%global _empty_manifest_terminate_build 0
Name: python-halo-bian
Version: 0.12.54
Release: 1
Summary: this is the Halo Bian library
License: MIT License
URL: https://github.com/halo-framework/halo-bian
Source0: https://mirrors.aliyun.com/pypi/web/packages/8f/2d/122d3ec42f344b069d04d45e7804b797fea084fed71cf0c2efbc85fdc600/halo-bian-0.12.54.tar.gz
BuildArch: noarch
%description
# Halo Bian - Flask BIAN Python Reference Architecture Library
The **Halo Bian** library is based on the [**Halo**](https://github.com/halo-framework/halo-app) library which is a python based library utilizing [**Serverless**](https://logz.io/blog/serverless-vs-containers/) technology and [**microservices architecture**](http://blog.binaris.com/your-guide-to-migrating-existing-microservices-to-serverless/)
BIAN (Banking Industry Architecture Network) is a membership group committed to developing open standards around banking and financial services. A key deliverable of this group is the BIAN Service Landscape model which defines a comprehensive services architecture for financial transactions and facilities. This library is an implementation of the BIAN model leveraging the Flask framework and allows a developer to **rapidly create BIAN-compliant services** while hiding much of the underlying BIAN model details. See www.bian.org for more information on BIAN.
This library leverages not only the Flask framework, but a number of the Flask Cloud Services components as well to facilitate building robust and resilient cloud-native BIAN microservices.
deploy your Service Domain to your local environment or use [**Serverless Framework**](https://serverless.com/) and [**zappa**](https://github.com/Miserlou/Zappa) to deploy your Service Domain to AWS.
## BIAN Basics
Before diving into the library architecture, it helps to understand two key concepts within BIAN, service domains and control records.
### Service Domain
The BIAN Service Landscape defines discrete areas of responsibility known as service domains. A **Service Domain** is a combination of a **Functional Pattern** and an **Asset Type**. For instance, using the functional pattern 'Registry' with the asset type 'Product' would yield a 'Product Registry' service domain, which could be used to manage a product catalog. If we instead changed the asset type to 'Device', we would have a 'Device Registry' service domain that could be used to authorize services on a mobile device.
### Control Record
The **Control Record** is used to track the state of a service domain, and like the service domain is derived from the functional pattern and asset type. However, in a control record, the functional pattern is represented by the **Generic Artifact Type**. There is a one-to-one correlation between functional patterns and generic artifact types. The control record goes one step further in delineating between specific service domain operations by introducing an additional parameter called the **Behavior Qualifier**, which, like generic artifact types, have a one-to-one correlation with functional patterns.
### In Addition
- The commercial behaviors that are called Functional Patterns. Functional Patterns, Generic Artifacts and Behavior Qualifier Types are mapped and correlated:
[**Image From Bian Manual**](https://bian.org)
- A Service Domain applies one of the 18 functional patterns to instances of one type of asset:
[**Image From Bian Manual**](https://bian.org)
- The standard set of ‘action terms’ that characterize the range of service operation calls :
[**Image From Bian Manual**](https://bian.org)
- The Default Action Term By Functional Pattern matrix:
[**Image From Bian Manual**](https://bian.org)
### BIAN Summary
So to summarize the above:
**Functional Pattern** ==> **Generic Artifact Type** ==> **Behavior Qualifier**
**Functional Pattern** + **Asset Type** = **Service Domain**
**Generic Artifact Type** + **Asset Type** + (optional)**Behavior Qualifier** = **Control Record**
**Functional Pattern** is correlated with a set of **Action Term** = **Service Domain Operations**
Key Benefits of using BIAN API solutions:
- Support for Emerging Industry Approaches – Two key technology approaches are considered: API development and the adoption of a Micro-service architecture
- Support for Industry Standards – The BIAN Service Domains and service operations present an Industry standard definition for the componentization and service enablement of Banking
- Support for Incremental Adoption/Migration – BIAN aligned solutions can be implemented and adopted incrementally enabling a prioritized migration from constraining legacy architectures
## Architecture
The Flask BIAN library implements a BIAN service domain wrapper that acts as an API and data translator while hiding much of the BIAN model complexity from the developer.
Halo Bian provides the following features:
- Bian version 7 - API release competability
- OAS ver. 2 support
- BianRequest object provides bian parameters support
- ServiceProperties object provides service status
- AssetType, GenericArtifact, BehaviorQualifier support per service domain
- BianServiceInfo object privides Bian details per service
- Support for all Bian Service Operations
- Support for all FunctionalPatterns
Halo provides the following features:
- Flask development for AWS Lambda & Dynamodb
- [correlation id across microservices](https://theburningmonk.com/2017/09/capture-and-forward-correlation-ids-through-different-lambda-event-sources/)
- [structured json based logging](https://theburningmonk.com/2018/01/you-need-to-use-structured-logging-with-aws-lambda/)
- [sample debug log in production](https://theburningmonk.com/2018/04/you-need-to-sample-debug-logs-in-production/)
- [support for microservice transactions with the saga pattern](https://read.acloud.guru/how-the-saga-pattern-manages-failures-with-aws-lambda-and-step-functions-bc8f7129f900)
- [using SSM Parameter Store over Lambda env variables](https://hackernoon.com/you-should-use-ssm-parameter-store-over-lambda-env-variables-5197fc6ea45b)
- [Serverless Error Handling & trace id for end users](https://aws.amazon.com/blogs/compute/error-handling-patterns-in-amazon-api-gateway-and-aws-lambda/)
- [Lambda timeout](https://blog.epsagon.com/best-practices-for-aws-lambda-timeouts) management for [slow HTTP responses](https://theburningmonk.com/2018/01/aws-lambda-use-the-invocation-context-to-better-handle-slow-http-responses/)
- [ootb support for Idempotent service invocations (md5)](https://cloudonaut.io/your-lambda-function-might-execute-twice-deal-with-it/)
If you are building a Python web app running on AWS Lambda (Flask), use this library to manage api transactions:
```
sagax = load_saga("test", jsonx, schema)
payloads = {"BookHotel": {"abc": "def"}, "BookFlight": {"abc": "def"}, "BookRental": {"abc": "def"},
"CancelHotel": {"abc": "def"}, "CancelFlight": {"abc": "def"}, "CancelRental": {"abc": "def"}}
apis = {"BookHotel": self.create_api1, "BookFlight": self.create_api2, "BookRental": self.create_api3,
"CancelHotel": self.create_api4, "CancelFlight": self.create_api5, "CancelRental": self.create_api6}
try:
self.context = Util.get_lambda_context(request)
ret = sagax.execute(self.req_context, payloads, apis)
return {"saga": "good"}, 200
except SagaRollBack as e:
return {"saga": "bad"}, 500
```
## License
This project is licensed under the MIT License
## Acknowledgments
* Pivotal-Field-Engineering - https://github.com/Pivotal-Field-Engineering/spring-bian
* Bian api - https://github.com/bianapis
* Bian - http://bian.org
%package -n python3-halo-bian
Summary: this is the Halo Bian library
Provides: python-halo-bian
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-halo-bian
# Halo Bian - Flask BIAN Python Reference Architecture Library
The **Halo Bian** library is based on the [**Halo**](https://github.com/halo-framework/halo-app) library which is a python based library utilizing [**Serverless**](https://logz.io/blog/serverless-vs-containers/) technology and [**microservices architecture**](http://blog.binaris.com/your-guide-to-migrating-existing-microservices-to-serverless/)
BIAN (Banking Industry Architecture Network) is a membership group committed to developing open standards around banking and financial services. A key deliverable of this group is the BIAN Service Landscape model which defines a comprehensive services architecture for financial transactions and facilities. This library is an implementation of the BIAN model leveraging the Flask framework and allows a developer to **rapidly create BIAN-compliant services** while hiding much of the underlying BIAN model details. See www.bian.org for more information on BIAN.
This library leverages not only the Flask framework, but a number of the Flask Cloud Services components as well to facilitate building robust and resilient cloud-native BIAN microservices.
deploy your Service Domain to your local environment or use [**Serverless Framework**](https://serverless.com/) and [**zappa**](https://github.com/Miserlou/Zappa) to deploy your Service Domain to AWS.
## BIAN Basics
Before diving into the library architecture, it helps to understand two key concepts within BIAN, service domains and control records.
### Service Domain
The BIAN Service Landscape defines discrete areas of responsibility known as service domains. A **Service Domain** is a combination of a **Functional Pattern** and an **Asset Type**. For instance, using the functional pattern 'Registry' with the asset type 'Product' would yield a 'Product Registry' service domain, which could be used to manage a product catalog. If we instead changed the asset type to 'Device', we would have a 'Device Registry' service domain that could be used to authorize services on a mobile device.
### Control Record
The **Control Record** is used to track the state of a service domain, and like the service domain is derived from the functional pattern and asset type. However, in a control record, the functional pattern is represented by the **Generic Artifact Type**. There is a one-to-one correlation between functional patterns and generic artifact types. The control record goes one step further in delineating between specific service domain operations by introducing an additional parameter called the **Behavior Qualifier**, which, like generic artifact types, have a one-to-one correlation with functional patterns.
### In Addition
- The commercial behaviors that are called Functional Patterns. Functional Patterns, Generic Artifacts and Behavior Qualifier Types are mapped and correlated:
[**Image From Bian Manual**](https://bian.org)
- A Service Domain applies one of the 18 functional patterns to instances of one type of asset:
[**Image From Bian Manual**](https://bian.org)
- The standard set of ‘action terms’ that characterize the range of service operation calls :
[**Image From Bian Manual**](https://bian.org)
- The Default Action Term By Functional Pattern matrix:
[**Image From Bian Manual**](https://bian.org)
### BIAN Summary
So to summarize the above:
**Functional Pattern** ==> **Generic Artifact Type** ==> **Behavior Qualifier**
**Functional Pattern** + **Asset Type** = **Service Domain**
**Generic Artifact Type** + **Asset Type** + (optional)**Behavior Qualifier** = **Control Record**
**Functional Pattern** is correlated with a set of **Action Term** = **Service Domain Operations**
Key Benefits of using BIAN API solutions:
- Support for Emerging Industry Approaches – Two key technology approaches are considered: API development and the adoption of a Micro-service architecture
- Support for Industry Standards – The BIAN Service Domains and service operations present an Industry standard definition for the componentization and service enablement of Banking
- Support for Incremental Adoption/Migration – BIAN aligned solutions can be implemented and adopted incrementally enabling a prioritized migration from constraining legacy architectures
## Architecture
The Flask BIAN library implements a BIAN service domain wrapper that acts as an API and data translator while hiding much of the BIAN model complexity from the developer.
Halo Bian provides the following features:
- Bian version 7 - API release competability
- OAS ver. 2 support
- BianRequest object provides bian parameters support
- ServiceProperties object provides service status
- AssetType, GenericArtifact, BehaviorQualifier support per service domain
- BianServiceInfo object privides Bian details per service
- Support for all Bian Service Operations
- Support for all FunctionalPatterns
Halo provides the following features:
- Flask development for AWS Lambda & Dynamodb
- [correlation id across microservices](https://theburningmonk.com/2017/09/capture-and-forward-correlation-ids-through-different-lambda-event-sources/)
- [structured json based logging](https://theburningmonk.com/2018/01/you-need-to-use-structured-logging-with-aws-lambda/)
- [sample debug log in production](https://theburningmonk.com/2018/04/you-need-to-sample-debug-logs-in-production/)
- [support for microservice transactions with the saga pattern](https://read.acloud.guru/how-the-saga-pattern-manages-failures-with-aws-lambda-and-step-functions-bc8f7129f900)
- [using SSM Parameter Store over Lambda env variables](https://hackernoon.com/you-should-use-ssm-parameter-store-over-lambda-env-variables-5197fc6ea45b)
- [Serverless Error Handling & trace id for end users](https://aws.amazon.com/blogs/compute/error-handling-patterns-in-amazon-api-gateway-and-aws-lambda/)
- [Lambda timeout](https://blog.epsagon.com/best-practices-for-aws-lambda-timeouts) management for [slow HTTP responses](https://theburningmonk.com/2018/01/aws-lambda-use-the-invocation-context-to-better-handle-slow-http-responses/)
- [ootb support for Idempotent service invocations (md5)](https://cloudonaut.io/your-lambda-function-might-execute-twice-deal-with-it/)
If you are building a Python web app running on AWS Lambda (Flask), use this library to manage api transactions:
```
sagax = load_saga("test", jsonx, schema)
payloads = {"BookHotel": {"abc": "def"}, "BookFlight": {"abc": "def"}, "BookRental": {"abc": "def"},
"CancelHotel": {"abc": "def"}, "CancelFlight": {"abc": "def"}, "CancelRental": {"abc": "def"}}
apis = {"BookHotel": self.create_api1, "BookFlight": self.create_api2, "BookRental": self.create_api3,
"CancelHotel": self.create_api4, "CancelFlight": self.create_api5, "CancelRental": self.create_api6}
try:
self.context = Util.get_lambda_context(request)
ret = sagax.execute(self.req_context, payloads, apis)
return {"saga": "good"}, 200
except SagaRollBack as e:
return {"saga": "bad"}, 500
```
## License
This project is licensed under the MIT License
## Acknowledgments
* Pivotal-Field-Engineering - https://github.com/Pivotal-Field-Engineering/spring-bian
* Bian api - https://github.com/bianapis
* Bian - http://bian.org
%package help
Summary: Development documents and examples for halo-bian
Provides: python3-halo-bian-doc
%description help
# Halo Bian - Flask BIAN Python Reference Architecture Library
The **Halo Bian** library is based on the [**Halo**](https://github.com/halo-framework/halo-app) library which is a python based library utilizing [**Serverless**](https://logz.io/blog/serverless-vs-containers/) technology and [**microservices architecture**](http://blog.binaris.com/your-guide-to-migrating-existing-microservices-to-serverless/)
BIAN (Banking Industry Architecture Network) is a membership group committed to developing open standards around banking and financial services. A key deliverable of this group is the BIAN Service Landscape model which defines a comprehensive services architecture for financial transactions and facilities. This library is an implementation of the BIAN model leveraging the Flask framework and allows a developer to **rapidly create BIAN-compliant services** while hiding much of the underlying BIAN model details. See www.bian.org for more information on BIAN.
This library leverages not only the Flask framework, but a number of the Flask Cloud Services components as well to facilitate building robust and resilient cloud-native BIAN microservices.
deploy your Service Domain to your local environment or use [**Serverless Framework**](https://serverless.com/) and [**zappa**](https://github.com/Miserlou/Zappa) to deploy your Service Domain to AWS.
## BIAN Basics
Before diving into the library architecture, it helps to understand two key concepts within BIAN, service domains and control records.
### Service Domain
The BIAN Service Landscape defines discrete areas of responsibility known as service domains. A **Service Domain** is a combination of a **Functional Pattern** and an **Asset Type**. For instance, using the functional pattern 'Registry' with the asset type 'Product' would yield a 'Product Registry' service domain, which could be used to manage a product catalog. If we instead changed the asset type to 'Device', we would have a 'Device Registry' service domain that could be used to authorize services on a mobile device.
### Control Record
The **Control Record** is used to track the state of a service domain, and like the service domain is derived from the functional pattern and asset type. However, in a control record, the functional pattern is represented by the **Generic Artifact Type**. There is a one-to-one correlation between functional patterns and generic artifact types. The control record goes one step further in delineating between specific service domain operations by introducing an additional parameter called the **Behavior Qualifier**, which, like generic artifact types, have a one-to-one correlation with functional patterns.
### In Addition
- The commercial behaviors that are called Functional Patterns. Functional Patterns, Generic Artifacts and Behavior Qualifier Types are mapped and correlated:
[**Image From Bian Manual**](https://bian.org)
- A Service Domain applies one of the 18 functional patterns to instances of one type of asset:
[**Image From Bian Manual**](https://bian.org)
- The standard set of ‘action terms’ that characterize the range of service operation calls :
[**Image From Bian Manual**](https://bian.org)
- The Default Action Term By Functional Pattern matrix:
[**Image From Bian Manual**](https://bian.org)
### BIAN Summary
So to summarize the above:
**Functional Pattern** ==> **Generic Artifact Type** ==> **Behavior Qualifier**
**Functional Pattern** + **Asset Type** = **Service Domain**
**Generic Artifact Type** + **Asset Type** + (optional)**Behavior Qualifier** = **Control Record**
**Functional Pattern** is correlated with a set of **Action Term** = **Service Domain Operations**
Key Benefits of using BIAN API solutions:
- Support for Emerging Industry Approaches – Two key technology approaches are considered: API development and the adoption of a Micro-service architecture
- Support for Industry Standards – The BIAN Service Domains and service operations present an Industry standard definition for the componentization and service enablement of Banking
- Support for Incremental Adoption/Migration – BIAN aligned solutions can be implemented and adopted incrementally enabling a prioritized migration from constraining legacy architectures
## Architecture
The Flask BIAN library implements a BIAN service domain wrapper that acts as an API and data translator while hiding much of the BIAN model complexity from the developer.
Halo Bian provides the following features:
- Bian version 7 - API release competability
- OAS ver. 2 support
- BianRequest object provides bian parameters support
- ServiceProperties object provides service status
- AssetType, GenericArtifact, BehaviorQualifier support per service domain
- BianServiceInfo object privides Bian details per service
- Support for all Bian Service Operations
- Support for all FunctionalPatterns
Halo provides the following features:
- Flask development for AWS Lambda & Dynamodb
- [correlation id across microservices](https://theburningmonk.com/2017/09/capture-and-forward-correlation-ids-through-different-lambda-event-sources/)
- [structured json based logging](https://theburningmonk.com/2018/01/you-need-to-use-structured-logging-with-aws-lambda/)
- [sample debug log in production](https://theburningmonk.com/2018/04/you-need-to-sample-debug-logs-in-production/)
- [support for microservice transactions with the saga pattern](https://read.acloud.guru/how-the-saga-pattern-manages-failures-with-aws-lambda-and-step-functions-bc8f7129f900)
- [using SSM Parameter Store over Lambda env variables](https://hackernoon.com/you-should-use-ssm-parameter-store-over-lambda-env-variables-5197fc6ea45b)
- [Serverless Error Handling & trace id for end users](https://aws.amazon.com/blogs/compute/error-handling-patterns-in-amazon-api-gateway-and-aws-lambda/)
- [Lambda timeout](https://blog.epsagon.com/best-practices-for-aws-lambda-timeouts) management for [slow HTTP responses](https://theburningmonk.com/2018/01/aws-lambda-use-the-invocation-context-to-better-handle-slow-http-responses/)
- [ootb support for Idempotent service invocations (md5)](https://cloudonaut.io/your-lambda-function-might-execute-twice-deal-with-it/)
If you are building a Python web app running on AWS Lambda (Flask), use this library to manage api transactions:
```
sagax = load_saga("test", jsonx, schema)
payloads = {"BookHotel": {"abc": "def"}, "BookFlight": {"abc": "def"}, "BookRental": {"abc": "def"},
"CancelHotel": {"abc": "def"}, "CancelFlight": {"abc": "def"}, "CancelRental": {"abc": "def"}}
apis = {"BookHotel": self.create_api1, "BookFlight": self.create_api2, "BookRental": self.create_api3,
"CancelHotel": self.create_api4, "CancelFlight": self.create_api5, "CancelRental": self.create_api6}
try:
self.context = Util.get_lambda_context(request)
ret = sagax.execute(self.req_context, payloads, apis)
return {"saga": "good"}, 200
except SagaRollBack as e:
return {"saga": "bad"}, 500
```
## License
This project is licensed under the MIT License
## Acknowledgments
* Pivotal-Field-Engineering - https://github.com/Pivotal-Field-Engineering/spring-bian
* Bian api - https://github.com/bianapis
* Bian - http://bian.org
%prep
%autosetup -n halo-bian-0.12.54
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-halo-bian -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Tue Jun 20 2023 Python_Bot - 0.12.54-1
- Package Spec generated