Skip to main content

iRODS is an open-source distributed data management system. This is a client API implemented in python.

Currently supported:

  • Establish a connection to iRODS, authenticate

  • Implement basic Gen Queries (select columns and filtering)

  • Support more advanced Gen Queries with limits, offsets, and aggregations

  • Query the collections and data objects within a collection

  • Execute direct SQL queries

  • Execute iRODS rules

  • Support read, write, and seek operations for files

  • Delete data objects

  • Create collections

  • Delete collections

  • Rename data objects

  • Rename collections

  • Query metadata for collections and data objects

  • Add, edit, remove metadata

  • Replicate data objects to different resource servers

  • Connection pool management

  • Implement gen query result sets as lazy queries

  • Return empty result sets when CAT_NO_ROWS_FOUND is raised

  • Manage permissions

  • Manage users and groups

  • Manage resources

  • GSI authentication

  • Unicode strings

  • Python 2.7, 3.4 or newer

Installing

PRC requires Python 2.7 or 3.4+. To install with pip:

pip install git+git://github.com/irods/python-irodsclient.git

Uninstalling

pip uninstall python-irodsclient

Establishing a connection

>>> from irods.session import iRODSSession
>>> sess = iRODSSession(host='localhost', port=1247, user='rods', password='rods', zone='tempZone')

If you’re an administrator acting on behalf of another user:

>>> from irods.session import iRODSSession
>>> sess = iRODSSession(host='localhost', port=1247, user='rods', password='rods', zone='tempZone',
           client_user='another_user', client_zone='another_zone')

If no client_zone is provided, the zone parameter is used in its place.

Working with collections

>>> coll = sess.collections.get("/tempZone/home/rods")

>>> coll.id
45798

>>> coll.path
/tempZone/home/rods

>>> for col in coll.subcollections:
>>>   print col
<iRODSCollection /tempZone/home/rods/subcol1>
<iRODSCollection /tempZone/home/rods/subcol2>

>>> for obj in coll.data_objects:
>>>   print obj
<iRODSDataObject /tempZone/home/rods/file.txt>
<iRODSDataObject /tempZone/home/rods/file2.txt>

Create a new collection:

>>> coll = sess.collections.create("/tempZone/home/rods/testdir")
>>> coll.id
45799

Working with data objects (files)

Create a new data object:

>>> obj = sess.data_objects.create("/tempZone/home/rods/test1")
<iRODSDataObject /tempZone/home/rods/test1>

Get an existing data object:

>>> obj = sess.data_objects.get("/tempZone/home/rods/test1")
>>> obj.id
12345

>>> obj.name
test1
>>> obj.collection
<iRODSCollection /tempZone/home/rods>

>>> for replica in obj.replicas:
...     print replica.resource_name
...     print replica.number
...     print replica.path
...     print replica.status
...
demoResc
0
/var/lib/irods/Vault/home/rods/test1
1

Reading and writing files

PRC provides file-like objects for reading and writing files

>>> obj = sess.data_objects.get("/tempZone/home/rods/test1")
>>> with obj.open('r+') as f:
...   f.write('foo\nbar\n')
...   f.seek(0,0)
...   for line in f:
...      print line
...
foo
bar

Working with metadata

>>> obj = sess.data_objects.get("/tempZone/home/rods/test1")
>>> print obj.metadata.items()
[]

>>> obj.metadata.add('key1', 'value1', 'units1')
>>> obj.metadata.add('key1', 'value2')
>>> obj.metadata.add('key2', 'value3')
>>> print obj.metadata.items()
[<iRODSMeta (key1, value1, units1, 10014)>, <iRODSMeta (key2, value3, None, 10017)>,
<iRODSMeta (key1, value2, None, 10020)>]

>>> print obj.metadata.get_all('key1')
[<iRODSMeta (key1, value1, units1, 10014)>, <iRODSMeta (key1, value2, None, 10020)>]

>>> print obj.metadata.get_one('key2')
<iRODSMeta (key2, value3, None, 10017)>

>>> obj.metadata.remove('key1', 'value1', 'units1')
>>> print obj.metadata.items()
[<iRODSMeta (key2, value3, None, 10017)>, <iRODSMeta (key1, value2, None, 10020)>]

Performing general queries

>>> from irods.session import iRODSSession
>>> from irods.models import Collection, User, DataObject
>>> sess = iRODSSession(host='localhost', port=1247, user='rods', password='rods', zone='tempZone')
>>> results = sess.query(DataObject.id, DataObject.name, DataObject.size, \
User.id, User.name, Collection.name).all()
>>> print results
+---------+-----------+-----------+---------------+--------------------------------+-----------+
| USER_ID | USER_NAME | D_DATA_ID | DATA_NAME     | COLL_NAME                      | DATA_SIZE |
+---------+-----------+-----------+---------------+--------------------------------+-----------+
| 10007   | rods      | 10012     | runDoxygen.rb | /tempZone/home/rods            | 5890      |
| 10007   | rods      | 10146     | test1         | /tempZone/home/rods            | 0         |
| 10007   | rods      | 10147     | test2         | /tempZone/home/rods            | 0         |
| 10007   | rods      | 10148     | test3         | /tempZone/home/rods            | 8         |
| 10007   | rods      | 10153     | test5         | /tempZone/home/rods            | 0         |
| 10007   | rods      | 10154     | test6         | /tempZone/home/rods            | 8         |
| 10007   | rods      | 10049     | .gitignore    | /tempZone/home/rods/pycommands | 12        |
| 10007   | rods      | 10054     | README.md     | /tempZone/home/rods/pycommands | 3795      |
| 10007   | rods      | 10052     | coll_test.py  | /tempZone/home/rods/pycommands | 658       |
| 10007   | rods      | 10014     | file_test.py  | /tempZone/home/rods/pycommands | 465       |
+---------+-----------+-----------+---------------+--------------------------------+-----------+

Query with aggregation(min, max, sum, avg, count):

>>> results = sess.query(DataObject.owner_name).count(DataObject.id).sum(DataObject.size).all()
>>> print results
+--------------+-----------+-----------+
| D_OWNER_NAME | D_DATA_ID | DATA_SIZE |
+--------------+-----------+-----------+
| rods         | 10        | 10836     |
+--------------+-----------+-----------+

Release files for python-irodsclient 0.6.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for python-irodsclient 0.6.0
File Size Uploaded
python-irodsclient-0.6.0.tar.gz 70.9 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for python-irodsclient 0.6.0
File Interpreter ABI Platform
python_irodsclient-0.6.0-py2.py3-none-any.whl Python 3, Python 2 none any Details

Total release size: 154.1 kB

Release files / python-irodsclient-0.6.0.tar.gz

Download URL python-irodsclient-0.6.0.tar.gz
Size 70.9 kB
Tags Source
SHA-256 checksum
How to use checksums
ca4fb5c390744420d2265043796a8fbb5f9ca1e3ac2c19e13e3072fc52161daf
BLAKE2b-256 checksum
How to use checksums
6eac7c35555b3cbb1662efe765ba33ec0d521bda700deac9b4fe35da4de3b904
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No

Release files / python_irodsclient-0.6.0-py2.py3-none-any.whl

Download URL python_irodsclient-0.6.0-py2.py3-none-any.whl
Size 83.2 kB
Tags Python 2 Python 3
SHA-256 checksum
How to use checksums
042a1df5953a33e4bc0ff720f54333e0513c10006f39e1e8c8718a4c6c916e03
BLAKE2b-256 checksum
How to use checksums
6add8863d5a98ec5d96629fc6779832dbd5f383fdf589fd3332be519ca94b287
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page