hubstorage 0.19.1

Client interface for Scrapinghub HubStorage

Note

This module is experimental and its API may change without previous notice.

Overview

This Python library can be used for interaction with spiders, jobs and scraped data through storage.scrapinghub.com endpoints, see Scrapinghub API.

Requirements

• requests: http://pypi.python.org/pypi/requests

Testing

Running the tests require the hubstorage backend to be running, and the python responses library (see tox.ini).

Usage

First, use your API key for authorization:

>>> from hubstorage import HubstorageClient
>>> hс = HubstorageClient(auth='apikey')
>>> hc.server_timestamp()
1446222762611

Project

To get project settings or jobs summary:

>>> project = hc.get_project('1111111')
>>> project.settings['botgroups']
[u'botgroup1', ]
>>> project.jobsummary()
{u'finished': 6,
 u'has_capacity': True,
 u'pending': 0,
 u'project': 1111111,
 u'running': 0}

Spider

To get spider id correlated with its name:

>>> project.ids.spider('foo')
1

To see last jobs summaries:

>>> summaries = project.spiders.lastjobsummary(count=3)

To get job summary per spider:

>>> summary = project.spiders.lastjobsummary(spiderid='1')

Job

Job can be retrieved directly by id (project_id/spider_id/job_id):

>>> job = hc.get_job('1111111/1/1')
>>> job.key
'1111111/1/1'
>>> job.metadata['state']
u'finished'

Creating a new job requires a spider name:

>>> job = hc.push_job(projectid='1111111', spidername='foo')
>>> job.key
'1111111/1/1'

Priority can be between 0 and 4 (from lowest to highest), the default is 2.

To push job from project level with the highest priority:

>>> job = project.push_job(spidername='foo', priority=4)
>>> job.metadata['priority']
4

Running job can be cancelled by calling request_cancel():

>>> job.request_cancel()
>>> job.metadata['cancelled_by']
u'John'

To delete job:

>>> job.purged()
>>> job.metadata['state']
u'deleted'

Job details

Job details can be found in jobs metadata and it’s scrapystats:

>>> job = hc.get_job('1111111/1/1')
>>> job.metadata['version']
u'5123a86-master'
>>> job.metadata['scrapystats']
...
u'downloader/response_count': 104,
u'downloader/response_status_count/200': 104,
u'finish_reason': u'finished',
u'finish_time': 1447160494937,
u'item_scraped_count': 50,
u'log_count/DEBUG': 157,
u'log_count/INFO': 1365,
u'log_count/WARNING': 3,
u'memusage/max': 182988800,
u'memusage/startup': 62439424,
...

Anything can be stored in metadata, here is example how to add tags:

>>> job.metadata.update_metadata({'tags': 'obsolete'})

Jobs

To iterate through all jobs metadata per project (descending order):

>>> jobs_metadata = project.jobq.list()
>>> [j['key'] for j in jobs_metadata]
['1111111/1/3', '1111111/1/2', '1111111/1/1']

Jobq metadata fieldset is less detailed, than job.metadata, but contains few new fields as well. Additional fields can be requested using the jobmeta parameter. If it used, then it’s up to the user to list all the required fields, so only few default fields would be added except requested ones.

>>> metadata = project.jobq.list().next()
>>> metadata.get('spider', 'missing')
u'foo'
>>> jobs_metadata = project.jobq.list(jobmeta=['scheduled_by', ])
>>> metadata = jobs_metadata.next()
>>> metadata.get('scheduled_by', 'missing')
u'John'
>>> metadata.get('spider', 'missing')
missing

By default jobq.list() returns maximum last 1000 results. Pagination is available using the start parameter:

>>> jobs_metadata = project.jobq.list(start=1000)

There are several filters like spider, state, has_tag, lacks_tag, startts and endts. To get jobs filtered by tags:

>>> jobs_metadata = project.jobq.list(has_tag=['new', 'verified'], lacks_tag='obsolete')

To get certain number of last finished jobs per some spider:

>>> jobs_metadata = project.jobq.list(spider='foo', state='finished' count=3)

There are 4 possible job states, which can be used as values for filtering by state:

• pending

• running

• finished

• deleted

Items

To iterate through items:

>>> items = job.items.iter_values()
>>> for item in items:
   # do something, item is just a dict

Logs

To iterate through 10 first logs for example:

>>> logs = job.logs.iter_values(count=10)
>>> for log in logs:
   # do something, log is a dict with log level, message and time keys

Collections

Let’s store hash and timestamp pair for foo spider. Usual workflow with Collections would be:

>>> collections = project.collections
>>> foo_store = collections.new_store('foo_store')
>>> foo_store.set({'_key': '002d050ee3ff6192dcbecc4e4b4457d7', 'value': '1447221694537'})
>>> foo_store.count()
1
>>> foo_store.get('002d050ee3ff6192dcbecc4e4b4457d7')
'1447221694537'
>>> for result in foo_store.iter_values():
   # do something with _key & value pair
>>> foo_store.delete('002d050ee3ff6192dcbecc4e4b4457d7')
>>> foo_store.count()
0