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Fix dumpinvestigation.py example script #164

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2 changes: 2 additions & 0 deletions CHANGES.rst
Original file line number Diff line number Diff line change
Expand Up @@ -18,11 +18,13 @@ Bug fixes and minor changes
---------------------------

+ `#162`_: Minor updates in the tool chain
+ `#164`_: Fix `dumpinvestigation.py` example script

.. _#160: https://github.com/icatproject/python-icat/issues/160
.. _#161: https://github.com/icatproject/python-icat/pull/161
.. _#162: https://github.com/icatproject/python-icat/pull/162
.. _#163: https://github.com/icatproject/python-icat/pull/163
.. _#164: https://github.com/icatproject/python-icat/pull/164


.. _changes-1_4_0:
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264 changes: 163 additions & 101 deletions doc/examples/dumpinvestigation.py
Original file line number Diff line number Diff line change
Expand Up @@ -17,130 +17,192 @@

logging.basicConfig(level=logging.INFO)

formats = icat.dumpfile.Backends.keys()
config = icat.config.Config()
config.add_variable('file', ("-o", "--outputfile"),
dict(help="output file name or '-' for stdout"),
default='-')
config.add_variable('format', ("-f", "--format"),
dict(help="output file format", choices=formats),
default='YAML')
config.add_variable('investigation', ("investigation",),
dict(help="name and optionally visit id "
"(separated by a colon) of the investigation"))
client, conf = config.getconfig()

if client.apiversion < '4.4':
raise RuntimeError("Sorry, ICAT version %s is too old, need 4.4.0 or newer."
% client.apiversion)
client.login(conf.auth, conf.credentials)


# ------------------------------------------------------------
# helper
# ------------------------------------------------------------

def getinvestigation(invid):
def get_investigation_id(client, invid):
"""Search the investigation id from name and optionally visitid."""
query = Query(client, "Investigation", attributes=["id"])
l = invid.split(':')
if len(l) == 1:
# No colon, invid == name
searchexp = "Investigation.id [name='%s']" % tuple(l)
elif len(l) == 2:
query.addConditions({"name": "= '%s'" % l[0]})
if len(l) == 2:
# one colon, invid == name:visitId
searchexp = "Investigation.id [name='%s' AND visitId='%s']" % tuple(l)
query.addConditions({"visitId": "= '%s'" % l[1]})
else:
# too many colons
raise RuntimeError("Invalid investigation identifier '%s'" % invid)
return (client.assertedSearch(searchexp)[0])
return client.assertedSearch(query)[0]

def mergesearch(sexps):
def mergesearch(client, queries):
"""Do many searches and merge the results in one list excluding dups."""
objs = set()
for se in sexps:
for se in queries:
objs.update(client.search(se))
return list(objs)

# The following helper functions control what ICAT objects are written
# in each of the dumpfile chunks. There are three options for the
# items in each list: either queries expressed as Query objects, or
# queries expressed as string expressions, or lists of objects. In
# the first two cases, the search results will be written, in the last
# case, the objects are written as provided.

def get_auth_types(client, invid):
"""Users and groups related to the investigation.
"""
# We need the users related to our investigation via
# InvestigationUser, the users member of one of the groups related
# via InvestigationGroup, and the instrument scientists from the
# instruments related to the investigations. These are
# independent searches, but the results are likely to overlap. So
# we need to search and merge results first.
usersearch = [
Query(client, "User", conditions={
"investigationUsers."
"investigation.id": "= %d" % invid,
}),
Query(client, "User", conditions={
"userGroups.grouping.investigationGroups."
"investigation.id": "= %d" % invid,
}),
Query(client, "User", conditions={
"instrumentScientists.instrument.investigationInstruments."
"investigation.id": "= %d" % invid,
}),
]
return [
mergesearch(client, usersearch),
Query(client, "Grouping", conditions={
"investigationGroups.investigation.id": "= %d" % invid,
}, includes=["userGroups.user"], aggregate="DISTINCT", order=True),
]

def get_static_types(client, invid):
"""Static stuff that exists independently of the investigation in ICAT.
"""
# Similar situation for ParameterType as for User: need to merge
# ParameterType used for InvestigationParameter, SampleParameter,
# DatasetParameter, and DatafileParameter.
ptsearch = [
Query(client, "ParameterType", conditions={
"investigationParameters."
"investigation.id": "= %d" % invid,
}, includes=["facility", "permissibleStringValues"]),
Query(client, "ParameterType", conditions={
"sampleParameters.sample."
"investigation.id": "= %d" % invid,
}, includes=["facility", "permissibleStringValues"]),
Query(client, "ParameterType", conditions={
"datasetParameters.dataset."
"investigation.id": "= %d" % invid,
}, includes=["facility", "permissibleStringValues"]),
Query(client, "ParameterType", conditions={
"datafileParameters.datafile.dataset."
"investigation.id": "= %d" % invid,
}, includes=["facility", "permissibleStringValues"]),
]
return [
Query(client, "Facility",
conditions={
"investigations.id": "= %d" % invid,
},
order=True),
Query(client, "Instrument",
conditions={
"investigationInstruments.investigation.id": "= %d" % invid,
},
includes=["facility", "instrumentScientists.user"],
order=True),
mergesearch(client, ptsearch),
Query(client, "InvestigationType",
conditions={
"investigations.id": "= %d" % invid,
},
includes=["facility"],
order=True),
Query(client, "SampleType",
conditions={
"samples.investigation.id": "= %d" % invid,
},
includes=["facility"],
aggregate="DISTINCT",
order=True),
Query(client, "DatasetType",
conditions={
"datasets.investigation.id": "= %d" % invid,
},
includes=["facility"],
aggregate="DISTINCT",
order=True),
Query(client, "DatafileFormat",
conditions={
"datafiles.dataset.investigation.id": "= %d" % invid,
},
includes=["facility"],
aggregate="DISTINCT",
order=True),
]

def get_investigation_types(client, invid):
"""The investigation and all the stuff that belongs to it.
"""
# The set of objects to be included in the Investigation.
inv_includes = {
"facility", "type.facility", "investigationInstruments",
"investigationInstruments.instrument.facility", "shifts",
"keywords", "publications", "investigationUsers",
"investigationUsers.user", "investigationGroups",
"investigationGroups.grouping", "parameters",
"parameters.type.facility"
}
return [
Query(client, "Investigation",
conditions={"id":"in (%d)" % invid},
includes=inv_includes),
Query(client, "Sample",
conditions={"investigation.id":"= %d" % invid},
includes={"investigation", "type.facility",
"parameters", "parameters.type.facility"},
order=True),
Query(client, "Dataset",
conditions={"investigation.id":"= %d" % invid},
includes={"investigation", "type.facility", "sample",
"parameters", "parameters.type.facility"},
order=True),
Query(client, "Datafile",
conditions={"dataset.investigation.id":"= %d" % invid},
includes={"dataset", "datafileFormat.facility",
"parameters", "parameters.type.facility"},
order=True)
]

# ------------------------------------------------------------
# Do it
# ------------------------------------------------------------

invid = getinvestigation(conf.investigation)

formats = icat.dumpfile.Backends.keys()
config = icat.config.Config()
config.add_variable('file', ("-o", "--outputfile"),
dict(help="output file name or '-' for stdout"),
default='-')
config.add_variable('format', ("-f", "--format"),
dict(help="output file format", choices=formats),
default='YAML')
config.add_variable('investigation', ("investigation",),
dict(help="name and optionally visit id "
"(separated by a colon) of the investigation"))
client, conf = config.getconfig()

# We need the users related to our investigation via
# InvestigationUser, the users member of one of the groups related via
# InvestigationGroup, and the instrument scientists from the
# instruments related to the investigations. These are independent
# searches, but the results are likely to overlap. So we need to
# search and merge results first. Similar situation for ParameterType.
usersearch = [("User <-> InvestigationUser <-> Investigation [id=%d]"),
("User <-> UserGroup <-> Grouping <-> InvestigationGroup "
"<-> Investigation [id=%d]"),
("User <-> InstrumentScientist <-> Instrument "
"<-> InvestigationInstrument <-> Investigation [id=%d]")]
ptsearch = [("ParameterType INCLUDE Facility, PermissibleStringValue "
"<-> InvestigationParameter <-> Investigation [id=%d]"),
("ParameterType INCLUDE Facility, PermissibleStringValue "
"<-> SampleParameter <-> Sample <-> Investigation [id=%d]"),
("ParameterType INCLUDE Facility, PermissibleStringValue "
"<-> DatasetParameter <-> Dataset <-> Investigation [id=%d]"),
("ParameterType INCLUDE Facility, PermissibleStringValue "
"<-> DatafileParameter <-> Datafile <-> Dataset "
"<-> Investigation [id=%d]"), ]
if client.apiversion < '4.4':
raise RuntimeError("Sorry, ICAT version %s is too old, need 4.4.0 or newer."
% client.apiversion)
client.login(conf.auth, conf.credentials)

# The set of objects to be included in the Investigation.
inv_includes = { "facility", "type.facility", "investigationInstruments",
"investigationInstruments.instrument.facility", "shifts",
"keywords", "publications", "investigationUsers",
"investigationUsers.user", "investigationGroups",
"investigationGroups.grouping", "parameters",
"parameters.type.facility" }

# The following lists control what ICAT objects are written in each of
# the dumpfile chunks. There are three options for the items in each
# list: either queries expressed as Query objects, or queries
# expressed as string expressions, or lists of objects. In the first
# two cases, the seacrh results will be written, in the last case, the
# objects are written as provided. We assume that there is only one
# relevant facility, e.g. that all objects related to the
# investigation are related to the same facility. We may thus ommit
# the facility from the ORDER BY clauses.
authtypes = [mergesearch([s % invid for s in usersearch]),
("Grouping ORDER BY name INCLUDE UserGroup, User "
"<-> InvestigationGroup <-> Investigation [id=%d]" % invid)]
statictypes = [("Facility ORDER BY name"),
("Instrument ORDER BY name "
"INCLUDE Facility, InstrumentScientist, User "
"<-> InvestigationInstrument <-> Investigation [id=%d]"
% invid),
(mergesearch([s % invid for s in ptsearch])),
("InvestigationType ORDER BY name INCLUDE Facility "
"<-> Investigation [id=%d]" % invid),
("SampleType ORDER BY name, molecularFormula INCLUDE Facility "
"<-> Sample <-> Investigation [id=%d]" % invid),
("DatasetType ORDER BY name INCLUDE Facility "
"<-> Dataset <-> Investigation [id=%d]" % invid),
("DatafileFormat ORDER BY name, version INCLUDE Facility "
"<-> Datafile <-> Dataset <-> Investigation [id=%d]" % invid)]
investtypes = [Query(client, "Investigation",
conditions={"id":"in (%d)" % invid},
includes=inv_includes),
Query(client, "Sample", order=["name"],
conditions={"investigation.id":"= %d" % invid},
includes={"investigation", "type.facility",
"parameters", "parameters.type.facility"}),
Query(client, "Dataset", order=["name"],
conditions={"investigation.id":"= %d" % invid},
includes={"investigation", "type.facility", "sample",
"parameters", "parameters.type.facility"}),
Query(client, "Datafile", order=["dataset.name", "name"],
conditions={"dataset.investigation.id":"= %d" % invid},
includes={"dataset", "datafileFormat.facility",
"parameters", "parameters.type.facility"})]
invid = get_investigation_id(client, conf.investigation)

with open_dumpfile(client, conf.file, conf.format, 'w') as dumpfile:
dumpfile.writedata(authtypes)
dumpfile.writedata(statictypes)
dumpfile.writedata(investtypes)
dumpfile.writedata(get_auth_types(client, invid))
dumpfile.writedata(get_static_types(client, invid))
dumpfile.writedata(get_investigation_types(client, invid))
2 changes: 1 addition & 1 deletion doc/examples/ingest.py
Original file line number Diff line number Diff line change
Expand Up @@ -24,7 +24,7 @@
The script takes the name of an investigation as argument. The
investigation MUST exist in ICAT beforehand and all datasets in the
input directory MUST belong to this investigation. The script will
create tha datasets in ICAT, e.g. they MUST NOT exist in ICAT
create the datasets in ICAT, e.g. they MUST NOT exist in ICAT
beforehand. The metadata input file may contain attributes and
related objects (datasetInstrument, datasetTechnique,
datasetParameter) for the datasets provided in the input directory.
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