BBO-Reitveld Python Client

A Python client library for the BBO-Reitveld—a server designed to automate Rietveld analysis of powder X-ray diffraction (XRD) measurement data. This client offers a programmatic interface for synchronous communication with the server, allowing users to submit analysis jobs, monitor their progress, and retrieve results through code.

✨ Features

• Submit analysis tasks to the server for automated Reitveld refinements
• Download analysis results
• Create new user accounts

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📦 Requirements

• Python 3.9 or higher
• Dependencies (automatically installed):
  • requests
  • pydantic
  • python-abc
  • pandas (optional, for getting Optuna data)
  • parsexml (optional, for parsing XML type measurement file)

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🚀 Installation

Install directly from the GitHub repository:

pip install git+https://git@github.com:quantumbeam/bborclient.git

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⚡ Usage

Create an account

from bbor_client import BBORClient
client = BBORClient()
client.create_user(
    username = 'your_username',
    password = 'your_password',
    group_id = 'your_group_id',
)

Start a Study of BBO-Rietveld analysis

from bbor_client import BBORClient
client = BBORClient('your_username', 'your_password')

# Start a BBO-Rietveld study
client.post_bborietveld_study_task(
    study_name_base = 'study_name',
    measurementfile = '/path/xrd_data.csv',
    ciffiles = '/path/NaCl.cif',
    prmfile = '/path/XC-BB.instprm',
)

# Check progress of Study tasks
client.ask_task_queue_status(study_id)

Get results of analyses

from bbor_client import BBORClient
client = BBORClient('your_username', 'your_password')

# Get a Study
client.get_study(study_id)

# Get a list of all Studies of your group
client.find_studies()

# Get all Studies you performed
client.find_my_studies()

# Get Studies where study_name matches a specified pattern
pattern = '^hoge' # Use regular expression
query = {'study_name': {'$regex': pattern}}
client.find_studies(query)

# Get Studies of a specified structure model
query = {
  'samples': {
    '$elemMatch': {
      'phases': {
        '$elemMatch': {'name': 'Y2O3'}
      }
    }
  }
}
client.find_studies(query)

# Get Studies which started earlier than 3 days ago and later than 7 days ago
from datetime import datetime, timedelta, timezone
tz = timezone(timedelta(hours=9))
now = datetime.now(tz=tz).astimezone(timezone.utc)
threedaysago = now - timedelta(days=3)
sevendaysago = now - timedelta(days=7)
query = {
    'start_at': {
      '$lt': threedaysago.isoformat(),
      '$gt': sevendaysago.isoformat(),
    }
}
client.find_studies(query)

# Get a Trial
client.get_study(trial_id)

# Get all Trials of your group
client.find_trials()

# Get all Trials of a Study
client.get_study_trials(study_id)

# Get best Trials of a Study
client.get_best_trials(study_id)

# Get a Refine
client.get_refine(refine_id)

# Get all Refines of your group
client.find_refines()

🌈 Planned Features

• Implement the native methods of MongoDB such as find_one, aggregation pipeline, sort, projection.
• Limit (unintended) large-scale data requests

📄 Terms and Conditions

TBD

🚘️ License

TBD