def sample_template_overview_handler_get_request(study_id, user):
# Check if the current user has access to the sample template
sample_template_checks(study_id, user)
# Check if the sample template exists
exists = SampleTemplate.exists(study_id)
# The following information should always be provided:
# The files that have been uploaded to the system and can be a
# sample template file
files = [
f for _, f in get_files_from_uploads_folders(study_id)
if f.endswith(('txt', 'tsv'))
]
# If there is a job associated with the sample information, the job id
job = None
job_info = r_client.get(SAMPLE_TEMPLATE_KEY_FORMAT % study_id)
if job_info:
job = loads(job_info)['job_id']
# Specific information if it exists or not:
data_types = []
st_fp_id = None
old_files = []
num_samples = 0
num_cols = 0
if exists:
# If it exists we need to provide:
# The id of the sample template file so the user can download it and
# the list of old filepaths
st = SampleTemplate(study_id)
all_st_files = st.get_filepaths()
# The current sample template file is the first one in the list
# (pop(0)) and we are interested only in the id ([0])
st_fp_id = all_st_files.pop(0)[0]
# For the old filepaths we are only interested in their basename
old_files = [basename(fp) for _, fp in all_st_files]
# The number of samples - this is a space efficient way of counting
# the number of samples. Doing len(list(st.keys())) creates a list
# that we are not using
num_samples = sum(1 for _ in st.keys())
# The number of columns
num_cols = len(st.categories())
else:
# It doesn't exist, we also need to provide the data_types in case
# the user uploads a QIIME mapping file
data_types = sorted(data_types_get_req()['data_types'])
return {
'exists': exists,
'uploaded_files': files,
'data_types': data_types,
'user_can_edit': Study(study_id).can_edit(user),
'job': job,
'download_id': st_fp_id,
'old_files': old_files,
'num_samples': num_samples,
'num_columns': num_cols
}
def sample_template_overview_handler_get_request(study_id, user):
# Check if the current user has access to the sample template
sample_template_checks(study_id, user)
# Check if the sample template exists
exists = SampleTemplate.exists(study_id)
# The following information should always be provided:
# The files that have been uploaded to the system and can be a
# sample template file
files = [f for _, f, _ in get_files_from_uploads_folders(study_id)
if f.endswith(('txt', 'tsv', 'xlsx'))]
# If there is a job associated with the sample information, the job id
job = None
job_info = r_client.get(SAMPLE_TEMPLATE_KEY_FORMAT % study_id)
if job_info:
job = loads(job_info)['job_id']
# Specific information if it exists or not:
data_types = []
st_fp_id = None
old_files = []
num_samples = 0
num_cols = 0
if exists:
# If it exists we need to provide:
# The id of the sample template file so the user can download it and
# the list of old filepaths
st = SampleTemplate(study_id)
all_st_files = st.get_filepaths()
# The current sample template file is the first one in the list
# (pop(0)) and we are interested only in the id ([0])
st_fp_id = all_st_files.pop(0)[0]
# For the old filepaths we are only interested in their basename
old_files = [basename(fp) for _, fp in all_st_files]
# The number of samples - this is a space efficient way of counting
# the number of samples. Doing len(list(st.keys())) creates a list
# that we are not using
num_samples = sum(1 for _ in st.keys())
# The number of columns
num_cols = len(st.categories())
else:
# It doesn't exist, we also need to provide the data_types in case
# the user uploads a QIIME mapping file
data_types = sorted(data_types_get_req()['data_types'])
return {'exists': exists,
'uploaded_files': files,
'data_types': data_types,
'user_can_edit': Study(study_id).can_edit(user),
'job': job,
'download_id': st_fp_id,
'old_files': old_files,
'num_samples': num_samples,
'num_columns': num_cols}
def display_template(self, preprocessed_data_id, msg, msg_level):
"""Simple function to avoid duplication of code"""
preprocessed_data_id = int(preprocessed_data_id)
try:
preprocessed_data = Artifact(preprocessed_data_id)
except QiitaDBUnknownIDError:
raise HTTPError(
404, "Artifact %d does not exist!" % preprocessed_data_id)
else:
user = self.current_user
if user.level != 'admin':
raise HTTPError(
403, "No permissions of admin, "
"get/VAMPSSubmitHandler: %s!" % user.id)
prep_template = PrepTemplate(preprocessed_data.prep_template)
sample_template = SampleTemplate(preprocessed_data.study)
study = Study(preprocessed_data.study)
stats = [('Number of samples', len(prep_template)),
('Number of metadata headers',
len(sample_template.categories()))]
demux = [
path for _, path, ftype in preprocessed_data.get_filepaths()
if ftype == 'preprocessed_demux'
]
demux_length = len(demux)
if not demux_length:
msg = ("Study does not appear to have demultiplexed "
"sequences associated")
msg_level = 'danger'
elif demux_length > 1:
msg = ("Study appears to have multiple demultiplexed files!")
msg_level = 'danger'
elif demux_length == 1:
demux_file = demux[0]
demux_file_stats = demux_stats(demux_file)
stats.append(('Number of sequences', demux_file_stats.n))
msg_level = 'success'
self.render('vamps_submission.html',
study_title=study.title,
stats=stats,
message=msg,
study_id=study.id,
level=msg_level,
preprocessed_data_id=preprocessed_data_id)
def display_template(self, preprocessed_data_id, msg, msg_level):
"""Simple function to avoid duplication of code"""
preprocessed_data_id = int(preprocessed_data_id)
try:
preprocessed_data = Artifact(preprocessed_data_id)
except QiitaDBUnknownIDError:
raise HTTPError(404, "Artifact %d does not exist!" % preprocessed_data_id)
else:
user = self.current_user
if user.level != "admin":
raise HTTPError(403, "No permissions of admin, " "get/VAMPSSubmitHandler: %s!" % user.id)
prep_template = PrepTemplate(preprocessed_data.prep_template)
sample_template = SampleTemplate(preprocessed_data.study)
study = Study(preprocessed_data.study)
stats = [
("Number of samples", len(prep_template)),
("Number of metadata headers", len(sample_template.categories())),
]
demux = [path for _, path, ftype in preprocessed_data.get_filepaths() if ftype == "preprocessed_demux"]
demux_length = len(demux)
if not demux_length:
msg = "Study does not appear to have demultiplexed " "sequences associated"
msg_level = "danger"
elif demux_length > 1:
msg = "Study appears to have multiple demultiplexed files!"
msg_level = "danger"
elif demux_length == 1:
demux_file = demux[0]
demux_file_stats = demux_stats(demux_file)
stats.append(("Number of sequences", demux_file_stats.n))
msg_level = "success"
self.render(
"vamps_submission.html",
study_title=study.title,
stats=stats,
message=msg,
study_id=study.id,
level=msg_level,
preprocessed_data_id=preprocessed_data_id,
)
def test_delete_sample_or_column(self):
st = SampleTemplate(1)
# Delete a sample template column
obs = delete_sample_or_column(SampleTemplate, 1, "columns",
"season_environment")
exp = {'status': "success", 'message': ""}
self.assertEqual(obs, exp)
self.assertNotIn('season_environment', st.categories())
# Delete a sample template sample - need to add one sample that we
# will remove
npt.assert_warns(
QiitaDBWarning, st.extend,
pd.DataFrame.from_dict({'Sample1': {
'taxon_id': '9606'
}},
orient='index',
dtype=str))
self.assertIn('1.Sample1', st.keys())
obs = delete_sample_or_column(SampleTemplate, 1, "samples",
"1.Sample1")
exp = {'status': "success", 'message': ""}
self.assertEqual(obs, exp)
self.assertNotIn('1.Sample1', st.keys())
# Delete a prep template column
pt = PrepTemplate(2)
obs = delete_sample_or_column(PrepTemplate, 2, "columns",
"target_subfragment")
exp = {'status': "success", 'message': ""}
self.assertEqual(obs, exp)
self.assertNotIn('target_subfragment', pt.categories())
# Delte a prep template sample
metadata = pd.DataFrame.from_dict(
{
'1.SKB8.640193': {
'barcode': 'GTCCGCAAGTTA',
'primer': 'GTGCCAGCMGCCGCGGTAA'
},
'1.SKD8.640184': {
'barcode': 'CGTAGAGCTCTC',
'primer': 'GTGCCAGCMGCCGCGGTAA'
}
},
orient='index',
dtype=str)
pt = npt.assert_warns(QiitaDBWarning, PrepTemplate.create, metadata,
Study(1), "16S")
obs = delete_sample_or_column(PrepTemplate, pt.id, "samples",
'1.SKD8.640184')
exp = {'status': "success", 'message': ""}
self.assertEqual(obs, exp)
self.assertNotIn('1.SKD8.640184', pt.categories())
# Exception
obs = delete_sample_or_column(PrepTemplate, 2, "samples",
"1.SKM9.640192")
exp = {
'status':
"danger",
'message':
"Prep info file '2' has files attached, you cannot "
"delete samples."
}
self.assertEqual(obs, exp)
# No "samples" or "columns"
obs = delete_sample_or_column(PrepTemplate, 2, "not_samples", "NOP")
exp = {
'status':
'danger',
'message':
'Unknown value "not_samples". Choose between '
'"samples" and "columns"'
}
self.assertEqual(obs, exp)
def test_delete_sample_or_column(self):
st = SampleTemplate(1)
# Delete a sample template column
job = self._create_job(
'delete_sample_or_column', {
'obj_class': 'SampleTemplate',
'obj_id': 1,
'sample_or_col': 'columns',
'name': 'season_environment'
})
private_task(job.id)
self.assertEqual(job.status, 'success')
self.assertNotIn('season_environment', st.categories())
# Delete a sample template sample - need to add one
# sample that we will remove
npt.assert_warns(
QiitaDBWarning, st.extend,
pd.DataFrame.from_dict({'Sample1': {
'taxon_id': '9606'
}},
orient='index',
dtype=str))
self.assertIn('1.Sample1', st.keys())
job = self._create_job(
'delete_sample_or_column', {
'obj_class': 'SampleTemplate',
'obj_id': 1,
'sample_or_col': 'samples',
'name': '1.Sample1'
})
private_task(job.id)
self.assertEqual(job.status, 'success')
self.assertNotIn('1.Sample1', st.keys())
# Delete a prep template column
pt = PrepTemplate(1)
job = self._create_job(
'delete_sample_or_column', {
'obj_class': 'PrepTemplate',
'obj_id': 1,
'sample_or_col': 'columns',
'name': 'target_subfragment'
})
private_task(job.id)
self.assertEqual(job.status, 'success')
self.assertNotIn('target_subfragment', pt.categories())
# Delete a prep template sample
metadata = pd.DataFrame.from_dict(
{
'1.SKB8.640193': {
'barcode': 'GTCCGCAAGTTA',
'primer': 'GTGCCAGCMGCCGCGGTAA'
},
'1.SKD8.640184': {
'barcode': 'CGTAGAGCTCTC',
'primer': 'GTGCCAGCMGCCGCGGTAA'
}
},
orient='index',
dtype=str)
pt = npt.assert_warns(QiitaDBWarning, PrepTemplate.create, metadata,
Study(1), "16S")
job = self._create_job(
'delete_sample_or_column', {
'obj_class': 'PrepTemplate',
'obj_id': pt.id,
'sample_or_col': 'samples',
'name': '1.SKD8.640184'
})
private_task(job.id)
self.assertNotIn('1.SKD8.640184', pt.keys())
# Test exceptions
job = self._create_job(
'delete_sample_or_column', {
'obj_class': 'UnknownClass',
'obj_id': 1,
'sample_or_col': 'columns',
'name': 'column'
})
private_task(job.id)
self.assertEqual(job.status, 'error')
self.assertIn(
'Unknown value "UnknownClass". Choose between '
'"SampleTemplate" and "PrepTemplate"', job.log.msg)
job = self._create_job(
'delete_sample_or_column', {
'obj_class': 'SampleTemplate',
'obj_id': 1,
'sample_or_col': 'unknown',
'name': 'column'
})
private_task(job.id)
self.assertEqual(job.status, 'error')
self.assertIn(
'Unknown value "unknown". Choose between "samples" '
'and "columns"', job.log.msg)
def test_delete_sample_or_column(self):
st = SampleTemplate(1)
# Delete a sample template column
job = self._create_job('delete_sample_or_column',
{'obj_class': 'SampleTemplate', 'obj_id': 1,
'sample_or_col': 'columns',
'name': 'season_environment'})
private_task(job.id)
self.assertEqual(job.status, 'success')
self.assertNotIn('season_environment', st.categories())
# Delete a sample template sample - need to add one
# sample that we will remove
npt.assert_warns(
QiitaDBWarning, st.extend,
pd.DataFrame.from_dict({'Sample1': {'taxon_id': '9606'}},
orient='index', dtype=str))
self.assertIn('1.Sample1', st.keys())
job = self._create_job('delete_sample_or_column',
{'obj_class': 'SampleTemplate', 'obj_id': 1,
'sample_or_col': 'samples',
'name': '1.Sample1'})
private_task(job.id)
self.assertEqual(job.status, 'success')
self.assertNotIn('1.Sample1', st.keys())
# Delete a prep template column
pt = PrepTemplate(1)
job = self._create_job('delete_sample_or_column',
{'obj_class': 'PrepTemplate', 'obj_id': 1,
'sample_or_col': 'columns',
'name': 'target_subfragment'})
private_task(job.id)
self.assertEqual(job.status, 'success')
self.assertNotIn('target_subfragment', pt.categories())
# Delete a prep template sample
metadata = pd.DataFrame.from_dict(
{'1.SKB8.640193': {'barcode': 'GTCCGCAAGTTA',
'primer': 'GTGCCAGCMGCCGCGGTAA'},
'1.SKD8.640184': {'barcode': 'CGTAGAGCTCTC',
'primer': 'GTGCCAGCMGCCGCGGTAA'}},
orient='index', dtype=str)
pt = npt.assert_warns(QiitaDBWarning, PrepTemplate.create, metadata,
Study(1), "16S")
job = self._create_job('delete_sample_or_column',
{'obj_class': 'PrepTemplate', 'obj_id': pt.id,
'sample_or_col': 'samples',
'name': '1.SKD8.640184'})
private_task(job.id)
self.assertNotIn('1.SKD8.640184', pt.keys())
# Test exceptions
job = self._create_job('delete_sample_or_column',
{'obj_class': 'UnknownClass', 'obj_id': 1,
'sample_or_col': 'columns', 'name': 'column'})
private_task(job.id)
self.assertEqual(job.status, 'error')
self.assertIn('Unknown value "UnknownClass". Choose between '
'"SampleTemplate" and "PrepTemplate"', job.log.msg)
job = self._create_job('delete_sample_or_column',
{'obj_class': 'SampleTemplate', 'obj_id': 1,
'sample_or_col': 'unknown', 'name': 'column'})
private_task(job.id)
self.assertEqual(job.status, 'error')
self.assertIn('Unknown value "unknown". Choose between "samples" '
'and "columns"', job.log.msg)
if not allow_submission:
msg_list.append(
"Only artifacts with a single prep template can be submitted")
# If allow_submission is already false, we technically don't need to
# do the following work. However, there is no clean way to fix this
# using the current structure, so we perform the work as we
# did so it doesn't fail.
# We currently support only one prep template for submission, so
# grabbing the first one
prep_template = prep_templates[0]
study = preprocessed_data.study
sample_template = study.sample_template
>>>>>>> 405cbef0c9f71c620da95a0c1ba6c7d3d588b3ed
stats = [('Number of samples', len(prep_template)),
('Number of metadata headers',
len(sample_template.categories()))]
demux = [path for _, path, ftype in preprocessed_data.get_filepaths()
if ftype == 'preprocessed_demux']
demux_length = len(demux)
if not demux_length:
msg = ("Study does not appear to have demultiplexed "
"sequences associated")
msg_level = 'danger'
elif demux_length > 1:
msg = ("Study appears to have multiple demultiplexed files!")
msg_level = 'danger'
elif demux_length == 1:
demux_file = demux[0]
demux_file_stats = demux_stats(demux_file)
def test_delete_sample_or_column(self):
st = SampleTemplate(1)
# Delete a sample template column
obs = delete_sample_or_column(SampleTemplate, 1, "columns",
"season_environment")
exp = {'status': "success", 'message': ""}
self.assertEqual(obs, exp)
self.assertNotIn('season_environment', st.categories())
# Delete a sample template sample - need to add one sample that we
# will remove
npt.assert_warns(
QiitaDBWarning, st.extend,
pd.DataFrame.from_dict({'Sample1': {'taxon_id': '9606'}},
orient='index', dtype=str))
self.assertIn('1.Sample1', st.keys())
obs = delete_sample_or_column(SampleTemplate, 1, "samples",
"1.Sample1")
exp = {'status': "success", 'message': ""}
self.assertEqual(obs, exp)
self.assertNotIn('1.Sample1', st.keys())
# Delete a prep template column
pt = PrepTemplate(2)
obs = delete_sample_or_column(PrepTemplate, 2, "columns",
"target_subfragment")
exp = {'status': "success", 'message': ""}
self.assertEqual(obs, exp)
self.assertNotIn('target_subfragment', pt.categories())
# Delte a prep template sample
metadata = pd.DataFrame.from_dict(
{'1.SKB8.640193': {'barcode': 'GTCCGCAAGTTA',
'primer': 'GTGCCAGCMGCCGCGGTAA'},
'1.SKD8.640184': {'barcode': 'CGTAGAGCTCTC',
'primer': 'GTGCCAGCMGCCGCGGTAA'}},
orient='index', dtype=str)
pt = npt.assert_warns(QiitaDBWarning, PrepTemplate.create, metadata,
Study(1), "16S")
obs = delete_sample_or_column(PrepTemplate, pt.id, "samples",
'1.SKD8.640184')
exp = {'status': "success", 'message': ""}
self.assertEqual(obs, exp)
self.assertNotIn('1.SKD8.640184', pt.categories())
# Exception
obs = delete_sample_or_column(PrepTemplate, 2, "samples",
"1.SKM9.640192")
exp = {'status': "danger",
'message': "Prep info file '2' has files attached, you cannot "
"delete samples."}
self.assertEqual(obs, exp)
# No "samples" or "columns"
obs = delete_sample_or_column(PrepTemplate, 2, "not_samples", "NOP")
exp = {'status': 'danger',
'message': 'Unknown value "not_samples". Choose between '
'"samples" and "columns"'}
self.assertEqual(obs, exp)
