WIP on refactor
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131d687d42
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@ -50,11 +50,11 @@ def create_session(name, desc, project_name, urgency=1):
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else:
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print('Session "{}" already exists.'.format(name))
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def bind_testing():
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def connect_testing():
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db.bind('sqlite', ':memory:')
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db.generate_mapping(create_tables=True)
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def bind(credentials_file):
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def connect(credentials_file):
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with open(credentials_file) as f:
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credentials = json.load(f)
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db.bind(**credentials)
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40
minigrida/logging.yaml
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40
minigrida/logging.yaml
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@ -0,0 +1,40 @@
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version: 1
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disable_existing_loggers: False
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formatters:
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simple:
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format: "%(asctime)s %(levelname)s %(name)s: %(message)s"
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handlers:
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console:
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class: logging.StreamHandler
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level: INFO
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formatter: simple
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stream: ext://sys.stdout
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info_file_handler:
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class: logging.handlers.RotatingFileHandler
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level: INFO
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formatter: simple
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filename: Logs/info.log
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maxBytes: 10485760 # 10MB
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backupCount: 20
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encoding: utf8
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error_file_handler:
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class: logging.handlers.RotatingFileHandler
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level: ERROR
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formatter: simple
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filename: Logs/errors.log
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maxBytes: 10485760 # 10MB
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backupCount: 20
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encoding: utf8
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loggers:
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my_module:
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level: DEBUG
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handlers: [console]
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propagate: no
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root:
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level: DEBUG
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handlers: [console, info_file_handler, error_file_handler]
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128
minigrida/protocols/jurse2.py
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128
minigrida/protocols/jurse2.py
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@ -0,0 +1,128 @@
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#!/usr/bin/env python
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# file jurse2.py
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# author Florent Guiotte <florent.guiotte@irisa.fr>
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# version 0.0
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# date 26 mai 2020
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"""Abstract
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doc.
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"""
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import importlib
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import numpy as np
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from sklearn import metrics
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import rasterio
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from .protocol import Protocol, TestError
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class Jurse2(Protocol):
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"""Second JURSE test protocol for LiDAR classification with 2D maps.
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"""
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def __init__(self, expe):
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super().__init__(expe, self.__class__.__name__)
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def _get_hashes(self):
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hashes = OrderedDict()
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glob = hashlib.sha1()
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for k in ['ground_truth', 'descriptors_script',
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'cross_validation', 'classifier']:
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val = str(self._expe[k]).encode('utf-8')
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hashes[k] = hashlib.sha1(val).hexdigest()
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glob.update(val)
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hashes['global'] = glob.hexdigest()
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return hashes
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def _run(self):
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self._log.info('Compute descriptors')
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try:
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descriptors = self._compute_descriptors()
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except Exception:
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raise TestError('Error occured during description')
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self._time('description')
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self._log.info('Classify data')
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try:
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classification = self._compute_classification(descriptors)
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except Exception:
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raise TestError('Error occured during classification')
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self._time('classification')
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self._log.info('Run metrics')
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metrics = self._run_metrics(classification, descriptors)
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self._time('metrics')
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cmap = str(self._results_base_name) + '.tif'
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self._log.info('Saving classification map {}'.format(cmap))
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triskele.write(cmap, classification)
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results = OrderedDict()
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results['classification'] = cmap
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results['metrics'] = metrics
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self._results = results
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def _compute_descriptors(self):
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script = self._expe['descriptors_script']
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desc = importlib.import_module(script['name'])
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att = desc.run(**script['parameters'])
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return att
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def _compute_classification(self, descriptors):
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# Ground truth
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gt = self._get_ground_truth()
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# CrossVal and ML
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cv = self._expe['cross_validation']
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cl = self._expe['classifier']
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cross_val = getattr(importlib.import_module(cv['package']), cv['name'])
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classifier = getattr(importlib.import_module(cl['package']), cl['name'])
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prediction = np.zeros_like(gt, dtype=np.uint8)
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for xt, xv, yt, yv, ti in cross_val(gt, descriptors, **cv['parameters']):
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rfc = classifier(**cl['parameters'])
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rfc.fit(xt, yt)
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ypred = rfc.predict(xv)
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prediction[ti] = ypred
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return prediction
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def _get_ground_truth(self):
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gt_expe = self._expe['ground_truth']
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gt = triskele.read(gt_expe['raster'])
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# Meta labeling
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idx_map = np.arange(gt.max() + 1)
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if 'meta_labels' in gt_expe:
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meta_idx = pd.read_csv(gt_expe['meta_labels'])
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idx = np.array(meta_idx['index'])
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midx = np.array(meta_idx['metaclass_index'])
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idx_map[idx] = midx
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return idx_map[gt]
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def _get_results(self):
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return self._results
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def _run_metrics(self, classification, descriptors):
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gt = self._get_ground_truth()
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f = np.nonzero(classification)
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pred = classification[f].ravel()
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gt = gt[f].ravel()
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results = OrderedDict()
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results['dimensions'] = descriptors.shape[-1]
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results['overall_accuracy'] = float(metrics.accuracy_score(gt, pred))
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results['cohen_kappa'] = float(metrics.cohen_kappa_score(gt, pred))
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return results
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@ -10,16 +10,12 @@
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import logging
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import time
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from collections import OrderedDict
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class Protocol:
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def __init__(self, expe, name=None):
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self._log = logging.getLogger(name)
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self._expe = expe
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self._name = name
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self._times = OrderedDict()
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self._results_base_name = None
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self._log.debug('expe loaded: {}'.format(self._expe))
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def get_hashes(self):
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@ -3,15 +3,13 @@
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# \file supervisor.py
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# \brief TODO
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# \author Florent Guiotte <florent.guiotte@gmail.com>
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# \version 0.1
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# \version 2.1
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# \date 07 sept. 2018
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#
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# TODO details
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import yaml
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import importlib
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import hashlib
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from collections import OrderedDict
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import json
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import time
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import os
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import datetime
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@ -21,34 +19,10 @@ import traceback
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import logging
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import logger
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from protocols.protocol import TestError
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ENRICHMENT_DIR = Path('./Enrichment/')
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TEST_DIR = ENRICHMENT_DIR / 'Tests'
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STAGING_DIR = ENRICHMENT_DIR / 'Staging'
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RESULT_DIR = ENRICHMENT_DIR / 'Results'
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FAILED_DIR = ENRICHMENT_DIR / 'Failed'
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import database
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log = logging.getLogger('Supervisor [{}]'.format(os.uname()[1]))
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def setup_yaml():
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""" Keep yaml ordered, newline string
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from https://stackoverflow.com/a/8661021
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"""
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represent_dict_order = lambda self, data: self.represent_mapping('tag:yaml.org,2002:map', data.items())
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yaml.add_representer(OrderedDict, represent_dict_order)
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""" https://stackoverflow.com/a/24291536 """
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yaml.Dumper.org_represent_str = yaml.Dumper.represent_str
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yaml.add_representer(str, repr_str, Dumper=yaml.Dumper)
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def repr_str(dumper, data):
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if '\n' in data:
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return dumper.represent_scalar(u'tag:yaml.org,2002:str',
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data, style='|')
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return dumper.org_represent_str(data)
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def update_queue():
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tmp_queue = list()
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for child in TEST_DIR.iterdir():
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@ -188,28 +162,12 @@ class ExpePath:
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def get_result_path(self):
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return Path(RESULT_DIR) / self._get_hash_name()
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def _check_hash(self, expe):
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if self._hash is None:
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if 'hashes' in expe:
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self._hash = expe['hashes']['global']
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def _write(self, path, expe):
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new_path = Path(path) / self._get_complete_name()
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with open(new_path, 'w') as of:
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yaml.dump(expe, of,
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default_flow_style=False,
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encoding=None,
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allow_unicode=True)
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self._actual.unlink()
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self._actual = new_path
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def watch_folder():
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log.info('Waiting for test')
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while not list(TEST_DIR.glob('*.yml')):
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time.sleep(3)
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def get_database():
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def main():
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print('Hello again')
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database
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return
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while(True):
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try:
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queue = update_queue()
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@ -239,5 +197,4 @@ if __name__ == '__main__':
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logger.setup_logging()
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log.info('Starting supervisor')
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setup_yaml()
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main()
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