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annotate planemo/lib/python3.7/site-packages/bioblend/galaxy/objects/galaxy_instance.py @ 1:56ad4e20f292 draft

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"planemo upload commit 6eee67778febed82ddd413c3ca40b3183a3898f1"
author guerler
date Fri, 31 Jul 2020 00:32:28 -0400
parents d30785e31577
children
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1 """
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2 A representation of a Galaxy instance based on oo wrappers.
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3 """
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4
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5 import time
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6
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7 import bioblend
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8 import bioblend.galaxy
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9 from bioblend.galaxy.datasets import TERMINAL_STATES
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10 from . import client
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11
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12
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13 def _get_error_info(hda):
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14 msg = hda.id
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15 try:
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16 msg += ' (%s): ' % hda.name
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17 msg += hda.wrapped['misc_info']
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18 except Exception: # avoid 'error while generating an error report'
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19 msg += ': error'
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20 return msg
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21
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22
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23 class GalaxyInstance(object):
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24 """
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25 A representation of an instance of Galaxy, identified by a URL and
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26 a user's API key.
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27
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28 :type url: str
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29 :param url: a FQDN or IP for a given instance of Galaxy. For example:
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30 ``http://127.0.0.1:8080``
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31
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32 :type api_key: str
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33 :param api_key: user's API key for the given instance of Galaxy, obtained
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34 from the Galaxy web UI.
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35
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36 This is actually a factory class which instantiates the entity-specific
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37 clients.
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38
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39 Example: get a list of all histories for a user with API key 'foo'::
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40
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41 from bioblend.galaxy.objects import *
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42 gi = GalaxyInstance('http://127.0.0.1:8080', 'foo')
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43 histories = gi.histories.list()
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44 """
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45 def __init__(self, url, api_key=None, email=None, password=None, verify=True):
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46 self.gi = bioblend.galaxy.GalaxyInstance(url, api_key, email, password, verify)
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47 self.log = bioblend.log
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48 self.histories = client.ObjHistoryClient(self)
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49 self.libraries = client.ObjLibraryClient(self)
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50 self.workflows = client.ObjWorkflowClient(self)
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51 self.tools = client.ObjToolClient(self)
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52 self.jobs = client.ObjJobClient(self)
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53
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54 def _wait_datasets(self, datasets, polling_interval, break_on_error=True):
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55 """
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56 Wait for datasets to come out of the pending states.
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57
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58 :type datasets: :class:`~collections.Iterable` of
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59 :class:`~.wrappers.Dataset`
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60 :param datasets: datasets
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61
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62 :type polling_interval: float
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63 :param polling_interval: polling interval in seconds
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64
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65 :type break_on_error: bool
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66 :param break_on_error: if ``True``, raise a RuntimeError exception as
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67 soon as at least one of the datasets is in the 'error' state.
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68
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69 .. warning::
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70
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71 This is a blocking operation that can take a very long time.
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72 Also, note that this method does not return anything;
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73 however, each input dataset is refreshed (possibly multiple
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74 times) during the execution.
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75 """
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76 def poll(ds_list):
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77 pending = []
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78 for ds in ds_list:
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79 ds.refresh()
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80 if break_on_error and ds.state == 'error':
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81 raise RuntimeError(_get_error_info(ds))
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82 if not ds.state:
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83 self.log.warning("Dataset %s has an empty state", ds.id)
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84 elif ds.state not in TERMINAL_STATES:
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85 self.log.info("Dataset {0.id} is in non-terminal state {0.state}".format(ds))
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86 pending.append(ds)
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87 return pending
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88
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89 self.log.info('Waiting for datasets')
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90 while datasets:
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91 datasets = poll(datasets)
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92 time.sleep(polling_interval)