%global _empty_manifest_terminate_build 0
Name:		python-hyperscience-saas-client
Version:	1.0.9
Release:	1
Summary:	hyperscience saas client library
License:	Apache License 2.0
URL:		https://pypi.org/project/hyperscience-saas-client/
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/87/1a/220ad61b8abcae4d9a622e332fea83ed27d4b876574ac65b58ed5f9f77c6/hyperscience-saas-client-1.0.9.tar.gz
BuildArch:	noarch

Requires:	python3-requests
Requires:	python3-urllib3

%description
# Hyperscience SaaS Client Library
With the Hyperscience SaaS client library, you can authenticate to SaaS instances of Hyperscience and make API requests. 

## Quickstart Guide
### 1. Install Hyperscience SaaS Client Library
Install the Hyperscience SAAS Client Library from PyPI:
```shell
pip install hyperscience-saas-client
```

To upgrade the package:
```shell
pip install hyperscience-saas-client --upgrade
```

### 2. Set Up API Credentials
Retrieve your API credentials from your Hyperscience SaaS instance. To learn more, see API Access for SaaS Instances.

### 3. Configure Authentication Parameters
To configure authentication, the ApiController uses a Configuration class. A configuration object contains:
- Authentication domain ("auth_server”)
- Hyperscience's domain to make the requests to ("hs_domain")
- Timeout for requests in seconds (optional) ("request_timeout")

By default, these values are used:
```json
{
    "auth_server": "login.hyperscience.net",
    "hs_domain": "cloud.hyperscience.net",
    "request_timeout": 120 
}
```

You can set your Configuration object in one of the following three ways:
#### Passing a JSON object
```python
from hyperscience import Configuration

config = '{ "auth_server": "login.hyperscience.net", "hs_domain": "cloud.hyperscience.net" }'
configuration = Configuration.from_json_string(config)
```

#### Full path to a JSON file containing the configuration
```python
from hyperscience import Configuration

configuration = Configuration.from_file('/absolute/path/to/config.json')
```

#### Specifying the parameters
```python
from hyperscience import Configuration
configuration = Configuration(hs_domain='cloud.hyperscience.net')
# or
configuration = Configuration(hs_domain='cloud.hyperscience.net', auth_server='login.hyperscience.net')
# or 
configuration = Configuration(
    hs_domain='cloud.hyperscience.net', auth_server='login.hyperscience.net', request_timeout=60
)
```

### 4. Provide Credentials
There are two options for providing credentials:

#### a. Environment Variables (Recommended) 
To use environment variables to store your credentials:
1. Put your client_id in an environment variable called HS_CLIENT_ID
2. Put the client_secret in an environment variable called HS_CLIENT_SECRET

To load them and pass them to ApiController, you can do it with:
```python
from hyperscience import EnvironmentCredentialsProvider, Configuration, ApiController

credentials = EnvironmentCredentialsProvider()
configuration = Configuration('<hyperscience.domain>')
api_controller = ApiController(configuration, credentials)
```

#### b. Pass them via a CredentialsProvider object
If you prefer having credentials loaded from a different place instead of environment variables, you can create an instance of the CredentialsProvider class and pass it to ApiController:
```python
from hyperscience import CredentialsProvider, Configuration, ApiController
credentials = CredentialsProvider('client_id', 'client_secret')
configuration = Configuration('<hyperscience.domain>')
api_controller = ApiController(configuration, credentials)
```

> **WARNING**: Keeping credentials in code is a bad practice. CredentialsProvider is best used when loading credentials from secret stores.

### 5. Make a Test Call
Finally, ensure that your setup is correct by making a test call to GET submissions from your instance.
```python
from hyperscience import ApiController, CredentialsProvider, Configuration

credentials = CredentialsProvider('<client_id>', '<client_secret>')
configuration = Configuration('<hyperscience.domain>')
api_controller = ApiController(configuration, credentials)

response = api_controller.get('/api/v5/submissions')
```

## Using the ApiController 
The ApiController allows users to interact with the Hyperscience API using easy-to-use wrapper methods. You can find Hyperscience’s API documentation here.

### Supported HTTP Methods
**GET**, **POST** and **PUT** operations are supported by the ApiController.\
Content (query params, encoded url parameters or files input) is accepted in the form of Dict[str, str] or List[Tuple[str, str]].\
To support multiple parameters of the same type (e.g. 'file' for submitting multiple files), parameters should be passed as List[Tuple[str, str]].
#### Examples
##### Configuration and Setup
```python
from hyperscience import ApiController, Configuration
from hyperscience.api import DataSupportedMediaType, PayloadSupportedMediaType

# Create an ApiController instance 
api_controller = ApiController(Configuration('cloud.hyperscience.net'))
```


#### GET Submissions
```python
# GET request with query params provided in dictionary
query_params = {'state': 'complete'}
res = api_controller.get('/api/v5/submissions', query_params)
print(res, res.content)

# GET request with query params provided in List[Tuple] format
query_params = [('state', 'complete')]
res = api_controller.get('/api/v5/submissions', query_params)
print(res, res.content)
```

#### POST a New Submission using URL-Encoded Form.
```python
# POST request with WwwFormUrlEncoded content-type to submit files from remote servers
# with List[Tuple] (multiple identical keys, e.g. multiple files)
data = [
    ('file', 'https://www.dropbox.com/demo-long.pdf'),
    (
        'file',
        's3://hyperscience/bucket/form1.pdf',
    ),
    ('machine_only', True),
]
res = api_controller.post('/api/v5/submissions', data, DataSupportedMediaType.FORM_URL_ENCODED)
print(res, res.content)

# POST request to submit files from remote servers with a dictionary (unique keys)
data = {
    'file': 'https://www.dropbox.com/demo-long.pdf',
    'machine_only': True,
}
res = api_controller.post('/api/v5/submissions', data, DataSupportedMediaType.FORM_URL_ENCODED)
print(res, res.content)

# POST request to submit files from remote servers with a dictionary (unique keys)
data = {
    'file': 'https://www.dropbox.com/demo-long.pdf',
    'machine_only': True,
}
res = api_controller.post('/api/v5/submissions', data, DataSupportedMediaType.FORM_URL_ENCODED)
print(res, res.content)
```

#### POST a New Submission Using MultipartFormData
```python
# POST request with MultipartFormData content-type to upload files from local filesystem with dictionary (unique keys)
data = {'file': '/absolute/path/to/file.pdf', 'machine_only': True}
res = api_controller.post('/api/v5/submissions', data, DataSupportedMediaType.MULTIPART_FORM_DATA)
print(res, res.content)

# POST request with MultipartFormData content-type to upload files from local filesystem with List[Tuple] (multiple identical keys, e.g. multiple files)
data = [
    ('file', '/absolute/path/to/file.pdf'),
    ('file', '/absolute/path/to/file2.pdf'),
    ('machine_only', True),
]
res = api_controller.post('/api/v5/submissions', data, DataSupportedMediaType.MULTIPART_FORM_DATA)
print(res, res.content)
```

#### POST a New Submission Using JSON
POST request with ApplicationJson content-type to submit base 64 encoded files using a dictionary
```python
json_data = {
    "metadata": {},
    "machine_only": True,
    "goal_duration_minutes": 5,
    "single_document_per_page": True,
    "restrictions": [],
    "source_routing_tags": ["tag1", "tag2"],
    "files": [
        {
            "file_content_base64": "data:image/png;base64,iVBORw0KGgoAAA…II=",
            "filename": "image.png"
        }
    ],
    "cases": [
        {
            "external_case_id": "case_1",
            "filenames": ["image.png"]
        }
    ]
}
res = api_controller.post('/api/v5/submissions', json_data, PayloadSupportedMediaType.APPLICATION_JSON)
print(res, res.content)
```

## Logging
The library implements HyperscienceLogging class to log messages related to the library. 
To set a different logging level, you can use the function <code>HyperscienceLogging.set_hyperscience_logging_level()</code> and choose from the following list of logging levels: <em>CRITICAL, FATAL, ERROR, WARNING, INFO, DEBUG</em>.



%package -n python3-hyperscience-saas-client
Summary:	hyperscience saas client library
Provides:	python-hyperscience-saas-client
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-hyperscience-saas-client
# Hyperscience SaaS Client Library
With the Hyperscience SaaS client library, you can authenticate to SaaS instances of Hyperscience and make API requests. 

## Quickstart Guide
### 1. Install Hyperscience SaaS Client Library
Install the Hyperscience SAAS Client Library from PyPI:
```shell
pip install hyperscience-saas-client
```

To upgrade the package:
```shell
pip install hyperscience-saas-client --upgrade
```

### 2. Set Up API Credentials
Retrieve your API credentials from your Hyperscience SaaS instance. To learn more, see API Access for SaaS Instances.

### 3. Configure Authentication Parameters
To configure authentication, the ApiController uses a Configuration class. A configuration object contains:
- Authentication domain ("auth_server”)
- Hyperscience's domain to make the requests to ("hs_domain")
- Timeout for requests in seconds (optional) ("request_timeout")

By default, these values are used:
```json
{
    "auth_server": "login.hyperscience.net",
    "hs_domain": "cloud.hyperscience.net",
    "request_timeout": 120 
}
```

You can set your Configuration object in one of the following three ways:
#### Passing a JSON object
```python
from hyperscience import Configuration

config = '{ "auth_server": "login.hyperscience.net", "hs_domain": "cloud.hyperscience.net" }'
configuration = Configuration.from_json_string(config)
```

#### Full path to a JSON file containing the configuration
```python
from hyperscience import Configuration

configuration = Configuration.from_file('/absolute/path/to/config.json')
```

#### Specifying the parameters
```python
from hyperscience import Configuration
configuration = Configuration(hs_domain='cloud.hyperscience.net')
# or
configuration = Configuration(hs_domain='cloud.hyperscience.net', auth_server='login.hyperscience.net')
# or 
configuration = Configuration(
    hs_domain='cloud.hyperscience.net', auth_server='login.hyperscience.net', request_timeout=60
)
```

### 4. Provide Credentials
There are two options for providing credentials:

#### a. Environment Variables (Recommended) 
To use environment variables to store your credentials:
1. Put your client_id in an environment variable called HS_CLIENT_ID
2. Put the client_secret in an environment variable called HS_CLIENT_SECRET

To load them and pass them to ApiController, you can do it with:
```python
from hyperscience import EnvironmentCredentialsProvider, Configuration, ApiController

credentials = EnvironmentCredentialsProvider()
configuration = Configuration('<hyperscience.domain>')
api_controller = ApiController(configuration, credentials)
```

#### b. Pass them via a CredentialsProvider object
If you prefer having credentials loaded from a different place instead of environment variables, you can create an instance of the CredentialsProvider class and pass it to ApiController:
```python
from hyperscience import CredentialsProvider, Configuration, ApiController
credentials = CredentialsProvider('client_id', 'client_secret')
configuration = Configuration('<hyperscience.domain>')
api_controller = ApiController(configuration, credentials)
```

> **WARNING**: Keeping credentials in code is a bad practice. CredentialsProvider is best used when loading credentials from secret stores.

### 5. Make a Test Call
Finally, ensure that your setup is correct by making a test call to GET submissions from your instance.
```python
from hyperscience import ApiController, CredentialsProvider, Configuration

credentials = CredentialsProvider('<client_id>', '<client_secret>')
configuration = Configuration('<hyperscience.domain>')
api_controller = ApiController(configuration, credentials)

response = api_controller.get('/api/v5/submissions')
```

## Using the ApiController 
The ApiController allows users to interact with the Hyperscience API using easy-to-use wrapper methods. You can find Hyperscience’s API documentation here.

### Supported HTTP Methods
**GET**, **POST** and **PUT** operations are supported by the ApiController.\
Content (query params, encoded url parameters or files input) is accepted in the form of Dict[str, str] or List[Tuple[str, str]].\
To support multiple parameters of the same type (e.g. 'file' for submitting multiple files), parameters should be passed as List[Tuple[str, str]].
#### Examples
##### Configuration and Setup
```python
from hyperscience import ApiController, Configuration
from hyperscience.api import DataSupportedMediaType, PayloadSupportedMediaType

# Create an ApiController instance 
api_controller = ApiController(Configuration('cloud.hyperscience.net'))
```


#### GET Submissions
```python
# GET request with query params provided in dictionary
query_params = {'state': 'complete'}
res = api_controller.get('/api/v5/submissions', query_params)
print(res, res.content)

# GET request with query params provided in List[Tuple] format
query_params = [('state', 'complete')]
res = api_controller.get('/api/v5/submissions', query_params)
print(res, res.content)
```

#### POST a New Submission using URL-Encoded Form.
```python
# POST request with WwwFormUrlEncoded content-type to submit files from remote servers
# with List[Tuple] (multiple identical keys, e.g. multiple files)
data = [
    ('file', 'https://www.dropbox.com/demo-long.pdf'),
    (
        'file',
        's3://hyperscience/bucket/form1.pdf',
    ),
    ('machine_only', True),
]
res = api_controller.post('/api/v5/submissions', data, DataSupportedMediaType.FORM_URL_ENCODED)
print(res, res.content)

# POST request to submit files from remote servers with a dictionary (unique keys)
data = {
    'file': 'https://www.dropbox.com/demo-long.pdf',
    'machine_only': True,
}
res = api_controller.post('/api/v5/submissions', data, DataSupportedMediaType.FORM_URL_ENCODED)
print(res, res.content)

# POST request to submit files from remote servers with a dictionary (unique keys)
data = {
    'file': 'https://www.dropbox.com/demo-long.pdf',
    'machine_only': True,
}
res = api_controller.post('/api/v5/submissions', data, DataSupportedMediaType.FORM_URL_ENCODED)
print(res, res.content)
```

#### POST a New Submission Using MultipartFormData
```python
# POST request with MultipartFormData content-type to upload files from local filesystem with dictionary (unique keys)
data = {'file': '/absolute/path/to/file.pdf', 'machine_only': True}
res = api_controller.post('/api/v5/submissions', data, DataSupportedMediaType.MULTIPART_FORM_DATA)
print(res, res.content)

# POST request with MultipartFormData content-type to upload files from local filesystem with List[Tuple] (multiple identical keys, e.g. multiple files)
data = [
    ('file', '/absolute/path/to/file.pdf'),
    ('file', '/absolute/path/to/file2.pdf'),
    ('machine_only', True),
]
res = api_controller.post('/api/v5/submissions', data, DataSupportedMediaType.MULTIPART_FORM_DATA)
print(res, res.content)
```

#### POST a New Submission Using JSON
POST request with ApplicationJson content-type to submit base 64 encoded files using a dictionary
```python
json_data = {
    "metadata": {},
    "machine_only": True,
    "goal_duration_minutes": 5,
    "single_document_per_page": True,
    "restrictions": [],
    "source_routing_tags": ["tag1", "tag2"],
    "files": [
        {
            "file_content_base64": "data:image/png;base64,iVBORw0KGgoAAA…II=",
            "filename": "image.png"
        }
    ],
    "cases": [
        {
            "external_case_id": "case_1",
            "filenames": ["image.png"]
        }
    ]
}
res = api_controller.post('/api/v5/submissions', json_data, PayloadSupportedMediaType.APPLICATION_JSON)
print(res, res.content)
```

## Logging
The library implements HyperscienceLogging class to log messages related to the library. 
To set a different logging level, you can use the function <code>HyperscienceLogging.set_hyperscience_logging_level()</code> and choose from the following list of logging levels: <em>CRITICAL, FATAL, ERROR, WARNING, INFO, DEBUG</em>.



%package help
Summary:	Development documents and examples for hyperscience-saas-client
Provides:	python3-hyperscience-saas-client-doc
%description help
# Hyperscience SaaS Client Library
With the Hyperscience SaaS client library, you can authenticate to SaaS instances of Hyperscience and make API requests. 

## Quickstart Guide
### 1. Install Hyperscience SaaS Client Library
Install the Hyperscience SAAS Client Library from PyPI:
```shell
pip install hyperscience-saas-client
```

To upgrade the package:
```shell
pip install hyperscience-saas-client --upgrade
```

### 2. Set Up API Credentials
Retrieve your API credentials from your Hyperscience SaaS instance. To learn more, see API Access for SaaS Instances.

### 3. Configure Authentication Parameters
To configure authentication, the ApiController uses a Configuration class. A configuration object contains:
- Authentication domain ("auth_server”)
- Hyperscience's domain to make the requests to ("hs_domain")
- Timeout for requests in seconds (optional) ("request_timeout")

By default, these values are used:
```json
{
    "auth_server": "login.hyperscience.net",
    "hs_domain": "cloud.hyperscience.net",
    "request_timeout": 120 
}
```

You can set your Configuration object in one of the following three ways:
#### Passing a JSON object
```python
from hyperscience import Configuration

config = '{ "auth_server": "login.hyperscience.net", "hs_domain": "cloud.hyperscience.net" }'
configuration = Configuration.from_json_string(config)
```

#### Full path to a JSON file containing the configuration
```python
from hyperscience import Configuration

configuration = Configuration.from_file('/absolute/path/to/config.json')
```

#### Specifying the parameters
```python
from hyperscience import Configuration
configuration = Configuration(hs_domain='cloud.hyperscience.net')
# or
configuration = Configuration(hs_domain='cloud.hyperscience.net', auth_server='login.hyperscience.net')
# or 
configuration = Configuration(
    hs_domain='cloud.hyperscience.net', auth_server='login.hyperscience.net', request_timeout=60
)
```

### 4. Provide Credentials
There are two options for providing credentials:

#### a. Environment Variables (Recommended) 
To use environment variables to store your credentials:
1. Put your client_id in an environment variable called HS_CLIENT_ID
2. Put the client_secret in an environment variable called HS_CLIENT_SECRET

To load them and pass them to ApiController, you can do it with:
```python
from hyperscience import EnvironmentCredentialsProvider, Configuration, ApiController

credentials = EnvironmentCredentialsProvider()
configuration = Configuration('<hyperscience.domain>')
api_controller = ApiController(configuration, credentials)
```

#### b. Pass them via a CredentialsProvider object
If you prefer having credentials loaded from a different place instead of environment variables, you can create an instance of the CredentialsProvider class and pass it to ApiController:
```python
from hyperscience import CredentialsProvider, Configuration, ApiController
credentials = CredentialsProvider('client_id', 'client_secret')
configuration = Configuration('<hyperscience.domain>')
api_controller = ApiController(configuration, credentials)
```

> **WARNING**: Keeping credentials in code is a bad practice. CredentialsProvider is best used when loading credentials from secret stores.

### 5. Make a Test Call
Finally, ensure that your setup is correct by making a test call to GET submissions from your instance.
```python
from hyperscience import ApiController, CredentialsProvider, Configuration

credentials = CredentialsProvider('<client_id>', '<client_secret>')
configuration = Configuration('<hyperscience.domain>')
api_controller = ApiController(configuration, credentials)

response = api_controller.get('/api/v5/submissions')
```

## Using the ApiController 
The ApiController allows users to interact with the Hyperscience API using easy-to-use wrapper methods. You can find Hyperscience’s API documentation here.

### Supported HTTP Methods
**GET**, **POST** and **PUT** operations are supported by the ApiController.\
Content (query params, encoded url parameters or files input) is accepted in the form of Dict[str, str] or List[Tuple[str, str]].\
To support multiple parameters of the same type (e.g. 'file' for submitting multiple files), parameters should be passed as List[Tuple[str, str]].
#### Examples
##### Configuration and Setup
```python
from hyperscience import ApiController, Configuration
from hyperscience.api import DataSupportedMediaType, PayloadSupportedMediaType

# Create an ApiController instance 
api_controller = ApiController(Configuration('cloud.hyperscience.net'))
```


#### GET Submissions
```python
# GET request with query params provided in dictionary
query_params = {'state': 'complete'}
res = api_controller.get('/api/v5/submissions', query_params)
print(res, res.content)

# GET request with query params provided in List[Tuple] format
query_params = [('state', 'complete')]
res = api_controller.get('/api/v5/submissions', query_params)
print(res, res.content)
```

#### POST a New Submission using URL-Encoded Form.
```python
# POST request with WwwFormUrlEncoded content-type to submit files from remote servers
# with List[Tuple] (multiple identical keys, e.g. multiple files)
data = [
    ('file', 'https://www.dropbox.com/demo-long.pdf'),
    (
        'file',
        's3://hyperscience/bucket/form1.pdf',
    ),
    ('machine_only', True),
]
res = api_controller.post('/api/v5/submissions', data, DataSupportedMediaType.FORM_URL_ENCODED)
print(res, res.content)

# POST request to submit files from remote servers with a dictionary (unique keys)
data = {
    'file': 'https://www.dropbox.com/demo-long.pdf',
    'machine_only': True,
}
res = api_controller.post('/api/v5/submissions', data, DataSupportedMediaType.FORM_URL_ENCODED)
print(res, res.content)

# POST request to submit files from remote servers with a dictionary (unique keys)
data = {
    'file': 'https://www.dropbox.com/demo-long.pdf',
    'machine_only': True,
}
res = api_controller.post('/api/v5/submissions', data, DataSupportedMediaType.FORM_URL_ENCODED)
print(res, res.content)
```

#### POST a New Submission Using MultipartFormData
```python
# POST request with MultipartFormData content-type to upload files from local filesystem with dictionary (unique keys)
data = {'file': '/absolute/path/to/file.pdf', 'machine_only': True}
res = api_controller.post('/api/v5/submissions', data, DataSupportedMediaType.MULTIPART_FORM_DATA)
print(res, res.content)

# POST request with MultipartFormData content-type to upload files from local filesystem with List[Tuple] (multiple identical keys, e.g. multiple files)
data = [
    ('file', '/absolute/path/to/file.pdf'),
    ('file', '/absolute/path/to/file2.pdf'),
    ('machine_only', True),
]
res = api_controller.post('/api/v5/submissions', data, DataSupportedMediaType.MULTIPART_FORM_DATA)
print(res, res.content)
```

#### POST a New Submission Using JSON
POST request with ApplicationJson content-type to submit base 64 encoded files using a dictionary
```python
json_data = {
    "metadata": {},
    "machine_only": True,
    "goal_duration_minutes": 5,
    "single_document_per_page": True,
    "restrictions": [],
    "source_routing_tags": ["tag1", "tag2"],
    "files": [
        {
            "file_content_base64": "data:image/png;base64,iVBORw0KGgoAAA…II=",
            "filename": "image.png"
        }
    ],
    "cases": [
        {
            "external_case_id": "case_1",
            "filenames": ["image.png"]
        }
    ]
}
res = api_controller.post('/api/v5/submissions', json_data, PayloadSupportedMediaType.APPLICATION_JSON)
print(res, res.content)
```

## Logging
The library implements HyperscienceLogging class to log messages related to the library. 
To set a different logging level, you can use the function <code>HyperscienceLogging.set_hyperscience_logging_level()</code> and choose from the following list of logging levels: <em>CRITICAL, FATAL, ERROR, WARNING, INFO, DEBUG</em>.



%prep
%autosetup -n hyperscience-saas-client-1.0.9

%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-hyperscience-saas-client -f filelist.lst
%dir %{python3_sitelib}/*

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

%changelog
* Tue Apr 25 2023 Python_Bot <Python_Bot@openeuler.org> - 1.0.9-1
- Package Spec generated