mving cri domain resources under cri.rhizi.net

4 files changed, 0 insertions, 469 deletions

diff --git a/src/local/domain/cri/__init__.py b/src/local/domain/cri/__init__.py
deleted file mode 100644
index e69de29b..00000000
--- a/src/local/domain/cri/__init__.py
+++ /dev/null
diff --git a/src/local/domain/cri/domain_cri.py b/src/local/domain/cri/domain_cri.py
deleted file mode 100644
index db6ed925..00000000
--- a/src/local/domain/cri/domain_cri.py
+++ /dev/null
@@ -1,140 +0,0 @@
-from db_op import DB_op
-
-class DBO_random_data_generation__domain__CRI(DB_op):
-
-    def __init__(self, lim_n=50,
-                       lim_r=10000,
-                       prob_link_create=0.03):
-        """
-        generate random data: CRI domain: Person x Skill
-        """
-        super(DBO_random_data_generation__domain__CRI, self).__init__()
-
-        n_attr_set__skill_raw = ['Cryptocurrency',
-                             'Database architecture',
-                             'Web-development',
-                             'Mobile-development',
-                             'Machine learning',
-                             'Guitar Playing',
-                             'Image processing',
-                             'Algebra',
-                             'Calculus',
-                             'Molecular-Biology',
-                             'Graphic design',
-                             'Geo-location services',
-                             'Drone-building',
-                             'Artificial-intelligence',
-                             'Distributed information systems',
-                             'Wordpress',
-                             'Woodworking',
-                             'Quality-control',
-                             'Video-editing',
-                             'Soldering',
-                             'Network engineering',
-                             'GIT',
-                             'Electronic music',
-                             'Network administration']
-
-        n_attr_set__skill = []
-        for s in n_attr_set__skill_raw:
-            n_attr_set__skill.append(s)
-
-        n_attr_set__name = ['John',
-                            'William',
-                            'James',
-                            'Charles',
-                            'George',
-                            'Frank',
-                            'Joseph',
-                            'Thomas',
-                            'Henry',
-                            'Robert',
-                            'Edward',
-                            'Harry',
-                            'Walter',
-                            'Arthur',
-                            'Fred',
-                            'Albert',
-                            'Samuel',
-                            'David',
-                            'Louis',
-                            'Joe',
-                            'Charlie',
-                            'Clarence',
-                            'Richard',
-                            'Andrew',
-                            'Daniel',
-                            'Ernest',
-                            'Mary',
-                            'Anna',
-                            'Emma',
-                            'Elizabeth',
-                            'Minnie',
-                            'Margaret',
-                            'Ida',
-                            'Alice',
-                            'Bertha',
-                            'Sarah',
-                            'Annie',
-                            'Clara',
-                            'Ella',
-                            'Florence',
-                            'Cora',
-                            'Martha',
-                            'Laura',
-                            'Nellie',
-                            'Grace',
-                            'Carrie',
-                            'Maude',
-                            'Mabel',
-                            'Bessie',
-                            'Jennie',
-                            'Gertrude',
-                            'Julia']
-
-        l_attr_set__level = ['Novice', 'Intermediate', 'Expert']
-
-
-        min_id = 10000  # separate group ids with numerical perfix
-
-        # create persons
-        q_arr = ['with {n_attr_set__name} as n_attr_set',  # TODO clean: foreach triggers SyntaxException: otherwise
-                 'foreach (idx in range(0,%d)' % (lim_n - 1),
-                 '|',
-                 'create (n:%s' % ('Person'),
-                 '{id: \'test-id_\' + toString(%d + idx),' % (min_id),
-                  'name: n_attr_set[idx %% %d]}' % (len(n_attr_set__name)),
-                 '))',
-                ]
-        q_param = {'n_attr_set__name': n_attr_set__name}
-        self.add_statement(q_arr, q_param)
-        min_id *= 2
-
-        # create skills
-        q_arr = ['with {skill_set} as skill_set',  # TODO clean: foreach triggers SyntaxException: otherwise
-                 'foreach (idx in range(0,%d)' % (len(n_attr_set__skill) - 1),
-                 '|',
-                 'create (n:%s' % ('Skill'),
-                 '{id: \'test-id_\' + toString(idx + %d),' % (min_id),
-                  'name: skill_set[idx]}',
-                 '))',
-                ]
-        q_param = {'skill_set': n_attr_set__skill}
-        self.add_statement(q_arr, q_param)
-        min_id *= 2
-
-        # create links
-        for skill_level in l_attr_set__level:
-            q_arr = ['match (n:%s),(m:%s)' % ('Person', 'Skill'),
-                     'with n, m, rand() as rand',
-                     'order by rand',
-                     'limit %d' % (lim_r - 1),
-                     'where rand() < %.2f' % (prob_link_create),
-                     'create (n)-[r:%s' % (skill_level),
-                     '{id: \'test-id_\' + toString(%d + toInt(%d * rand())),' % (min_id, lim_r * 100000),  # aim for low id collision probability,
-                     'proficiency: \'%s\'}' % (skill_level),
-                     ']->(m)',
-                     'return collect(r.id)',
-                     ]
-
-            self.add_statement(q_arr, q_param)
diff --git a/src/local/domain/cri/from_csv b/src/local/domain/cri/from_csv
deleted file mode 100755
index c11babd0..00000000
--- a/src/local/domain/cri/from_csv
+++ /dev/null
@@ -1,271 +0,0 @@
-#!/usr/bin/python2.7
-
-"""
-Import CSV files into Rhizi Server via pythonic API.
-
-Tricky, since this is the only API user. Try to use it exactly as the REST/WS
-API would, just without actually creating a socket connection.
-"""
-
-import sys
-import os
-import argparse
-import string
-import csv
-
-root = os.path.realpath(os.path.join(os.path.dirname(__file__), '..', '..', '..', '..'))
-print("root = %s" % root)
-sys.path.append(os.path.join(root, 'src', 'server'))
-
-from rz_api_common import sanitize_input__topo_diff
-from rz_kernel import RZ_Kernel
-import db_controller as dbc
-from rz_server import Config
-
-from model.graph import Topo_Diff
-
-def topo_diff_json(node_set_add=[], link_set_add=[]):
-    topo_diff_dict = ({
-         u'link_id_set_rm': [],
-         u'link_set_add': link_set_add,
-         u'drop_conjugator_links': True,
-         u'node_set_add': node_set_add,
-         u'node_id_set_rm': []
-        })
-    topo_diff = Topo_Diff.from_json_dict(topo_diff_dict)
-    sanitize_input__topo_diff(topo_diff)
-    return topo_diff;
-
-def commit(topo_diff):
-    _, commit_ret = kernel.diff_commit__topo(topo_diff, ctx)
-
-# Rhizi constants - FIXME use API
-PERSON_LABEL = 'Person'
-INTEREST_LABEL = 'Interest'
-INTERNSHIP_LABEL = "Internship"
-LABEL_SET = '__label_set'
-
-# CSV file columns
-PERSONAL_EMAIL = 'Personal e-mail'
-INTEREST = 'Interests'
-
-id_count = 0
-def next_id():
-    global id_count
-    id_count += 1
-    return '%08d' % id_count
-
-def node_dict(the_id, **args):
-    """ FIXME use API """
-    ret = dict(args)
-    ret['id'] = the_id
-    return ret
-
-def link_dict(source_id, target_id, label, the_id):
-    return ({
-               u'__type': [label],
-               u'__src_id': source_id,
-               u'__dst_id': target_id,
-               u'id': the_id
-           })
-
-def read_csv(filename):
-    for dialect in ['excel', 'excel-tab']:
-        lines = list(csv.reader(open(filename), dialect=dialect))
-        lens = map(len, lines)
-        if max(lens) == min(lens) and max(lens) > 2:
-            return lines
-    raise Exception("no dialect found")
-
-class CSV(object):
-    def __init__(self, filename):
-        self.filename = filename
-        rows = read_csv(filename)
-        headers = rows[0]
-        self.parse_headers(headers)
-        #import pdb; pdb.set_trace()
-        self.rows = rows[1:]
-        self.row_dicts = map(lambda fields: dict(zip(headers, fields)), self.rows)
-
-    def run(self):
-        print("    ****************************    run on data from %r     ****************" % self.filename)
-        self.nodes_dict = {}
-        self.node_set_add = []
-        self.link_set_add = []
-        self.generate_nodes_and_links()
-        #for node in node_set_add:
-        #    print('committing %s' % repr(node))
-        #    commit(topo_diff_json(node_set_add=[node]))
-        commit(topo_diff_json(node_set_add=self.node_set_add))
-        commit(topo_diff_json(link_set_add=self.link_set_add))
-
-    def append_id_node(self, the_id, node):
-        if the_id in self.nodes_dict:
-            return
-        print(repr(node))
-        self.nodes_dict[the_id] = node
-        self.node_set_add.append(node)
-        return the_id
-
-    def _csv_row_to_node(self, d, dict_gen):
-        the_id = next_id()
-        print(repr(d))
-        return the_id, node_dict(the_id=the_id, **dict_gen(d))
-
-    def append_link(self, source_id, target_id, label):
-        the_id = next_id()
-        link = link_dict(source_id, target_id, label, the_id)
-        self.link_set_add.append(link)
-        print(repr(link))
-        return the_id
-
-class Persons(object):
-    def __init__(self):
-        self.by_name = {}
-        self.by_email = {}
-
-    def id_from_something(self, first_name, last_name, email):
-        return self.by_name.get(self.name_from_first_and_last(first_name, last_name), self.by_email.get(email, (None, None)))[0]
-
-    def name_from_first_and_last(self, first_name, last_name):
-        return first_name + ' ' + last_name
-
-    def addPersonNode(self, first_name, last_name, email):
-        ret = ret2 = None
-        name = self.name_from_first_and_last(first_name, last_name)
-        if name in self.by_name:
-            ret = self.by_name[name]
-        if email in self.by_email:
-            ret2 = self.by_email[email]
-        if ret != ret2:
-            print("person node similar but not same for: %r, %r, %r" % (first_name, last_name, email))
-            print(ret2)
-        if ret2 and not ret:
-            ret = ret2
-        if ret:
-            return ret
-        node_id = next_id()
-        node = node_dict(the_id=node_id, name=name, description=email, **{LABEL_SET: [PERSON_LABEL]})
-        ret = (node_id, node)
-        self.by_name[name] = ret
-        self.by_email[email] = ret
-        return ret
-
-persons = Persons()
-addPersonNode = persons.addPersonNode
-
-def cleanEmailField(unclean):
-    return unclean.lower().strip()
-
-class StudentCSV(CSV):
-
-    def __init__(self, filename, **kw):
-        super(StudentCSV, self).__init__(filename=filename, **kw)
-
-    def interests(self, d):
-        return d[self.interestsField]
-
-    def generate_nodes_and_links(self):
-        for d in self.row_dicts:
-            d[self.interestsField] = map(string.strip, d[self.interestsField].split(','))
-            person_id = next_id()
-            person_email = cleanEmailField(d[self.personalEmailField])
-            person_id, person_node = addPersonNode(first_name=d[self.firstNameField], last_name=d[self.lastNameField], email=person_email)
-            self.append_id_node(person_id, person_node)
-            for interest in self.interests(d):
-                interest_id = next_id()
-                interest_node = node_dict(the_id=interest_id,
-                    **{'name':interest, LABEL_SET:[INTEREST_LABEL]})
-                interest_id = self.append_id_node(interest_id, interest_node)
-                self.append_link(person_id, interest_id, 'Is interested in')
-
-    def parse_headers(self, headers):
-        self.firstNameField = headers[0]
-        self.lastNameField = headers[1]
-        self.personalEmailField = headers[2]
-        self.interestsField = headers[3]
-
-descriptionTemplate = """Nature: %s
---------
-Abstract:
-%s"""
-
-class StudentInternshipsCSV(CSV):
-
-    def __init__(self, filename, **kw):
-        super(StudentInternshipsCSV, self).__init__(filename=filename, **kw)
-
-    def parse_headers(self, headers):
-        it = iter(headers)
-        self.firstNameField = it.next()
-        self.lastNameField = it.next()
-        self.emailField = it.next()
-        self.internshipTitleField = it.next()
-        self.internshipNatureField = it.next()
-        self.abstractField = it.next()
-        self.dateStartField = it.next()
-        self.dateEndField = it.next()
-        self.supervisorFirstNameField = it.next()
-        self.supervisorLastNameField = it.next()
-        self.supervisorTitleField = it.next()
-        self.supervisorEmailField = it.next()
-        self.laboratoryNameField = it.next()
-        self.laboratoryAffiliationField = it.next()
-        self.unitCodeField = it.next() # CNRS  / INSERM unit code
-        self.streetField = it.next() # Street
-        self.streetSecondPartField = it.next() # Street (continued)
-        self.cityField = it.next() # City
-        self.countryField = it.next() # Country
-
-    def generate_nodes_and_links(self):
-        for d in self.row_dicts:
-            internship_id = next_id()
-            # FIXME should be title. fix requires client change. need
-            # configurable fields, or a list of names and types for display per
-            # node (using a type node in the db, which could be cached
-            title = d[self.internshipTitleField].strip()
-            if len(title) == 0:
-                print("skipping empty internship field")
-                continue
-            input_dict = {
-                         LABEL_SET:[INTERNSHIP_LABEL],
-                         'name': title,
-                         'description': descriptionTemplate % (d[self.internshipNatureField], d[self.abstractField]),
-                         'startdate': d[self.dateStartField],
-                         'enddate': d[self.dateEndField],
-                         'internship-type': d[self.internshipNatureField],
-                         'cnrs-inserm-unit-code': d[self.unitCodeField],
-                         'city': d[self.cityField],
-                         'country': d[self.countryField],
-                         'street-address': d[self.streetField] + d[self.streetSecondPartField],
-                         'facility': d[self.laboratoryNameField],
-                         'facility-affiliation': d[self.laboratoryAffiliationField],
-                         }
-            internship_node = node_dict(the_id=internship_id, **input_dict)
-            self.append_id_node(internship_id, internship_node)
-            person_email = cleanEmailField(d[self.emailField])
-            first_name = d[self.firstNameField]
-            last_name = d[self.lastNameField]
-            person_id = persons.id_from_something(first_name, last_name, person_email)
-            if None == person_id:
-                print("ERROR: missing %r (%r %r), creating person node with no interests" % (person_email, first_name, last_name))
-                person_id, person_node = addPersonNode(first_name=first_name, last_name=last_name, email=person_email)
-                self.append_id_node(person_id, person_node)
-            self.append_link(source_id=person_id, target_id=internship_id, label='Did this internship')
-
-def main(args, internships):
-    cfg = Config.init_from_file(args.config)
-    kernel = RZ_Kernel()
-    kernel.db_ctl = dbc.DB_Controller(cfg) # yes, that. FIXME
-    globals()['kernel'] = kernel
-    globals()['ctx'] = {} # FIXME not logged it - fix later (also, don't do this here, put constructor in kernel)
-    StudentCSV(filename=args.student).run()
-    for internship in internships:
-        StudentInternshipsCSV(filename=internship).run()
-
-if __name__ == '__main__':
-    parser = argparse.ArgumentParser()
-    parser.add_argument('--student', required=True)
-    parser.add_argument('--config', default=os.path.join(root, 'res', 'etc', 'rhizi-server.conf'))
-    args, internships = parser.parse_known_args(sys.argv[1:])
-    main(args, internships)
diff --git a/src/local/domain/cri/test_domain__CRI.py b/src/local/domain/cri/test_domain__CRI.py
deleted file mode 100644
index 54131bbd..00000000
--- a/src/local/domain/cri/test_domain__CRI.py
+++ /dev/null
@@ -1,58 +0,0 @@
-import inspect
-import logging
-import tempfile
-import unittest
-
-import db_controller as dbc
-from db_op import DBO_cypher_query
-from domain_cri import DBO_random_data_generation__domain__CRI
-from rz_server import Config
-
-
-class Test_Domain_CRI(unittest.TestCase):
-
-    @classmethod
-    def setUpClass(self):
-        cfg = Config.init_from_file('res/etc/rhizi-server.conf')
-        self.db_ctl = dbc.DB_Controller(cfg)
-        self.log = logging.getLogger('rhizi')
-        self.log.addHandler(logging.StreamHandler())
-
-    def test_random_data_generation__domain__CRI(self, export_as_csv=True):
-        """
-        test:
-           - random CRI domain data generation
-           - DB dump in cvs format: person x skill x skill-level
-        """
-        op = DBO_random_data_generation__domain__CRI()
-        self.db_ctl.exec_op(op)
-
-        if False == export_as_csv:
-            return
-
-        q_arr = ['match (n: Person)',
-                 'with n',
-                 'match (n)-[r:Novice|Intermediate|Expert]->(m:Skill)',  # [!] expect link type to be proficiency level
-                 'return n.name, collect({skill_name: m.name, skill_level: r.proficiency})'
-                 ]
-        op = DBO_cypher_query(q_arr)
-
-        cur_f_name = inspect.stack()[0][3]
-        def q_process_result_set():
-            with tempfile.NamedTemporaryFile(prefix='rz_%s' % (cur_f_name), dir='/tmp', suffix='.csv', delete=False) as f_out:
-                for _, _, r_set in op:
-                    for row in r_set:
-                        person_name, skill_dict_set = row  # person to {sname: skill, s:pro: skill_level{ dict set
-                        cvs_line_arr = [person_name]
-                        for skill_dict in skill_dict_set:
-                            skill_name = skill_dict['skill_name']
-                            skill_level = skill_dict['skill_level']
-                            cvs_line_arr += [skill_name, skill_level]
-                        f_out.write(','.join(cvs_line_arr) + '\n')
-                f_out.write('\n')
-
-        op.process_result_set = q_process_result_set
-        self.db_ctl.exec_op(op)
-
-if __name__ == "__main__":
-    unittest.main()