path: root/python-ayeaye.spec

%global _empty_manifest_terminate_build 0
Name:		python-ayeaye
Version:	0.0.45
Release:	1
Summary:	An ETL (Extract, Transform, Load) framework
License:	Apache Software License
URL:		https://github.com/Aye-Aye-Dev/AyeAye
Source0:	https://mirrors.aliyun.com/pypi/web/packages/12/d4/36db2468a349a551797f7eae9d1dc2727ab8d0074aa4e70a7486f2f25b12/ayeaye-0.0.45.tar.gz
BuildArch:	noarch

Requires:	python3-requests
Requires:	python3-boto3
Requires:	python3-smart-open
Requires:	python3-smart-open

%description
# Aye Aye

An ETL (Extract, Transform, Load) framework.

## Quick install

In the virtual environment for the project you’d like to use Aye Aye in, run:-

```shell
pip install ayeaye
```

## Quick start

Use [Pipenv](https://pipenv.pypa.io/en/latest/) to manage a python virtual environment and package management0

```shell
pipenv shell
pipenv install ayeaye
```

Within the environment created by pipenv above, run one of the examples:-

```shell
curl "https://raw.githubusercontent.com/Aye-Aye-Dev/AyeAye/master/examples/poisonous_animals.py" \
  --output poisonous_animals.py
mkdir data
curl https://raw.githubusercontent.com/Aye-Aye-Dev/AyeAye/master/examples/data/poisonous_animals.json \
  --output data/poisonous_animals.json
python poisonous_animals.py 
```

This model takes a small input dataset of animals and collates them by the country they are found. It doesn't write to a dataset, it just outputs a log. The log for this example contains the name of the country and the animals found there.

There are more examples in the [Aye-Aye-Recipes](https://github.com/Aye-Aye-Dev/Aye-Aye-Recipes) git repo.


## Overview

An Aye Aye ETL *model* inherits from `ayeaye.model` and uses class level variables to declare *connectors* to the data it acts on.

Example:-

```python
import ayeaye

class PoisonousAnimals(ayeaye.Model):
    poisonous_animals = ayeaye.Connect(engine_url='json://data/poisonous_animals.json')
```

When instantiated, `self.poisonous_animals` will be a *dataset* that ETL operations can be done with.

The `engine_url` parameter passed to `ayeaye.Connect` is specifying the dataset type JSON in this case) and exact location for the data (`data/poisonous_animals.json` is a relative file path).

Instead of `engine_url` you could also specify a `ref` and this uses the data catalogue to lookup the `engine_url`. (TODO this feature is coming soon!). When used this way, `ayeaye.Connect` is responsible for resolving the `ref` to an `engine_url` and passing this to a subclass of `ayeaye.connectors.base.DataConnector` which can read and maybe write this data type.


## Unit tests

Ensure the working directory is the base Aye Aye directory (i.e. the same directory as the Pipfile):
```shell
pipenv install --dev
export PYTHONPATH=`pwd`/lib
pipenv run python -m unittest discover
```

## Development version

To use the latest code in editable mode-

```shell
pipenv install -e git+https://github.com/Aye-Aye-Dev/AyeAye#egg=ayeaye
```

When `venv` is being used, add this line to `requirements.txt`-

```
git+https://github.com/Aye-Aye-Dev/AyeAye#egg=ayeaye
```

## Optional extras

Extra dependencies for API usage within Aye-aye models can be installed like this:

```shell
pipenv install "ayeaye[api]"
```

| Label | Functionality |
| --- | --- |
| api | Restful JSON via http(s) |
| aws | File based connectors can use Amazon Web Service S3 file storage |
| compression | On the fly compression for file based connectors |


## License

Aye Aye is distributed under the terms of the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0.html) and Copyright Progressive Logic Limit 2021 and onwards.


%package -n python3-ayeaye
Summary:	An ETL (Extract, Transform, Load) framework
Provides:	python-ayeaye
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-ayeaye
# Aye Aye

An ETL (Extract, Transform, Load) framework.

## Quick install

In the virtual environment for the project you’d like to use Aye Aye in, run:-

```shell
pip install ayeaye
```

## Quick start

Use [Pipenv](https://pipenv.pypa.io/en/latest/) to manage a python virtual environment and package management0

```shell
pipenv shell
pipenv install ayeaye
```

Within the environment created by pipenv above, run one of the examples:-

```shell
curl "https://raw.githubusercontent.com/Aye-Aye-Dev/AyeAye/master/examples/poisonous_animals.py" \
  --output poisonous_animals.py
mkdir data
curl https://raw.githubusercontent.com/Aye-Aye-Dev/AyeAye/master/examples/data/poisonous_animals.json \
  --output data/poisonous_animals.json
python poisonous_animals.py 
```

This model takes a small input dataset of animals and collates them by the country they are found. It doesn't write to a dataset, it just outputs a log. The log for this example contains the name of the country and the animals found there.

There are more examples in the [Aye-Aye-Recipes](https://github.com/Aye-Aye-Dev/Aye-Aye-Recipes) git repo.


## Overview

An Aye Aye ETL *model* inherits from `ayeaye.model` and uses class level variables to declare *connectors* to the data it acts on.

Example:-

```python
import ayeaye

class PoisonousAnimals(ayeaye.Model):
    poisonous_animals = ayeaye.Connect(engine_url='json://data/poisonous_animals.json')
```

When instantiated, `self.poisonous_animals` will be a *dataset* that ETL operations can be done with.

The `engine_url` parameter passed to `ayeaye.Connect` is specifying the dataset type JSON in this case) and exact location for the data (`data/poisonous_animals.json` is a relative file path).

Instead of `engine_url` you could also specify a `ref` and this uses the data catalogue to lookup the `engine_url`. (TODO this feature is coming soon!). When used this way, `ayeaye.Connect` is responsible for resolving the `ref` to an `engine_url` and passing this to a subclass of `ayeaye.connectors.base.DataConnector` which can read and maybe write this data type.


## Unit tests

Ensure the working directory is the base Aye Aye directory (i.e. the same directory as the Pipfile):
```shell
pipenv install --dev
export PYTHONPATH=`pwd`/lib
pipenv run python -m unittest discover
```

## Development version

To use the latest code in editable mode-

```shell
pipenv install -e git+https://github.com/Aye-Aye-Dev/AyeAye#egg=ayeaye
```

When `venv` is being used, add this line to `requirements.txt`-

```
git+https://github.com/Aye-Aye-Dev/AyeAye#egg=ayeaye
```

## Optional extras

Extra dependencies for API usage within Aye-aye models can be installed like this:

```shell
pipenv install "ayeaye[api]"
```

| Label | Functionality |
| --- | --- |
| api | Restful JSON via http(s) |
| aws | File based connectors can use Amazon Web Service S3 file storage |
| compression | On the fly compression for file based connectors |


## License

Aye Aye is distributed under the terms of the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0.html) and Copyright Progressive Logic Limit 2021 and onwards.


%package help
Summary:	Development documents and examples for ayeaye
Provides:	python3-ayeaye-doc
%description help
# Aye Aye

An ETL (Extract, Transform, Load) framework.

## Quick install

In the virtual environment for the project you’d like to use Aye Aye in, run:-

```shell
pip install ayeaye
```

## Quick start

Use [Pipenv](https://pipenv.pypa.io/en/latest/) to manage a python virtual environment and package management0

```shell
pipenv shell
pipenv install ayeaye
```

Within the environment created by pipenv above, run one of the examples:-

```shell
curl "https://raw.githubusercontent.com/Aye-Aye-Dev/AyeAye/master/examples/poisonous_animals.py" \
  --output poisonous_animals.py
mkdir data
curl https://raw.githubusercontent.com/Aye-Aye-Dev/AyeAye/master/examples/data/poisonous_animals.json \
  --output data/poisonous_animals.json
python poisonous_animals.py 
```

This model takes a small input dataset of animals and collates them by the country they are found. It doesn't write to a dataset, it just outputs a log. The log for this example contains the name of the country and the animals found there.

There are more examples in the [Aye-Aye-Recipes](https://github.com/Aye-Aye-Dev/Aye-Aye-Recipes) git repo.


## Overview

An Aye Aye ETL *model* inherits from `ayeaye.model` and uses class level variables to declare *connectors* to the data it acts on.

Example:-

```python
import ayeaye

class PoisonousAnimals(ayeaye.Model):
    poisonous_animals = ayeaye.Connect(engine_url='json://data/poisonous_animals.json')
```

When instantiated, `self.poisonous_animals` will be a *dataset* that ETL operations can be done with.

The `engine_url` parameter passed to `ayeaye.Connect` is specifying the dataset type JSON in this case) and exact location for the data (`data/poisonous_animals.json` is a relative file path).

Instead of `engine_url` you could also specify a `ref` and this uses the data catalogue to lookup the `engine_url`. (TODO this feature is coming soon!). When used this way, `ayeaye.Connect` is responsible for resolving the `ref` to an `engine_url` and passing this to a subclass of `ayeaye.connectors.base.DataConnector` which can read and maybe write this data type.


## Unit tests

Ensure the working directory is the base Aye Aye directory (i.e. the same directory as the Pipfile):
```shell
pipenv install --dev
export PYTHONPATH=`pwd`/lib
pipenv run python -m unittest discover
```

## Development version

To use the latest code in editable mode-

```shell
pipenv install -e git+https://github.com/Aye-Aye-Dev/AyeAye#egg=ayeaye
```

When `venv` is being used, add this line to `requirements.txt`-

```
git+https://github.com/Aye-Aye-Dev/AyeAye#egg=ayeaye
```

## Optional extras

Extra dependencies for API usage within Aye-aye models can be installed like this:

```shell
pipenv install "ayeaye[api]"
```

| Label | Functionality |
| --- | --- |
| api | Restful JSON via http(s) |
| aws | File based connectors can use Amazon Web Service S3 file storage |
| compression | On the fly compression for file based connectors |


## License

Aye Aye is distributed under the terms of the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0.html) and Copyright Progressive Logic Limit 2021 and onwards.


%prep
%autosetup -n ayeaye-0.0.45

%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-ayeaye -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 0.0.45-1
- Package Spec generated