PDBeCif 1.3.4

A lightweight pure python package for reading, writing and manipulating mmCIF files distributed by the wwPDB

Copyright [2013] EMBL - European Bioinformatics Institute
Licensed under the Apache License, Version 2.0 (the
"License"); you may not use this file except in
compliance with the License. You may obtain a copy of
the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing,
software distributed under the License is distributed on
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
KIND, either express or implied. See the License for the
specific language governing permissions and limitations
under the License.

Description: # PDBeCIF
Protein Data Bank in Europe (PDBe; http://pdbe.org) mmCif/CIF/STAR parser and API

used to work with STAR, CIF, and mmCIF formatted files. The package
contains modules for accessing mmCIF data in different ways depending
on the type of task required.

Typical usage often looks like this:

```python
from mmCif import *
from mmcifIO import mmcifIO
```

## Reading from a file

### INPUT: Any STAR/CIF/mmCIF file, OUTPUT: CifFile object
```python
cfr = mmcifIO.CifFileReader(input='dictionary')
cif_file = cfr.read(os.path.join(<your_path>, "usage-example.cif"), output='cif_file')
print "CifFile:", cif_file
```

## Writing to a file

### INPUT: CifFile object
```python
# create a file writer
cff = mmcifIO.CifFileWriter(os.path.join(<your_path>, "cif_output_test.cif"))
# write the file
cff.write(cif_file)
```


## Using a CifFile object

Using the CifFile object to access, edit and update mmCIF data.
The following examples use a CifFile object with roughly the following structure.

Data are manipulated using the accessors and mutators provided:

NB: See the Test suite in mmCif.test for more examples

### Example 1 - Working with CifFile

```python
print "DataBlock ids:", cif_file.getDataBlockIds() #List all datablock ids
print "DataBlock objects:", cif_file.getDataBlocks() #List all datablock objects
data_block_1 = cif_file.getDataBlock("TEST_CIF") #Get a specific datablock
data_block_1 = cif_file.getDataBlocks()[0] #Get the first datablock
data_block_2 = cif_file.setDataBlock("BLOCK_2") # Create another empty datablock
data_block_3 = cif_file.setDataBlock("BLOCK_3") # Create another empty datablock
cif_file.removeChild(data_block_2) # Remove datablock (Method 1 - given object)
cif_file.removeChild("BLOCK_3") # Remove datablock (Method 2 - given ID)
print "RECYCLED DATABLOCKS:", cif_file.recycleBin # Removed objects are stored in a recycle bin
```

### Example 2 - Working with DataBlock

NB: Category and SaveFrame are handled in the same manner

```python
data_block_1 = cif_file.getDataBlock("TEST_CIF") #Get a specific datablock
data_block_4 = cif_file.setDataBlock("BLOCK_4") # Create another empty datablock
data_block_5 = cif_file.setDataBlock("BLOCK_5") # Create another empty datablock
data_block_5.getId() # Get the datablock ID
data_block_5.updateId("BLOCK_5.1") # Change the datablock ID
print "Category ids:", data_block_1.getCategoryIds() #List all category ids
print "Category objects:", data_block_1.getCategories() #List all category objects
category_1 = data_block_1.getCategory("_test_keyword") #Get a specific category
category_2 = data_block_4.setCategory("CATEGORY_2") #Create an empty category
category_3 = data_block_4.setCategory("CATEGORY_3") #Create an empty category
data_block_4.removeChild(category_2) # Remove category (Method 1 - given object)
data_block_4.removeChild("CATEGORY_3") # Remove category (Method 2 - given ID)
data_block_5.remove() # Remove datablock from CifFile
print "RECYCLED CATEGORIES:", data_block_4.recycleBin # Removed objects are stored in a recycle bin
```

### Example 3 - Working with Category

```python
category_1 = data_block_1.getCategory("_test_keyword") #Get a specific category
category_4 = data_block_4.setCategory("CATEGORY_4") # Create another empty category
category_5 = data_block_4.setCategory("CATEGORY_5") # Create another empty category
print "Item names:", category_1.getItemNames() #List all item names
print "Item objects:", category_1.getItems() #List all item objects
item_1 = category_1.getItem("field_1") #Get a specific item
item_2 = category_4.setItem("ITEM_2") #Create an empty item
item_3 = category_4.setItem("ITEM_3") #Create an empty item
category_4.removeChild(item_2) # Remove item (Method 1 - given object)
category_4.removeChild("ITEM_3") # Remove item (Method 2 - given ID)
category_5.remove() # Remove category from DataBlock
print "RECYCLED ITEMS:", category_4.recycleBin # Removed objects end up in the recycle bin
```

### Example 4 - Working with Item

```python
item_1 = category_1.getItem("field_1") #Get a specific item
item_4 = category_4.setItem("ITEM_4") # Create another empty item
item_5 = category_4.setItem("ITEM_5") # Create another empty item
print "Value (raw):", item_1.getRawValue() #Get raw item value (Method 1 - using accessor)
print "Value (raw):", item_1.value #Get raw item value (Method 2 - using attribute)
print "Value (formated):", item_1.getFormattedValue() #Get the formated value (for file export)
item_4.setValue("VALUE_2") #Set the item value
item_5.setValue([9, 8, 7, 6, 5]) #Set the item value
item_5.remove() # Remove item from Category
print "RECYCLED ITEMS:", category_4.recycleBin # Removed objects end up in the recycle bin
```
### Example 5 - Method chaining
For every object the setXXXX() method always returns the this you are
trying to set. If no object is present it creates a new one and returns it.
setXXXX() can therefor be used as both accessor and mutator
```python

cif_file.setDataBlock("BLOCK_6").setCategory("CATEGORY_6").setItem("ITEM_6").setValue("VALUE_6")
```

## Installation

### pip

pip install git+http://github.com/glenveegee/PDBeCIF.git

Optionally, you can specify a tag/branch. For example:

pip install git+http://github.com/glenveegee/PDBeCIF.git@v1.3.4

### Manual

You can also simply download a release from https://github.com/glenveegee/PDBeCIF/releases and copy it to your Python library path.


Keywords: STAR CIF mmCIF PDB PDBe parsing parser API
Platform: UNKNOWN
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Operating System :: POSIX
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics