semvec/pypi-packages huggingface dataset:
pyrssa 1.0.11
Rssa for Python
License: Apache 2.0

# pyrssa: Python package for Singular Spectrum Analysis

This package contains methods and tools for Singular Spectrum Analysis including decomposition, 
forecasting and gap-filling for univariate and multivariate time series. 
General description of the methods with many examples can be found in the book
Golyandina (2018, <[doi:10.1007/978-3-662-57380-8](https://doi.org/10.1007%2F978-3-662-57380-8)>).

pyrssa is a wrapper over [Rssa package](https://github.com/asl/rssa) made for R language, having its own visualization methods and data structures.

## Install

1. To install the package, make sure you have any [R compiler](https://cran.r-project.org/bin/) installed.
2. Package installer for the latest released version is available at the [Python Package Index (PyPI)](https://pypi.org/project/pyrssa/).
   To install the package, just run the following command:
   
```sh
pip install pyrssa
```

Install requires rpy2, numpy, pandas and matplotlib packages of any version (preferable newest ones).
These packages will be installed automatically during the default installation.

## Documentation

Documentation for pyrssa package is available [here](https://fleyderer.github.io/pyrssa/).

## Examples

Package usage examples are available in [examples folder](https://github.com/Fleyderer/pyrssa/tree/master/examples).

Original examples with identical numbering are available [here](https://ssa-with-r-book.github.io/).

## Source code

Source code of pyrssa package is available in [pyrssa folder](https://github.com/Fleyderer/pyrssa/tree/master/pyrssa).
xfhir 0.0.2
XFHIR Python SDK
License: Apache 2.0
Requires Python: >=3
Keywords: package development template

# XFHIR Python SDK


```python

import xfhir
xfhir.init(client_id='xxx', client_secret='xxxx')
xfhir.create({})
xfhir.get(id='', resource_type='Patient')
xfhir.filter(resource_type='Patient', q='')
xfhir.search(q='')
```







Connect to the XFHIR Service
```python
from xfhir import XFHIR
x = XFHIR(client_id='xxx', client_secret='xxxx')

```

Create a Policy for a FHIR Resource
```python
patient_redact_policy = x.policy.create(effect='Redact', actions=[
   'account-id:client-id:method:resource:path',
   'account-id:*:Read:Patient:$',
])
```

Create the FHIR Resource on XFHIR along with its resource policies
```python
x.create({
   'fhir_resource': {},
   'policies': [
      patient_redact_policy
   ]
})

```

Full example
```python
from xfhir import XFHIR
x = XFHIR(client_id='xxx', client_secret='xxxx')

patient_redact_policy = x.policy.create(effect='Redact', actions=[
   'account-id:client-id:method:resource:path',
   'account-id:*:Read:Patient:$',
])

x.create({
   'fhir_resource': {},
   'policies': [
      patient_redact_policy
   ]
})

patient = x.get('Patient', 'identifier')
```

The output of the patient object should be

```json

{
   "id": "*** REDACTED **",
   "name": "*** REDACTED **"
}
```


To redact only a few fields in the patient object you can create a policy that only redacts your custom fields
```python

patient_redact_policy = x.policy.create(effect='Redact', actions=[
   'account-id:*:Read:Patient:$.id',
   'account-id:*:Read:Patient:$.name',
   'account-id:*:Read:Patient:$.contact'   
])

```