-p common_config.properties,algod_config.properties
~$ java -jar generator*jar template
-s indexer.oas2.json
-t go_templates
-c indexerClient
-m allModels
-q indexerQueries
-p common_config.properties,indexer_config.properties
There is a test template that gives you some basic usage in the test_templates directory.
You can generate the test code in the output directory with the following commands:
~$ mkdir output
~$ java -jar target/generator-*-jar-with-dependencies.jar \
template \
-s /path/to/a/spec/file/indexer.oas2.json \
-t test_templates/ \
-m output \
-q output \
-c output \
-p test_templates/my.properties
The Golang templates are in the go_templates directory.
The Golang HTTP API is only partially generated. The hand written parts were not totally consistent with the spec and that makes it difficult to regenerate them. Regardless, an attempt has been made. In the templates there are some macros which map "generated" values to the hand written ones. For example the query types have this mapping:
#macro ( queryType )
#if ( ${str.capitalize($q.name)} == "SearchForAccounts" )
SearchAccounts## The hand written client doesn't quite match the spec...
#elseif ( ${str.capitalize($q.name)} == "GetStatus" )
Status##
#elseif ( ${str.capitalize($q.name)} == "GetPendingTransactionsByAddress" )
PendingTransactionInformationByAddress##
#elseif ( ${str.capitalize($q.name)} == "GetPendingTransactions" )
PendingTransactions##
#else
${str.capitalize($q.name)}##
#end
#end
Other mappings are more specific to the language, such as the OpenAPI type to SDK type:
#macro ( toQueryType $param )##
#if ( $param.algorandFormat == "RFC3339 String" )
string##
#elseif ( $param.type == "integer" )
uint64##
#elseif ( $param.type == "string" )
string##
#elseif ( $param.type == "boolean" )
bool##
#elseif( $param.type == "binary" )
string##
#else
UNHANDLED TYPE
- ref: $!param.refType
- type: $!param.type
- array type: $!param.arrayType
- algorand format: $!param.algorandFormat
- format: $!param.format
##$unknown.type ## force a template failure because $unknown.type does not exist.
#end
#end
Because of this, we are phasing in code generation gradually by skipping some types. The skipped types are specified in the property files:
common_config.properties
model_skip=AccountParticipation,AssetParams,RawBlockJson,etc,...
algod_config.properties
query_skip=Block,BlockRaw,SendRawTransaction,SuggestedParams,etc,...
indexer_config.properties
query_skip=LookupAssetByID,LookupAccountTransactions,SearchForAssets,LookupAssetBalances,LookupAssetTransactions,LookupBlock,LookupTransactions,SearchForTransactions
The Java templates are in the java_templates directory.
These are not used yet, they are the initial experiments for the template engine. Since the Java SDK has used code generation from the beginning, we should be able to fully migrate to the template engine eventually.
In general, the automation pipeline will build and run whatever Dockerfile
is found in a repository's templates
directory. For instructions on how to configure the templates
directory, look at the repository template directory example.
If you are trying to verify that automatic code generation works as intended, we recommend creating a testing branch from that repository and using the SKIP_PR=true
environment variable to avoid creating pull requests. If all goes according to plan, generated files should be available in the container's /repo
directory.
The automatic generator scripts depend on certain prerequisites that are listed in automation/REQUIREMENTS.md. Once those conditions have been satisfied, automatically generating code for external repositories should be as easy as building and running a particular SDK's templates/Dockerfile
file.
Download Details:
Author: algorand
Source Code: https://github.com/algorand/generator
License:
#algorand #blockchain #cryptocurrency #java #golang #openapi
1604008800
Static code analysis refers to the technique of approximating the runtime behavior of a program. In other words, it is the process of predicting the output of a program without actually executing it.
Lately, however, the term “Static Code Analysis” is more commonly used to refer to one of the applications of this technique rather than the technique itself — program comprehension — understanding the program and detecting issues in it (anything from syntax errors to type mismatches, performance hogs likely bugs, security loopholes, etc.). This is the usage we’d be referring to throughout this post.
“The refinement of techniques for the prompt discovery of error serves as well as any other as a hallmark of what we mean by science.”
We cover a lot of ground in this post. The aim is to build an understanding of static code analysis and to equip you with the basic theory, and the right tools so that you can write analyzers on your own.
We start our journey with laying down the essential parts of the pipeline which a compiler follows to understand what a piece of code does. We learn where to tap points in this pipeline to plug in our analyzers and extract meaningful information. In the latter half, we get our feet wet, and write four such static analyzers, completely from scratch, in Python.
Note that although the ideas here are discussed in light of Python, static code analyzers across all programming languages are carved out along similar lines. We chose Python because of the availability of an easy to use ast
module, and wide adoption of the language itself.
Before a computer can finally “understand” and execute a piece of code, it goes through a series of complicated transformations:
As you can see in the diagram (go ahead, zoom it!), the static analyzers feed on the output of these stages. To be able to better understand the static analysis techniques, let’s look at each of these steps in some more detail:
The first thing that a compiler does when trying to understand a piece of code is to break it down into smaller chunks, also known as tokens. Tokens are akin to what words are in a language.
A token might consist of either a single character, like (
, or literals (like integers, strings, e.g., 7
, Bob
, etc.), or reserved keywords of that language (e.g, def
in Python). Characters which do not contribute towards the semantics of a program, like trailing whitespace, comments, etc. are often discarded by the scanner.
Python provides the tokenize
module in its standard library to let you play around with tokens:
Python
1
import io
2
import tokenize
3
4
code = b"color = input('Enter your favourite color: ')"
5
6
for token in tokenize.tokenize(io.BytesIO(code).readline):
7
print(token)
Python
1
TokenInfo(type=62 (ENCODING), string='utf-8')
2
TokenInfo(type=1 (NAME), string='color')
3
TokenInfo(type=54 (OP), string='=')
4
TokenInfo(type=1 (NAME), string='input')
5
TokenInfo(type=54 (OP), string='(')
6
TokenInfo(type=3 (STRING), string="'Enter your favourite color: '")
7
TokenInfo(type=54 (OP), string=')')
8
TokenInfo(type=4 (NEWLINE), string='')
9
TokenInfo(type=0 (ENDMARKER), string='')
(Note that for the sake of readability, I’ve omitted a few columns from the result above — metadata like starting index, ending index, a copy of the line on which a token occurs, etc.)
#code quality #code review #static analysis #static code analysis #code analysis #static analysis tools #code review tips #static code analyzer #static code analysis tool #static analyzer
1621137960
Having another pair of eyes scan your code is always useful and helps you spot mistakes before you break production. You need not be an expert to review someone’s code. Some experience with the programming language and a review checklist should help you get started. We’ve put together a list of things you should keep in mind when you’re reviewing Java code. Read on!
NullPointerException
…
#java #code quality #java tutorial #code analysis #code reviews #code review tips #code analysis tools #java tutorial for beginners #java code review
1604088000
There are more code smells. Let’s keep changing the aromas. We see several symptoms and situations that make us doubt the quality of our development. Let’s look at some possible solutions.
Most of these smells are just hints of something that might be wrong. They are not rigid rules.
This is part II. Part I can be found here.
The code is difficult to read, there are tricky with names without semantics. Sometimes using language’s accidental complexity.
_Image Source: NeONBRAND on _Unsplash
Problems
Solutions
Examples
Exceptions
Sample Code
Wrong
function primeFactors(n){
var f = [], i = 0, d = 2;
for (i = 0; n >= 2; ) {
if(n % d == 0){
f[i++]=(d);
n /= d;
}
else{
d++;
}
}
return f;
}
Right
function primeFactors(numberToFactor){
var factors = [],
divisor = 2,
remainder = numberToFactor;
while(remainder>=2){
if(remainder % divisor === 0){
factors.push(divisor);
remainder = remainder/ divisor;
}
else{
divisor++;
}
}
return factors;
}
Detection
Automatic detection is possible in some languages. Watch some warnings related to complexity, bad names, post increment variables, etc.
#pixel-face #code-smells #clean-code #stinky-code-parts #refactor-legacy-code #refactoring #stinky-code #common-code-smells
1597817005
Bar Code Generate in Laravel 7, 6. In this post, i will show you simple and easy steps to generate bar/qr code in laravel.
Use the below given steps and generate bAR/QR codes in laravel Projects:
https://www.tutsmake.com/laravel-6-simple-generate-or-create-qr-codes-example/
#laravel 7 bar code generator #barcode generator laravel 7 #barcode generator laravel 6 #laravel 7 qr code generator #laravel simple/barcode example