Merge pull request #104 from matthiaskoenig/develop

pkdb-v0.2.6

README.md

@@ -1,10 +1,12 @@
+[![DOI](https://zenodo.org/badge/131752339.svg)](https://zenodo.org/badge/latestdoi/131752339)
+
 # PKDB - Pharmacokinetics database
 
 <b><a href="https://orcid.org/0000-0002-4588-4925" title="0000-0002-4588-4925"><img src="./docs/images/orcid.png" height="15"/></a> Jan Grzegorzewski</b>
 and
 <b><a href="https://orcid.org/0000-0003-1725-179X" title="https://orcid.org/0000-0003-1725-179X"><img src="./docs/images/orcid.png" height="15" width="15"/></a> Matthias König</b>
 
-Database and web interface for storing pharmacokinetics information including
+Database and web interface for storing (pharmaco-)kinetics information including
 - study data (publication data)
 - trial design
 - subjects information
@@ -14,102 +16,70 @@ Database and web interface for storing pharmacokinetics information including
 - timecourse data
 
 <img src="./docs/images/data_extraction.png" width="600"/>
-Figure 1: Overview over data extraction.
-
-## Access
-http://localhost:8000/api/v1/
-http://localhost:8000/api/v1/studies/17955229/
-
+Figure 1: Overview over data extraction and curation work flow.
 
+# Installation
+The database with backend and frontend is available as docker container for local installation.
 
-
-## Data model
-Pharmacokinetics data is a special type of experimental data.
-Pharmacokinetics data like clearance, halflife, ... (with units and error measurements) are either directly reported in publications
-or can be calculated from time course data.
-* the reported value (mean, median) as well as the error terms associated with the values (SD, SE, CV, Range) can vary
-* Important information is the number of subjects (n) underlying the measurement, which is required to convert between different error
-measurements.
-
-# Setup & Installation
 ## Requirements
 - [Docker](https://docs.docker.com/docker-for-mac/install/)
 - Python3.6
 
-## Virtual Environment
-Setting up a virtual environment
-```
-mkvirtualenv pkdb --python=python3.6
-(pkdb) pip install -r requirements.txt
+## Build docker container
+To build the dev server for local development:
+```bash
+git clone https://github.com/matthiaskoenig/pkdb.git
+cd pkdb
+docker-compose up build
 ```
-add your virtual environment to jupyter kernels:
+To update an existing version use
+```bash
+docker-compose down
+./remove_migrations.sh
+docker-compose up build
 ```
-(pkdb) ipython kernel install --user --name=pkdb
-``` 
-# Initialize the project
-
-Start the dev server for local development:
+To run an existing version use
 ```bash
 docker-compose up
 ```
 
-Create a superuser to login to the admin:
+PKDB can than be accessed via the locally running server at  
+http://localhost:8000/api/v1/  
+
+To run commands inside the docker container use
 ```bash
-docker-compose run --rm web ./manage.py createsuperuser
+docker-compose run --rm web [command]
 ```
-
-# Update after code change
+For instance create a superuser to login to the admin:
+```bash
+docker-compose run --rm web ./manage.py createsuperuser
 ```
-# reset migrations
-sudo find . -path "*/migrations/*.py" -not -name "__init__.py" -delete && sudo find . -path "*/migrations/*.pyc"  -delete && sudo rm -r media/study/
-
-# rebuild container
-docker-compose down
-docker-compose up --build
+or to run migrations
+```bash
+docker-compose run --rm web python manage.py makemigrations
 ```
 
-
-# Fill database
-From console use the following
+## Fill database
+The database can be filled via the `fill_database` scripts using curated data folders.
+The curated data is currently not made available, but only accessible via the REST API.
 ```
-workon pkdb
-(pkdb) pip install -r requirements.txt --upgrade
 (pkdb) python ./pkdb_app/data_management/fill_database.py
 ```
 
-
-# Connect database pycharm
-```
-DataSource -> postgres
-```
-Use port defined in `docker-compose.yml` (5433), database name and password in `docker-compose.yml`
-
-# Local Development
-Start the dev server for local development:
-
-```bash
-docker-compose up
-```
-Run a command inside the docker container:
-
-```bash
-docker-compose run --rm web [command]
+## Python (Virtual Environment)
+Setting up a virtual environment to interact with the data base via python
 ```
-Example:
-
+mkvirtualenv pkdb --python=python3.6
+(pkdb) pip install -r requirements.txt
 ```
- docker-compose run --rm web python manage.py makemigrations
+add your virtual environment to jupyter kernels:
 ```
+(pkdb) ipython kernel install --user --name=pkdb
+``` 
 
-----
-# Client
-check out ./client/README.md.
-## Requirements
-- node.js
-- npm
-- vue.js
-
-
+## Frontend 
+Documentation of the `vue.js` frontend is available in
+./pkdb_client/README.md
 
 
-&copy; 2018 Jan Grzegorzewski & Matthias König.
+&copy; 2017-2018 Jan Grzegorzewski & Matthias König.

pkdb_app/_version.py

@@ -1,4 +1,4 @@
 """
 Definition of version string.
 """
-__version__ = "0.2.5"
+__version__ = "0.2.6"

pkdb_app/subjects/serializers.py

@@ -154,6 +154,9 @@ def group_to_internal_value(group, study_sid):
             except ObjectDoesNotExist:
                 msg = f'group: {group} in study: {study_sid} does not exist'
                 raise serializers.ValidationError(msg)
+        else:
+            msg = {"group": f'group is required on individual',"detail":group}
+            raise serializers.ValidationError(msg)
         return group
 
     def to_internal_value(self, data):