Initial commit.

Author: feserm

.gitignore

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+dist/
+__pycache__/
+.pytest_cache/

CITATIONS.cff

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+cff-version: 1.2.0
+title: pyBrAPI
+message: >-
+  If you use this software, please cite it using the
+  metadata from this file.
+type: software
+authors:
+  - given-names: Manuel
+    family-names: Feser
+    email: [email protected]
+    name-particle: Manuel
+    affiliation: >-
+      Leibniz Institute of Plant Genetics and Crop Plant
+      Research
+    orcid: 'https://orcid.org/0000-0001-6546-1818'
+repository-code: 'https://github.com/IPK-BIT/pyBrapi'
+abstract: >-
+  pyBrAPI is a Python package that provides convenient
+  access to data from BrAPI servers. It simplifies
+  interacting with BrAPI endpoints by handling REST requests
+  and responses, and returns data typed into Python data
+  models.
+keywords:
+  - BrAPI
+  - python
+license: MIT
+version: 0.1.0

LICENSE

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+MIT License
+
+Copyright (c) 2025 Manuel Feser <[email protected]>
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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+# pyBrAPI
+
+## Project Overview
+pyBrAPI is a Python package that provides convenient access to data from BrAPI servers. It simplifies interacting with BrAPI endpoints by handling REST requests and responses, and returns data typed into data models.
+
+## Setup and Installation
+Download the release from this Github repository. Then install the package using `pip`:
+
+```
+pip install dist/pybrapi-0.1.0-py3-none-any.whl
+```
+
+## Usage Instructions
+### Connect to server
+```py
+from pybrapi import BrAPI
+
+server = BrAPI('https://test-server.brapi.org/brapi/v2/')
+```
+
+### Request Germplasm
+```py
+response = server.get_germplasm(germplasmDbId="germplasm1")
+```
+
+Similar functions are provided for:
+- trials
+- studies
+- observations
+- observation units
+- observation variables
+
+### Request Observations Tables
+Additionally for observations, users can receive the data in a pandas data frame.
+```py
+df = server.get_observations_as_dataframe(observationVariableDbId="variable1")
+```
+
+
+## Features
+- Simplified interface for querying BrAPI endpoints
+- Typed data models for returned data
+- Handles authentication and connection management
+- Supports various BrAPI operations like retrieving germplasm, observations, trials, etc.
+
+## License
+- The project is licensed under [MIT License](LICENSE)
+
+## Additional Resources
+- [BrAPI](https://brapi.org)
+- [BrAPI Specification](https://brapi.org/specification)

poetry.lock

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+from dataclasses import dataclass
+from pybrapi.authentication import AbstractAuth
+from pybrapi.modules import core, phenotyping, germplasm
+
+@dataclass
+class BrAPI:
+    base_url: str = "https://test-server.brapi.org/brapi/v2"
+    auth: AbstractAuth|None = None
+    
+    __core__: core.Core = core.Core()
+    __germplasm__: germplasm.Germplasm = germplasm.Germplasm()
+    __phenotyping__: phenotyping.Phenotyping = phenotyping.Phenotyping()
+    
+    def get_germplasm(self, **kwargs):
+        return self.__germplasm__.get_germplasm(self.base_url, self.auth, **kwargs)
+    
+    def get_observations(self, **kwargs):
+        return self.__phenotyping__.get_observations(self.base_url, self.auth, **kwargs)
+    
+    def get_observations_as_dataframe(self, **kwargs):
+        return self.__phenotyping__.get_observations_as_dataframe(self.base_url, self.auth, **kwargs)
+    
+    def get_observation_units(self, **kwargs):
+        return self.__phenotyping__.get_observation_units(self.base_url, self.auth, **kwargs)
+    
+    def get_observation_variables(self, **kwargs):
+        return self.__phenotyping__.get_observation_variables(self.base_url, self.auth, **kwargs)
+    
+    def get_studies(self, **kwargs):
+        return self.__core__.get_studies(self.base_url, self.auth, **kwargs)
+    
+    def get_trials(self, **kwargs):
+        return self.__core__.get_trials(self.base_url, self.auth, **kwargs)
+    

pybrapi/__init__.py

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+import requests
+
+def __collect_results__(url, headers, params):
+    if "pageSize" not in params:
+        params["pageSize"] = 1000
+    if "page" not in params:
+        params["page"] = 0
+        
+    response = __get_page__(url, headers, params)
+    # print(f'collecting page {params["page"]+1}/{response["metadata"]["pagination"]["totalPages"]}')
+    if "headerRow" in response["result"]:
+        result = response["result"]
+        while params["page"] < response["metadata"]["pagination"]["totalPages"]-1:
+            params["page"] += 1
+            result["data"].extend(__get_page__(url, headers, params)["result"]["data"])
+            # print(f'collecting page {params["page"]+1}/{response["metadata"]["pagination"]["totalPages"]}')
+    elif "data" in response["result"]:
+        result: list = response["result"]["data"]
+        while params["page"] < response["metadata"]["pagination"]["totalPages"]-1:
+            params["page"] += 1
+            result.extend(__get_page__(url, headers, params)["result"]["data"])
+    else:
+        result = response["result"]    
+    return result
+                
+def __get_page__(url, headers, params):
+    response = requests.get(url, headers=headers, params=params)
+    response.raise_for_status()
+    return response.json()

pybrapi/__utils__/__collector__.py

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+from dataclasses import dataclass
+from base64 import b64encode
+import requests
+
+@dataclass
+class AbstractAuth:
+    def get_auth_string(self):
+        raise NotImplementedError("get_auth_string not implemented")
+    
+@dataclass
+class BasicAuth(AbstractAuth):
+    username: str
+    password: str
+    
+    def get_auth_string(self):
+        return f"Basic {b64encode(f'{self.username}:{self.password}'.encode()).decode()}"
+    
+@dataclass
+class OIDCAuth(AbstractAuth):
+    oidc_url: str
+    oidc_details: dict
+    __token__: str = None
+    __refresh_token__: str = None
+    
+    def __init__(self, oidc_url: str, oidc_details: dict):
+        self.oidc_url = oidc_url
+        self.oidc_details = oidc_details
+        self.__token__ = self.get_token()
+    
+    def get_token(self):
+        response = requests.post(f"{self.oidc_url}/token", data=self.oidc_details)
+        response.raise_for_status()
+        self.__refresh_token__ = response.json()["refresh_token"]
+        return response.json()["access_token"]
+    
+    def get_auth_string(self):
+        return f"Bearer {self.__token__}"
+    
+    def refresh(self):
+        self.__token__ = self.get_token()

pybrapi/authentication.py

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+from pydantic import BaseModel
+from pybrapi.models.subclasses import Contact, DataLink, DatasetAuthorship, EnvironmentalParameter, ExperimentalDesign, ExternalReference, GrowthFacility, LastUpdate, ObservationUnitHierarchyLevel, Publication
+
+class Trial(BaseModel):
+    active: bool|None = None
+    additionalInfo: dict|None = None
+    commonCropName: str|None = None
+    contacts: list[Contact]|None = None
+    datasetAuthorships: list[DatasetAuthorship]|None = None
+    documentationURL: str|None = None
+    endDate: str|None = None
+    externalReferences: list[ExternalReference]|None = None
+    programDbId: str|None = None
+    programName: str|None = None
+    publications: list[Publication]|None = None
+    startDate: str|None = None
+    trialDbId: str
+    trialDescription: str|None = None
+    trialName: str
+    trialPUI: str|None = None
+
+class Study(BaseModel):
+    active: bool|None = None
+    additionalInfo: dict|None = None
+    commonCropName: str|None = None
+    contacts: list[Contact]|None = None
+    culturalPractices: str|None = None
+    dataLinks: list[DataLink]|None = None
+    documentationURL: str|None = None
+    endDate: str|None = None
+    environmentParameters: list[EnvironmentalParameter]|None = None
+    experimentalDesign: ExperimentalDesign|None = None
+    externalReferences: list[ExternalReference]|None = None
+    growthFacility: GrowthFacility|None = None
+    lastUpdate: LastUpdate|None = None
+    license: str|None = None
+    locationDbId: str|None = None
+    locationName: str|None = None
+    observationLevels: list[ObservationUnitHierarchyLevel]|None = None
+    observationUnitsDescription: str|None = None
+    observationVariableDbIds: list[str]|None = None
+    seasons: list[str]|None = None
+    startDate: str|None = None
+    studyCode: str|None = None
+    studyDbId: str
+    studyDescription: str|None = None
+    studyName: str
+    studyPUI: str|None = None
+    studyType: str|None = None
+    trialDbId: str|None = None
+    trialName: str|None = None