%global _empty_manifest_terminate_build 0
Name: python-madam-mam
Version: 0.7.0
Release: 1
Summary: MADAM (TM) Multi Agent Digital Asset Manager - a MAM server for Docker Swarm to handle higly distributed media processes
License: GPL-3.0-only
URL: https://pypi.org/project/madam-mam/
Source0: https://mirrors.aliyun.com/pypi/web/packages/6f/0b/96784c07c5c45fc66be3cac2b88a483668095c1d6d3f1732a53643642045/madam-mam-0.7.0.tar.gz
BuildArch: noarch
Requires: python3-psycopg2-binary
Requires: python3-PyYAML
Requires: python3-docker
Requires: python3-timecode
Requires: python3-sql
Requires: python3-rich
Requires: python3-ariadne
Requires: python3-uvicorn
Requires: python3-yoyo-migrations
Requires: python3-lxml
Requires: python3-watchgod
Requires: python3-Jinja2
Requires: python3-adhesive-zeebe
%description
# MADAM
MADAM is the Multi Agent Digital Asset Manager.
It provides a three-tier architecture platform to handle workflow processing in a distributed environment.
It uses Docker swarm to dispatch processes in a cluster of machines.
It is a free (as freedom) software written in Python.
## Documentation
[Link to the documentation](https://m5231.gitlab.io/documentation/)
## Support
If you find this project useful and want to contribute, please submit issues, merge requests. If you use it regularly,
you can help by the author by a financial support.
## Requirements
You will need [Camunda Modeler 4.11+](https://github.com/camunda/camunda-modeler/releases) to easily create
Zeebe BPMN XML workflows for MADAM.
## Licensing
MADAM is licensed under the [Gnu Public License Version 3](https://www.gnu.org/licenses/gpl-3.0.en.html).
Camunda Modeler is licensed under [the MIT License (MIT)](https://mit-license.org/).
At its core, MADAM use [adhesive-zebe](https://github.com/vtexier/adhesive), a BPMN workflow python engine able to
execute Zeebe BPMN XML workflows. It is a fork of [adhesive](https://github.com/germaniumhq/adhesive) under
the original adhesive license that is [GNU Affero General Public License v3.0](https://www.gnu.org/licenses/agpl-3.0.en.html)
## System environment setup
1. [Install Docker](https://docs.docker.com/engine/install/).
2. [Configure userns-remap](https://docs.docker.com/engine/security/userns-remap/) to map container user `root` to a
host non-root user.
3. Configure the dev station as a [Docker Swarm Manager](https://docs.docker.com/engine/swarm/).
4. Install a [Postgresql](https://www.postgresql.org/download/) database server.
_You can use the Ansible playbook provided to install PostgreSQL locally with Docker,
after configuring `hosts.yaml`:_
make environment
### Python environment setup
* It requires Python 3.8+.
* [Pyenv](https://github.com/pyenv/pyenv) should be used to choose the right version of Python, without breaking the
default Python of the Operating System.
* A Python virtual environment should be created in a `.venv` folder.
```bash
pyenv install 3.8.0
pyenv shell 3.8.0
python -m venv .venv
source .venv/bin/activate`
```
### Installation/Update
From PyPI:
In a Python virtualenv:
pip install -U madam-mam
In your user install directory:
pip install --user -U madam-mam
You should have a the `madam` cli command available:
madam
or
madam --help
will display command usage.
To have bash completion, you can type:
_MADAM_COMPLETE=source_bash madam > madam-complete.sh
sudo cp madam-complete.sh /etc/bash_completion.d/.
For another shell, replace `source_bash` by `source_zsh` or `source_fish`
### Development environment
Install [Poetry](https://python-poetry.org/) with the custom installer:
curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python
Install Python dependencies:
poetry install --no-root
You can use the madam-cli dev command:
./bin/madam-cli
Get `bin/madam-cli` bash shell completion:
_MADAM_CLI_COMPLETE=source_bash bin/madam-cli > madam-cli-complete.sh
sudo cp madam-cli-complete.sh /etc/bash_completion.d/.
For another shell, replace `source_bash` by `source_zsh` or `source_fish`
### Configuration
Make a copy of the environment config example file:
cp .env.example .env
Edit `.env` to suit your needs, then:
export $(grep -v '^#' .env | xargs -d '\n')
Make a copy of the Ansible inventory example file:
cp hosts.yaml.example hosts.yaml
Edit `hosts.yaml` to suit your needs.
Make a copy of the MADAM config example file:
cp madam.yaml.example madam.yaml
Edit `madam.yaml` to suit your needs.
Make a copy of the MADAM config example file for the test environment:
cp madam_tests.yaml.example madam_tests.yaml
Edit `madam_tests.yaml` to suit your needs.
Make a copy of the MADAM config example file for the local deploy:
cp madam_deploy.yaml.example madam_deploy.yaml
Edit `madam_deploy.yaml` to suit your needs.
### Set and tag project version in Git
./bin/release.sh 1.0.0
### Build MADAM python package and Docker image
make build
The wheel package will be build in the `dist` directory.
## Deploy MADAM as local docker container
To deploy MADAM container on localhost:
make deploy
## Check static type and code quality
make check
## Run tests
Run all [pytest](https://docs.pytest.org) tests with:
make tests
Run only some tests by using `bin/tests.sh`:
bin/tests.sh tests/domains/test_workflows.py::test_create
## Database setup
Set `DATABASE_URL` and `DATABASE_URL_TESTS` environment variable in `.env` file:
DATABASE_URL=postgresql://postgres:xxxxx@hostname:5432/madam?sslmode=allow
DATABASE_URL_TESTS=postgresql://postgres:xxxxx@hostname:5432/madam_tests?sslmode=allow
### Migrations scripts
Add/Edit scripts in `resources/migrations` directory:
# version.name.[rollback].sql
00001.init_tables.sql
00001.init_tables.rollback.sql
### Migrate commands
make databases
make databases_rollback
make databases_list
%package -n python3-madam-mam
Summary: MADAM (TM) Multi Agent Digital Asset Manager - a MAM server for Docker Swarm to handle higly distributed media processes
Provides: python-madam-mam
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-madam-mam
# MADAM
MADAM is the Multi Agent Digital Asset Manager.
It provides a three-tier architecture platform to handle workflow processing in a distributed environment.
It uses Docker swarm to dispatch processes in a cluster of machines.
It is a free (as freedom) software written in Python.
## Documentation
[Link to the documentation](https://m5231.gitlab.io/documentation/)
## Support
If you find this project useful and want to contribute, please submit issues, merge requests. If you use it regularly,
you can help by the author by a financial support.
## Requirements
You will need [Camunda Modeler 4.11+](https://github.com/camunda/camunda-modeler/releases) to easily create
Zeebe BPMN XML workflows for MADAM.
## Licensing
MADAM is licensed under the [Gnu Public License Version 3](https://www.gnu.org/licenses/gpl-3.0.en.html).
Camunda Modeler is licensed under [the MIT License (MIT)](https://mit-license.org/).
At its core, MADAM use [adhesive-zebe](https://github.com/vtexier/adhesive), a BPMN workflow python engine able to
execute Zeebe BPMN XML workflows. It is a fork of [adhesive](https://github.com/germaniumhq/adhesive) under
the original adhesive license that is [GNU Affero General Public License v3.0](https://www.gnu.org/licenses/agpl-3.0.en.html)
## System environment setup
1. [Install Docker](https://docs.docker.com/engine/install/).
2. [Configure userns-remap](https://docs.docker.com/engine/security/userns-remap/) to map container user `root` to a
host non-root user.
3. Configure the dev station as a [Docker Swarm Manager](https://docs.docker.com/engine/swarm/).
4. Install a [Postgresql](https://www.postgresql.org/download/) database server.
_You can use the Ansible playbook provided to install PostgreSQL locally with Docker,
after configuring `hosts.yaml`:_
make environment
### Python environment setup
* It requires Python 3.8+.
* [Pyenv](https://github.com/pyenv/pyenv) should be used to choose the right version of Python, without breaking the
default Python of the Operating System.
* A Python virtual environment should be created in a `.venv` folder.
```bash
pyenv install 3.8.0
pyenv shell 3.8.0
python -m venv .venv
source .venv/bin/activate`
```
### Installation/Update
From PyPI:
In a Python virtualenv:
pip install -U madam-mam
In your user install directory:
pip install --user -U madam-mam
You should have a the `madam` cli command available:
madam
or
madam --help
will display command usage.
To have bash completion, you can type:
_MADAM_COMPLETE=source_bash madam > madam-complete.sh
sudo cp madam-complete.sh /etc/bash_completion.d/.
For another shell, replace `source_bash` by `source_zsh` or `source_fish`
### Development environment
Install [Poetry](https://python-poetry.org/) with the custom installer:
curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python
Install Python dependencies:
poetry install --no-root
You can use the madam-cli dev command:
./bin/madam-cli
Get `bin/madam-cli` bash shell completion:
_MADAM_CLI_COMPLETE=source_bash bin/madam-cli > madam-cli-complete.sh
sudo cp madam-cli-complete.sh /etc/bash_completion.d/.
For another shell, replace `source_bash` by `source_zsh` or `source_fish`
### Configuration
Make a copy of the environment config example file:
cp .env.example .env
Edit `.env` to suit your needs, then:
export $(grep -v '^#' .env | xargs -d '\n')
Make a copy of the Ansible inventory example file:
cp hosts.yaml.example hosts.yaml
Edit `hosts.yaml` to suit your needs.
Make a copy of the MADAM config example file:
cp madam.yaml.example madam.yaml
Edit `madam.yaml` to suit your needs.
Make a copy of the MADAM config example file for the test environment:
cp madam_tests.yaml.example madam_tests.yaml
Edit `madam_tests.yaml` to suit your needs.
Make a copy of the MADAM config example file for the local deploy:
cp madam_deploy.yaml.example madam_deploy.yaml
Edit `madam_deploy.yaml` to suit your needs.
### Set and tag project version in Git
./bin/release.sh 1.0.0
### Build MADAM python package and Docker image
make build
The wheel package will be build in the `dist` directory.
## Deploy MADAM as local docker container
To deploy MADAM container on localhost:
make deploy
## Check static type and code quality
make check
## Run tests
Run all [pytest](https://docs.pytest.org) tests with:
make tests
Run only some tests by using `bin/tests.sh`:
bin/tests.sh tests/domains/test_workflows.py::test_create
## Database setup
Set `DATABASE_URL` and `DATABASE_URL_TESTS` environment variable in `.env` file:
DATABASE_URL=postgresql://postgres:xxxxx@hostname:5432/madam?sslmode=allow
DATABASE_URL_TESTS=postgresql://postgres:xxxxx@hostname:5432/madam_tests?sslmode=allow
### Migrations scripts
Add/Edit scripts in `resources/migrations` directory:
# version.name.[rollback].sql
00001.init_tables.sql
00001.init_tables.rollback.sql
### Migrate commands
make databases
make databases_rollback
make databases_list
%package help
Summary: Development documents and examples for madam-mam
Provides: python3-madam-mam-doc
%description help
# MADAM
MADAM is the Multi Agent Digital Asset Manager.
It provides a three-tier architecture platform to handle workflow processing in a distributed environment.
It uses Docker swarm to dispatch processes in a cluster of machines.
It is a free (as freedom) software written in Python.
## Documentation
[Link to the documentation](https://m5231.gitlab.io/documentation/)
## Support
If you find this project useful and want to contribute, please submit issues, merge requests. If you use it regularly,
you can help by the author by a financial support.
## Requirements
You will need [Camunda Modeler 4.11+](https://github.com/camunda/camunda-modeler/releases) to easily create
Zeebe BPMN XML workflows for MADAM.
## Licensing
MADAM is licensed under the [Gnu Public License Version 3](https://www.gnu.org/licenses/gpl-3.0.en.html).
Camunda Modeler is licensed under [the MIT License (MIT)](https://mit-license.org/).
At its core, MADAM use [adhesive-zebe](https://github.com/vtexier/adhesive), a BPMN workflow python engine able to
execute Zeebe BPMN XML workflows. It is a fork of [adhesive](https://github.com/germaniumhq/adhesive) under
the original adhesive license that is [GNU Affero General Public License v3.0](https://www.gnu.org/licenses/agpl-3.0.en.html)
## System environment setup
1. [Install Docker](https://docs.docker.com/engine/install/).
2. [Configure userns-remap](https://docs.docker.com/engine/security/userns-remap/) to map container user `root` to a
host non-root user.
3. Configure the dev station as a [Docker Swarm Manager](https://docs.docker.com/engine/swarm/).
4. Install a [Postgresql](https://www.postgresql.org/download/) database server.
_You can use the Ansible playbook provided to install PostgreSQL locally with Docker,
after configuring `hosts.yaml`:_
make environment
### Python environment setup
* It requires Python 3.8+.
* [Pyenv](https://github.com/pyenv/pyenv) should be used to choose the right version of Python, without breaking the
default Python of the Operating System.
* A Python virtual environment should be created in a `.venv` folder.
```bash
pyenv install 3.8.0
pyenv shell 3.8.0
python -m venv .venv
source .venv/bin/activate`
```
### Installation/Update
From PyPI:
In a Python virtualenv:
pip install -U madam-mam
In your user install directory:
pip install --user -U madam-mam
You should have a the `madam` cli command available:
madam
or
madam --help
will display command usage.
To have bash completion, you can type:
_MADAM_COMPLETE=source_bash madam > madam-complete.sh
sudo cp madam-complete.sh /etc/bash_completion.d/.
For another shell, replace `source_bash` by `source_zsh` or `source_fish`
### Development environment
Install [Poetry](https://python-poetry.org/) with the custom installer:
curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python
Install Python dependencies:
poetry install --no-root
You can use the madam-cli dev command:
./bin/madam-cli
Get `bin/madam-cli` bash shell completion:
_MADAM_CLI_COMPLETE=source_bash bin/madam-cli > madam-cli-complete.sh
sudo cp madam-cli-complete.sh /etc/bash_completion.d/.
For another shell, replace `source_bash` by `source_zsh` or `source_fish`
### Configuration
Make a copy of the environment config example file:
cp .env.example .env
Edit `.env` to suit your needs, then:
export $(grep -v '^#' .env | xargs -d '\n')
Make a copy of the Ansible inventory example file:
cp hosts.yaml.example hosts.yaml
Edit `hosts.yaml` to suit your needs.
Make a copy of the MADAM config example file:
cp madam.yaml.example madam.yaml
Edit `madam.yaml` to suit your needs.
Make a copy of the MADAM config example file for the test environment:
cp madam_tests.yaml.example madam_tests.yaml
Edit `madam_tests.yaml` to suit your needs.
Make a copy of the MADAM config example file for the local deploy:
cp madam_deploy.yaml.example madam_deploy.yaml
Edit `madam_deploy.yaml` to suit your needs.
### Set and tag project version in Git
./bin/release.sh 1.0.0
### Build MADAM python package and Docker image
make build
The wheel package will be build in the `dist` directory.
## Deploy MADAM as local docker container
To deploy MADAM container on localhost:
make deploy
## Check static type and code quality
make check
## Run tests
Run all [pytest](https://docs.pytest.org) tests with:
make tests
Run only some tests by using `bin/tests.sh`:
bin/tests.sh tests/domains/test_workflows.py::test_create
## Database setup
Set `DATABASE_URL` and `DATABASE_URL_TESTS` environment variable in `.env` file:
DATABASE_URL=postgresql://postgres:xxxxx@hostname:5432/madam?sslmode=allow
DATABASE_URL_TESTS=postgresql://postgres:xxxxx@hostname:5432/madam_tests?sslmode=allow
### Migrations scripts
Add/Edit scripts in `resources/migrations` directory:
# version.name.[rollback].sql
00001.init_tables.sql
00001.init_tables.rollback.sql
### Migrate commands
make databases
make databases_rollback
make databases_list
%prep
%autosetup -n madam-mam-0.7.0
%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-madam-mam -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Tue Jun 20 2023 Python_Bot - 0.7.0-1
- Package Spec generated
## Requirements
You will need [Camunda Modeler 4.11+](https://github.com/camunda/camunda-modeler/releases) to easily create
Zeebe BPMN XML workflows for MADAM.
## Licensing
MADAM is licensed under the [Gnu Public License Version 3](https://www.gnu.org/licenses/gpl-3.0.en.html).
Camunda Modeler is licensed under [the MIT License (MIT)](https://mit-license.org/).
At its core, MADAM use [adhesive-zebe](https://github.com/vtexier/adhesive), a BPMN workflow python engine able to
execute Zeebe BPMN XML workflows. It is a fork of [adhesive](https://github.com/germaniumhq/adhesive) under
the original adhesive license that is [GNU Affero General Public License v3.0](https://www.gnu.org/licenses/agpl-3.0.en.html)
## System environment setup
1. [Install Docker](https://docs.docker.com/engine/install/).
2. [Configure userns-remap](https://docs.docker.com/engine/security/userns-remap/) to map container user `root` to a
host non-root user.
3. Configure the dev station as a [Docker Swarm Manager](https://docs.docker.com/engine/swarm/).
4. Install a [Postgresql](https://www.postgresql.org/download/) database server.
_You can use the Ansible playbook provided to install PostgreSQL locally with Docker,
after configuring `hosts.yaml`:_
make environment
### Python environment setup
* It requires Python 3.8+.
* [Pyenv](https://github.com/pyenv/pyenv) should be used to choose the right version of Python, without breaking the
default Python of the Operating System.
* A Python virtual environment should be created in a `.venv` folder.
```bash
pyenv install 3.8.0
pyenv shell 3.8.0
python -m venv .venv
source .venv/bin/activate`
```
### Installation/Update
From PyPI:
In a Python virtualenv:
pip install -U madam-mam
In your user install directory:
pip install --user -U madam-mam
You should have a the `madam` cli command available:
madam
or
madam --help
will display command usage.
To have bash completion, you can type:
_MADAM_COMPLETE=source_bash madam > madam-complete.sh
sudo cp madam-complete.sh /etc/bash_completion.d/.
For another shell, replace `source_bash` by `source_zsh` or `source_fish`
### Development environment
Install [Poetry](https://python-poetry.org/) with the custom installer:
curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python
Install Python dependencies:
poetry install --no-root
You can use the madam-cli dev command:
./bin/madam-cli
Get `bin/madam-cli` bash shell completion:
_MADAM_CLI_COMPLETE=source_bash bin/madam-cli > madam-cli-complete.sh
sudo cp madam-cli-complete.sh /etc/bash_completion.d/.
For another shell, replace `source_bash` by `source_zsh` or `source_fish`
### Configuration
Make a copy of the environment config example file:
cp .env.example .env
Edit `.env` to suit your needs, then:
export $(grep -v '^#' .env | xargs -d '\n')
Make a copy of the Ansible inventory example file:
cp hosts.yaml.example hosts.yaml
Edit `hosts.yaml` to suit your needs.
Make a copy of the MADAM config example file:
cp madam.yaml.example madam.yaml
Edit `madam.yaml` to suit your needs.
Make a copy of the MADAM config example file for the test environment:
cp madam_tests.yaml.example madam_tests.yaml
Edit `madam_tests.yaml` to suit your needs.
Make a copy of the MADAM config example file for the local deploy:
cp madam_deploy.yaml.example madam_deploy.yaml
Edit `madam_deploy.yaml` to suit your needs.
### Set and tag project version in Git
./bin/release.sh 1.0.0
### Build MADAM python package and Docker image
make build
The wheel package will be build in the `dist` directory.
## Deploy MADAM as local docker container
To deploy MADAM container on localhost:
make deploy
## Check static type and code quality
make check
## Run tests
Run all [pytest](https://docs.pytest.org) tests with:
make tests
Run only some tests by using `bin/tests.sh`:
bin/tests.sh tests/domains/test_workflows.py::test_create
## Database setup
Set `DATABASE_URL` and `DATABASE_URL_TESTS` environment variable in `.env` file:
DATABASE_URL=postgresql://postgres:xxxxx@hostname:5432/madam?sslmode=allow
DATABASE_URL_TESTS=postgresql://postgres:xxxxx@hostname:5432/madam_tests?sslmode=allow
### Migrations scripts
Add/Edit scripts in `resources/migrations` directory:
# version.name.[rollback].sql
00001.init_tables.sql
00001.init_tables.rollback.sql
### Migrate commands
make databases
make databases_rollback
make databases_list
%package -n python3-madam-mam
Summary: MADAM (TM) Multi Agent Digital Asset Manager - a MAM server for Docker Swarm to handle higly distributed media processes
Provides: python-madam-mam
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-madam-mam
# MADAM
MADAM is the Multi Agent Digital Asset Manager.
It provides a three-tier architecture platform to handle workflow processing in a distributed environment.
It uses Docker swarm to dispatch processes in a cluster of machines.
It is a free (as freedom) software written in Python.
## Documentation
[Link to the documentation](https://m5231.gitlab.io/documentation/)
## Support
If you find this project useful and want to contribute, please submit issues, merge requests. If you use it regularly,
you can help by the author by a financial support.