Python utilities for PDBx/mmCIF storage model

2.0.1 · active · verified Tue Apr 14

mmcif-pdbx provides a pure Python interface for working with PDBx/mmCIF files, emphasizing simplicity. It allows parsing and serialization of macromolecular crystallographic information files. The library is derived from Python examples provided by the wwPDB and is currently at version 2.0.1, with releases occurring periodically to add features and address issues.

Warnings

breaking Version 1.0.0 introduced significant API changes, breaking compatibility with versions 0.*. These changes include PEP8-compliant class and function naming and simplification of the module structure.
Fix: Update code to reflect PEP8 naming conventions and the revised module structure. Consult the 1.0.0 release notes and documentation for specific changes.
gotcha This `mmcif-pdbx` package provides a pure Python interface. For higher performance or more comprehensive features, especially those involving C/C++ acceleration for I/O, consider `rcsb/py-mmcif` (PyPI: `mmcif`), which is described as the 'canonical mmCIF Python package'.
Fix: Evaluate your project's performance and feature requirements. If `mmcif-pdbx`'s pure Python approach is sufficient, continue using it. If not, consider migrating to `rcsb/py-mmcif`.

Install

pip install mmcif-pdbx Install stable version

Imports

PdbxReader
```
from pdbx.reader import PdbxReader
```
For reading mmCIF files.
PdbxWriter
```
from pdbx.writer import PdbxWriter
```
For writing mmCIF files.
DataContainer
```
from pdbx.containers import DataContainer
```
Represents a data block within an mmCIF file.
load
```
from pdbx import load
```
Convenience function for parsing a CIF file object.
loads
```
from pdbx import loads
```
Convenience function for parsing a CIF string.
dump
```
from pdbx import dump
```
Convenience function for writing DataContainer objects to a CIF file object.
dumps
```
from pdbx import dumps
```
Convenience function for serializing DataContainer objects to a CIF string.

Quickstart

This quickstart demonstrates how to parse an mmCIF string, access data within categories, and serialize modified data back to an mmCIF string using the `loads` and `dumps` utility functions, and interacting with `DataContainer` and `DataCategory` objects.

import io
from pdbx import loads, dumps, DataCategory, DataContainer

# Example mmCIF data as a string
mmcif_data = '''
data_testblock
_entry.id test
loop_
_atom_site.id
_atom_site.type_symbol
_atom_site.label_atom_id
1 C CA
2 O O
'''

# Parse the mmCIF string
data_containers = loads(mmcif_data)

# Access data (assuming one data block)
if data_containers:
    data_block = data_containers[0]
    print(f"Data block ID: {data_block.name}")

    # Access a category
    atom_site_category = data_block.getObj('atom_site')
    if atom_site_category:
        print("\nAtom Site Category:")
        for i in range(atom_site_category.getRowCount()):
            atom_id = atom_site_category.getValue('id', i)
            atom_type = atom_site_category.getValue('type_symbol', i)
            print(f"  ID: {atom_id}, Type: {atom_type}")
    else:
        print("Atom_site category not found.")

    # Modify data (example: add a new item to the entry category)
    entry_category = data_block.getObj('entry')
    if entry_category:
        entry_category.setValue('new_item', 0, 'new_value')

    # Serialize the modified data back to a string
    modified_mmcif_data = dumps(data_containers)
    print("\nModified mmCIF data:\n", modified_mmcif_data)

else:
    print("No data containers found.")

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