semvec/pypi-packages huggingface dataset:
pr-keepachangelog 1.0.11
Add pull requests to changelog automatically with BitBucket pipelines and release changelog with keepachangelog.
License: MIT

### Documentation
The package can be installed with `pip install pr-keepachangelog`.
For help and to use it: `python -m pr_keepachangelog`.

Based on a pull request that is merged on a certain branch, you can populate the changelog automatically. The category in which the changelog is populated depends on the prefix of the specified branch:
- hotfix/ -> Fixed
- feature/ -> Fixed
- bugfix/ -> Fixed
# additional branch types
- deprecated/ -> Deprecated
- changed/ -> Changed
- removed/ -> Removed
- security/ -> Security

### Keepachangelog categories
Keepachangelog will guess the new version number when you make a release with `--release`:
- Added: for new features. Results in minor update.
- Changed: for changes in existing functionality. Results in major update.
- Deprecated: for soon-to-be removed features. Results in major update.
- Removed: for now removed features. Results in major update.
- Fixed: for any bug fixes (hotfix/bugfix). Results in patch update.
- Security: in case of vulnerabilities. Results in patch update.
fhir-biobank 0.1.3
Python library working with FHIR standard in scope of biobanks MIABIS requirements
License: MIT

# FHIR Library

This Python library is simplifying work with FHIR library focused on BBMRI-ERIC biobanks.
This library works with Patient, Specimen, and Condition resources, along with
extensions needed for these resources as defined by [simplifier.net/bbrmi.de](https://simplifier.net/bbmri.de).

Documentation of this library is available at [fhir-biobank.readthedocs.io](https://fhir-biobank.readthedocs.io)


## Installation
pip install fhir-biobank

## Usage
This library allows you to easily create FHIR resources along with all the data in a single constructor.
Use case of creating a simple Patient resource:
```python
from fhir_biobank import PatientResource

internal_id = "0"
patient_identifier = "4816522"
patient_gender = "female"
patient_birthdate = date(2000, 12, 11)
patient = PatientResource(internal_id, patient_identifier, patient_gender, patient_birthdate)
```

Standard action is to convert FHIR resource to a JSON representation.
Use case of converting Patient resource to a JSON representation:

```python
json_representation = patient.patientJSON()
```

JSON representation of the Patient resource initialized above looks like this:
```json
{
  "id": "0",
  "meta": { "profile": [ "https://fhir.bbmri.de/StructureDefinition/Patient" ] },
  "birthDate": "2000-12-11",
  "deceasedBoolean": "False",
  "gender": "female",
  "identifier": [
    {
      "type": {
        "coding": [
          {
            "code": "ACSN",
            "system": "http://terminology.hl7.org/CodeSystem/v2-0203",
            "userSelected": "True"
          }
        ]
      },
      "use": "usual",
      "value": "4816522"
    }
  ],
  "multipleBirthBoolean": "False",
  "resourceType": "Patient"
}
```
In order to upload resource to a server, creating Bundle resource containing all of the resources that you want to upload is necessary.
Bundle contains list of Entry resources, where each Entry resource represents specific resource(for example Patient resource).
Here is a example how to create Bundle resource containing the Patient resource made earlier:

```python
from fhir_biobank.bundle import Bundle, Entry

fullURL_patient_resource = "https://example.com/patient/0"
shortURL_patient_resource = "patient/0"
entry = Entry(patient, fullURL_patient_resource, shortURL_patient_resource)
entries = [entry]
bundle_id = "424242"
bundle = Bundle(bundle_id, entries)
```
fabrique-actor 5.0.6
Fabrique actor transport layer engine
License: MIT
Keywords: kafka

fabrique-actor
==============

fabrique kafka transport layer

Install this lib
----------------

``pip3 install fabrique-actor``

Create new actor
----------------

1. Create empty git project and clone it to your local machine
2. Run ``actor_boilerplate.py %actor_type%`` in your project directory
   (``actor_boilerplate.py -h`` to show all supported actor types)
3. Edit files
4. Stage, commit, push, ``git tag %version_str% && git push --tags``