Python config.DEBUG Examples
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Example #1
Source File: nfp_log.py From nightmare with GNU General Public License v2.0 | 5 votes |
def debug(msg): if DEBUG: log(msg)
Example #2
Source File: base.py From backtrader-binance-bot with MIT License | 5 votes |
def log(self, txt, send_telegram=False, color=None): if not DEBUG: return value = datetime.now() if len(self) > 0: value = self.data0.datetime.datetime() if color: txt = colored(txt, color) print('[%s] %s' % (value.strftime("%d-%m-%y %H:%M"), txt)) if send_telegram: send_telegram_message(txt)
Example #3
Source File: web.py From certitude with GNU General Public License v2.0 | 5 votes |
def run_server(): context = None if USE_SSL and os.path.isfile(SSL_KEY_FILE) and os.path.isfile(SSL_CERT_FILE): context = ssl.SSLContext(ssl.PROTOCOL_TLSv1_2) context.load_cert_chain(SSL_CERT_FILE, SSL_KEY_FILE) loggingserver.info('Using SSL, open interface in HTTPS') loggingserver.info('Web interface starting') app.run( host=LISTEN_ADDRESS, port=LISTEN_PORT, debug=DEBUG, ssl_context=context )
Example #4
Source File: gen.py From web-traffic-generator with MIT License | 5 votes |
def debug_print(message, color=Colors.NONE): """ A method which prints if DEBUG is set """ if config.DEBUG: print(color + message + Colors.NONE)
Example #5
Source File: cn_log.py From cosa-nostra with GNU General Public License v3.0 | 5 votes |
def debug(msg): if DEBUG: log(msg)
Example #6
Source File: self-serve.py From danforth-east with MIT License | 5 votes |
def get(self): """Serve the form page. """ logging.info('SelfComboPage.GET') logging.info('headers: %s' % self.request.headers.items()) logging.info('params: %s' % self.request.params.items()) logging.info('body: %s' % self.request.body) # Make sure (as best we can) that this is being requested from a site # that's allowed to embed our join form. # This is such a weak check that I'm not sure it's worth it. #if not config.DEBUG: # if not self.request.referer or \ # urlparse(self.request.referer).hostname not in config.ALLOWED_EMBED_REFERERS: # webapp2.abort(403, detail='bad referer') csrf_token = helpers.get_csrf_token(self.request) volunteer_interests = gapps.get_volunteer_interests() skills_categories = gapps.get_skills_categories() template_values = { 'FIELDS': config.FIELDS, 'csrf_token': csrf_token, 'volunteer_interests': volunteer_interests, 'skills_categories': skills_categories, 'config': config, } template = JINJA_ENVIRONMENT.get_template('self-serve-combo.jinja') helpers.set_csrf_cookie(self.response, csrf_token) self.response.write(template.render(template_values))
Example #7
Source File: self-serve.py From danforth-east with MIT License | 5 votes |
def post(self): """Create the new volunteer. """ logging.info('SelfVolunteerPage.POST') logging.info('headers: %s' % self.request.headers.items()) logging.info('params: %s' % self.request.params.items()) logging.info('body: %s' % self.request.body) # Make sure (as best we can) that this is being requested from a site # that's allowed to embed our join form. # This is such a weak check that I'm not sure it's worth it. #if not config.DEBUG: # if not self.request.referer or \ # urlparse(self.request.referer).hostname not in config.ALLOWED_EMBED_REFERERS: # webapp2.abort(403, detail='bad referer') # TODO: Use new CSRF approach that doesn't need cookies. #helpers.check_csrf(self.request) # TODO: Don't hardcode key referrer = self.request.params.get('_referrer') or self.request.referer # Create a dict of the volunteer info. new_volunteer = gapps.volunteer_dict_from_request(self.request, referrer) gapps.join_volunteer_from_dict(new_volunteer) self.response.write('success') # Queue the welcome email taskqueue.add(url='/tasks/new-volunteer-mail', params=new_volunteer)
Example #8
Source File: self-serve.py From danforth-east with MIT License | 5 votes |
def get(self): """Serve the form page. """ logging.info('SelfVolunteerPage.GET') logging.info('headers: %s' % self.request.headers.items()) logging.info('params: %s' % self.request.params.items()) logging.info('body: %s' % self.request.body) # Make sure (as best we can) that this is being requested from a site # that's allowed to embed our join form. # This is such a weak check that I'm not sure it's worth it. #if not config.DEBUG: # if not self.request.referer or \ # urlparse(self.request.referer).hostname not in config.ALLOWED_EMBED_REFERERS: # webapp2.abort(403, detail='bad referer') csrf_token = helpers.get_csrf_token(self.request) volunteer_interests = gapps.get_volunteer_interests() skills_categories = gapps.get_skills_categories() template_values = { 'FIELDS': config.FIELDS, 'csrf_token': csrf_token, 'volunteer_interests': volunteer_interests, 'skills_categories': skills_categories, 'config': config, } template = JINJA_ENVIRONMENT.get_template('self-serve-volunteer.jinja') helpers.set_csrf_cookie(self.response, csrf_token) self.response.write(template.render(template_values))
Example #9
Source File: self-serve.py From danforth-east with MIT License | 5 votes |
def get(self): """Serve the form page. """ logging.info('SelfJoinPage.GET') logging.info('headers: %s', self.request.headers.items()) logging.info('params: %s', self.request.params.items()) logging.info('body: %s', self.request.body) # Make sure (as best we can) that this is being requested from a site # that's allowed to embed our join form. # This is such a weak check that I'm not sure it's worth it. #if not config.DEBUG: # if not self.request.referer or \ # urlparse(self.request.referer).hostname not in config.ALLOWED_EMBED_REFERERS: # webapp2.abort(403, detail='bad referer') csrf_token = helpers.get_csrf_token(self.request) volunteer_interests = gapps.get_volunteer_interests() skills_categories = gapps.get_skills_categories() template_values = { 'FIELDS': config.FIELDS, 'csrf_token': csrf_token, 'volunteer_interests': volunteer_interests, 'skills_categories': skills_categories, 'config': config, } template = JINJA_ENVIRONMENT.get_template('self-serve-join.jinja') helpers.set_csrf_cookie(self.response, csrf_token) self.response.write(template.render(template_values))
Example #10
Source File: morphoconllu.py From Finnish-dep-parser with GNU General Public License v2.0 | 5 votes |
def __init__(self, form, lemma, cpostag, postag, feats): self.form = form self.lemma = lemma self.cpostag = cpostag self.postag = postag self._feats = feats if DEBUG: self.validate() self._fmap = None
Example #11
Source File: runserver.py From apache-flask with MIT License | 5 votes |
def runserver(): port = int(os.environ.get('PORT', DEFAULT_PORT)) app.run(host=DEFAULT_HOST, port=port, debug=DEBUG) #------------------------------
Example #12
Source File: manage.py From CHN-Server with GNU Lesser General Public License v2.1 | 5 votes |
def runlocal(): serverurl = urlparse(config.SERVER_BASE_URL) mhn.run(debug=config.DEBUG, host='0.0.0.0', port=serverurl.port)
Example #13
Source File: manage.py From CHN-Server with GNU Lesser General Public License v2.1 | 5 votes |
def run(): # Takes run parameters from configuration. serverurl = urlparse(config.SERVER_BASE_URL) mhn.run(debug=config.DEBUG, host='0.0.0.0', port=serverurl.port)
Example #14
Source File: preprocessing.py From tf.fashionAI with Apache License 2.0 | 5 votes |
def preprocess_for_test_raw_output(image, output_height, output_width, data_format='NCHW', scope=None): """Preprocesses the given image for evaluation. Args: image: A `Tensor` representing an image of arbitrary size. output_height: The height of the image after preprocessing. output_width: The width of the image after preprocessing. Returns: A preprocessed image. """ with tf.name_scope(scope, 'vgg_test_image_raw_output', [image, output_height, output_width]): # Crop the central region of the image with an area containing 87.5% of # the original image. image = tf.image.resize_bilinear(image, [output_height, output_width], align_corners=False) image = tf.squeeze(image, [0]) image.set_shape([output_height, output_width, 3]) if config.DEBUG: save_image_op = tf.py_func(_save_image, [image], tf.int64, stateful=True) image = tf.Print(image, [save_image_op]) image = tf.to_float(image) normarlized_image = _mean_image_subtraction(image, [_R_MEAN, _G_MEAN, _B_MEAN]) if data_format == 'NCHW': normarlized_image = tf.transpose(normarlized_image, perm=(2, 0, 1)) return tf.expand_dims(normarlized_image/255., 0)
Example #15
Source File: utility.py From PeachOrchard with MIT License | 5 votes |
def msg(string, level=INFO): """ Handle messages; this takes care of logging and debug checking, as well as output colors """ string = "[%s] %s" % (timestamp(), string) color_string = None if 'linux' in platform.platform().lower(): if level is INFO: color_string = '%s%s%s' % ('\033[32m', string, '\033[0m') elif level is DEBUG: color_string = '%s%s%s' % ('\033[34m', string, '\033[0m') elif level is ERROR: color_string = '%s%s%s' % ('\033[31m', string, '\033[0m') else: color_string = string if not color_string: color_string = string if level is DEBUG and not config.DEBUG: return if not level is LOG: print color_string log(string)
Example #16
Source File: w.py From goodbye-mihome with BSD 2-Clause "Simplified" License | 5 votes |
def make_app(): static_path = os.path.join(os.path.dirname(__file__), "static") settings = { 'static_path': static_path, 'debug': config.DEBUG } return tornado.web.Application([ (r"/", MainHandler), (r"/updates", UpdatesHandler), (r"/static/(.*)", tornado.web.StaticFileHandler, {'path': static_path}), ], **settings)
Example #17
Source File: self-serve.py From danforth-east with MIT License | 4 votes |
def post(self): """Create the new member. """ logging.info('SelfJoinPage.POST') logging.info('headers: %s', self.request.headers.items()) logging.info('params: %s', self.request.params.items()) logging.info('cookies: %s', self.request.cookies.items()) logging.info('body: %s', self.request.body) # Make sure (as best we can) that this is being requested from a site # that's allowed to embed our join form. # This is such a weak check that I'm not sure it's worth it. #if not config.DEBUG: # if not self.request.referer or \ # urlparse(self.request.referer).hostname not in config.ALLOWED_EMBED_REFERERS: # webapp2.abort(403, detail='bad referer') # HACK: Safari doesn't allow cookie setting in an iframe without # direct user interaction. So this fails every time on desktop and # mobile Safari. # TODO: Use new CSRF approach that doesn't need cookies. #helpers.check_csrf(self.request) # TODO: Don't hardcode key referrer = self.request.params.get('_referrer') or self.request.referer # Create a dict of the member info. new_member = gapps.member_dict_from_request(self.request, referrer, 'join') # "Paid" field shouldn't be set by form in self-serve. new_member[config.MEMBER_FIELDS.paid.name] = 'N' if self.request.params.get('payment_method') == 'paypal': new_member[config.MEMBER_FIELDS.paid.name] = 'paypal' # Write the member info to the member candidate store. member_candidate = MemberCandidate( member_json=webapp2_extras.json.encode(new_member), created=datetime.datetime.now(), expire=datetime.datetime.now()+datetime.timedelta(days=1)) member_candidate_key = member_candidate.put() invoice_id = member_candidate_key.urlsafe() # If the payment method is "cheque" create the new member directly, # otherwise start the PayPal process. # TODO: Don't hardcode field name if self.request.params.get('payment_method') == 'cheque': params = {'invoice': invoice_id} taskqueue.add(url='/self-serve/process-member-worker', params=params) self.response.write('success') else: # We put the key value into the URL so we can retrieve this member # after payment. paypal_url = config.PAYPAL_PAYMENT_URL % (invoice_id,) self.response.write(paypal_url)
Example #18
Source File: network.py From Learning-to-See-Moving-Objects-in-the-Dark with MIT License | 4 votes |
def network(input, depth=3, channel=32, prefix=''): depth = min(max(depth, 2), 4) conv1 = slim.conv3d(input, channel, [3, 3, 3], rate=1, activation_fn=lrelu, scope=prefix + 'g_conv1_1') conv1 = slim.conv3d(conv1, channel, [3, 3, 3], rate=1, activation_fn=lrelu, scope=prefix + 'g_conv1_2') pool1 = tf.expand_dims(slim.max_pool2d(conv1[0], [2, 2], padding='SAME'), axis=0) conv2 = slim.conv3d(pool1, channel * 2, [3, 3, 3], rate=1, activation_fn=lrelu, scope=prefix + 'g_conv2_1') conv2 = slim.conv3d(conv2, channel * 2, [3, 3, 3], rate=1, activation_fn=lrelu, scope=prefix + 'g_conv2_2') pool2 = tf.expand_dims(slim.max_pool2d(conv2[0], [2, 2], padding='SAME'), axis=0) conv3 = slim.conv3d(pool2, channel * 4, [3, 3, 3], rate=1, activation_fn=lrelu, scope=prefix + 'g_conv3_1') conv3 = slim.conv3d(conv3, channel * 4, [3, 3, 3], rate=1, activation_fn=lrelu, scope=prefix + 'g_conv3_2') if depth == 2: up8 = upsample_and_concat(conv3, conv2, channel * 2, channel * 4) else: pool3 = tf.expand_dims(slim.max_pool2d(conv3[0], [2, 2], padding='SAME'), axis=0) conv4 = slim.conv3d(pool3, channel * 8, [3, 3, 3], rate=1, activation_fn=lrelu, scope=prefix + 'g_conv4_1') conv4 = slim.conv3d(conv4, channel * 8, [3, 3, 3], rate=1, activation_fn=lrelu, scope=prefix + 'g_conv4_2') if depth == 3: up7 = upsample_and_concat(conv4, conv3, channel * 4, channel * 8) else: pool4 = tf.expand_dims(slim.max_pool2d(conv4[0], [2, 2], padding='SAME'), axis=0) conv5 = slim.conv3d(pool4, channel * 16, [3, 3, 3], rate=1, activation_fn=lrelu, scope=prefix + 'g_conv5_1') conv5 = slim.conv3d(conv5, channel * 16, [3, 3, 3], rate=1, activation_fn=lrelu, scope=prefix + 'g_conv5_2') up6 = upsample_and_concat(conv5, conv4, channel * 8, channel * 16) conv6 = slim.conv3d(up6, channel * 8, [3, 3, 3], rate=1, activation_fn=lrelu, scope=prefix + 'g_conv6_1') conv6 = slim.conv3d(conv6, channel * 8, [3, 3, 3], rate=1, activation_fn=lrelu, scope=prefix + 'g_conv6_2') up7 = upsample_and_concat(conv6, conv3, channel * 4, channel * 8) conv7 = slim.conv3d(up7, channel * 4, [3, 3, 3], rate=1, activation_fn=lrelu, scope=prefix + 'g_conv7_1') conv7 = slim.conv3d(conv7, channel * 4, [3, 3, 3], rate=1, activation_fn=lrelu, scope=prefix + 'g_conv7_2') up8 = upsample_and_concat(conv7, conv2, channel * 2, channel * 4) conv8 = slim.conv3d(up8, channel * 2, [3, 3, 3], rate=1, activation_fn=lrelu, scope=prefix + 'g_conv8_1') conv8 = slim.conv3d(conv8, channel * 2, [3, 3, 3], rate=1, activation_fn=lrelu, scope=prefix + 'g_conv8_2') up9 = upsample_and_concat(conv8, conv1, channel, channel * 2) conv9 = slim.conv3d(up9, channel, [3, 3, 3], rate=1, activation_fn=lrelu, scope=prefix + 'g_conv9_1') conv9 = slim.conv3d(conv9, channel, [3, 3, 3], rate=1, activation_fn=lrelu, scope=prefix + 'g_conv9_2') conv10 = slim.conv3d(conv9, 12, [1, 1, 1], rate=1, activation_fn=None, scope=prefix + 'g_conv10') out = tf.concat([tf.expand_dims(tf.depth_to_space(conv10[:, i, :, :, :], 2), axis=1) for i in range(conv10.shape[1])], axis=1) if DEBUG: print '[DEBUG] (network.py) conv10.shape, out.shape:', conv10.shape, out.shape return out # test function for network
Example #19
Source File: main.py From w12scan-client with MIT License | 4 votes |
def main(): PATHS.ROOT_PATH = module_path() PATHS.PLUGIN_PATH = os.path.join(PATHS.ROOT_PATH, "pocs") PATHS.OUTPUT_PATH = os.path.join(PATHS.ROOT_PATH, "output") PATHS.DATA_PATH = os.path.join(PATHS.ROOT_PATH, "data") patch_all() logger.info("Hello W12SCAN !") # domain域名整理(统一格式:无论是域名还是二级目录,右边没有 /),ip cidr模式识别,ip整理 # 访问redis获取目标 def redis_get(): list_name = "w12scan_scanned" while 1: target = redis_con.blpop(list_name)[1] scheduler.put_target(target) # redis_get() def debug_get(): target = "http://stun.tuniu.com" scheduler.put_target(target) def node_register(): first_blood = True while 1: if first_blood: dd = { "last_time": time.time(), "tasks": 0, "running": 0, "finished": 0 } redis_con.hmset(NODE_NAME, dd) first_blood = False else: redis_con.hset(NODE_NAME, "last_time", time.time()) time.sleep(50 * 5) scheduler = Schedular(threadnum=THREAD_NUM) scheduler.start() # 启动任务分发调度器 if DEBUG: func_target = debug_get else: func_target = redis_get # 与WEB的通信线程 node = threading.Thread(target=node_register) node.start() # 队列下发线程 t = threading.Thread(target=func_target, name='LoopThread') t.start() try: scheduler.run() except KeyboardInterrupt: logger.info("User exit")
Example #20
Source File: collector.py From w12scan-client with MIT License | 4 votes |
def submit(self): ''' 传递信息给web restful接口 :return: ''' # domain while not self.cache_queue.empty(): data = self.cache_queue.get() # self.collect_lock.acquire() # with open("domain.result.txt", "a+") as f: # f.write(json.dumps(data) + ",") # self.collect_lock.release() if DEBUG: print("[submit] " + repr(data)) continue _api = urljoin(WEB_INTERFACE, "./api/v1/domain") headers = { "W12SCAN": WEB_INTERFACE_KEY } try: r = requests.post(_api, json=data, headers=headers) except Exception as e: print("api request faild: {0} ".format(str(e))) continue if r.status_code == 200: status = json.loads(r.text) if status["status"] != 200: print("api request faild(status!=200) " + status["msg"]) # ips while not self.cache_ips.empty(): data = self.cache_ips.get() # self.collect_lock.acquire() # with open("ips.result.txt", "a+") as f: # f.write(json.dumps(data) + ",") # self.collect_lock.release() if DEBUG: print("[submit] " + repr(data)) continue _api = urljoin(WEB_INTERFACE, "./api/v1/ip") headers = { "w12scan": WEB_INTERFACE_KEY } try: r = requests.post(_api, json=data, headers=headers) except Exception as e: print("api request faild: {0} ".format(str(e))) continue if r.status_code == 200: status = json.loads(r.text) if status["status"] != 200: print("api request faild(status!=200) " + status["msg"])
Example #21
Source File: preprocessing.py From tf.fashionAI with Apache License 2.0 | 4 votes |
def preprocess_for_test(image, file_name, shape, output_height, output_width, data_format='NCHW', bbox_border=25., heatmap_sigma=1., heatmap_size=64, pred_df=None, scope=None): """Preprocesses the given image for evaluation. Args: image: A `Tensor` representing an image of arbitrary size. output_height: The height of the image after preprocessing. output_width: The width of the image after preprocessing. Returns: A preprocessed image. """ with tf.name_scope(scope, 'vgg_test_image', [image, output_height, output_width]): # Crop the central region of the image with an area containing 87.5% of # the original image. if pred_df is not None: xmin, ymin, xmax, ymax = [table_.lookup(file_name) for table_ in pred_df] #xmin, ymin, xmax, ymax = [tf.to_float(b) for b in bbox_cord] #xmin = tf.Print(xmin, [file_name, xmin, ymin, xmax, ymax], summarize=500) height, width, channals = tf.unstack(shape, axis=0) xmin, ymin, xmax, ymax = xmin - 100, ymin - 80, xmax + 100, ymax + 80 xmin, ymin, xmax, ymax = tf.clip_by_value(xmin, 0, width[0]-1), tf.clip_by_value(ymin, 0, height[0]-1), \ tf.clip_by_value(xmax, 0, width[0]-1), tf.clip_by_value(ymax, 0, height[0]-1) bbox_h = ymax - ymin bbox_w = xmax - xmin areas = bbox_h * bbox_w offsets=tf.stack([xmin, ymin], axis=0) crop_shape = tf.stack([bbox_h, bbox_w, channals[0]], axis=0) ymin, xmin, bbox_h, bbox_w = tf.cast(ymin, tf.int32), tf.cast(xmin, tf.int32), tf.cast(bbox_h, tf.int32), tf.cast(bbox_w, tf.int32) crop_image = tf.image.crop_to_bounding_box(image, ymin, xmin, bbox_h, bbox_w) image, shape, offsets = tf.cond(areas > 0, lambda : (crop_image, crop_shape, offsets), lambda : (image, shape, tf.constant([0, 0], tf.int64))) offsets.set_shape([2]) shape.set_shape([3]) else: offsets = tf.constant([0, 0], tf.int64) image = tf.expand_dims(image, 0) image = tf.image.resize_bilinear(image, [output_height, output_width], align_corners=False) image = tf.squeeze(image, [0]) image.set_shape([output_height, output_width, 3]) if config.DEBUG: save_image_op = tf.py_func(_save_image, [image], tf.int64, stateful=True) image = tf.Print(image, [save_image_op]) image = tf.to_float(image) normarlized_image = _mean_image_subtraction(image, [_R_MEAN, _G_MEAN, _B_MEAN]) if data_format == 'NCHW': normarlized_image = tf.transpose(normarlized_image, perm=(2, 0, 1)) return normarlized_image/255., shape, offsets
Example #22
Source File: preprocessing.py From tf.fashionAI with Apache License 2.0 | 4 votes |
def preprocess_for_eval(image, classid, shape, output_height, output_width, key_x, key_y, key_v, norm_table, data_format, category, bbox_border, heatmap_sigma, heatmap_size, resize_side, scope=None): """Preprocesses the given image for evaluation. Args: image: A `Tensor` representing an image of arbitrary size. output_height: The height of the image after preprocessing. output_width: The width of the image after preprocessing. resize_side: The smallest side of the image for aspect-preserving resizing. Returns: A preprocessed image. """ with tf.name_scope(scope, 'vgg_eval_image', [image, output_height, output_width]): # Crop the central region of the image with an area containing 87.5% of # the original image. fkey_x, fkey_y = tf.cast(key_x, tf.float32)/tf.cast(shape[1], tf.float32), tf.cast(key_y, tf.float32)/tf.cast(shape[0], tf.float32) image = tf.expand_dims(image, 0) image = tf.image.resize_bilinear(image, [output_height, output_width], align_corners=False) image = tf.squeeze(image, [0]) image.set_shape([output_height, output_width, 3]) image = tf.to_float(image) ikey_x = tf.cast(tf.round(fkey_x * heatmap_size), tf.int64) ikey_y = tf.cast(tf.round(fkey_y * heatmap_size), tf.int64) targets, isvalid = draw_labelmap(ikey_x, ikey_y, heatmap_sigma, heatmap_size) norm_gather_ind = tf.stack([norm_table[0].lookup(classid), norm_table[1].lookup(classid)], axis=-1) key_x = tf.cast(tf.round(fkey_x * output_width), tf.int64) key_y = tf.cast(tf.round(fkey_y * output_height), tf.int64) norm_x, norm_y = tf.cast(tf.gather(key_x, norm_gather_ind), tf.float32), tf.cast(tf.gather(key_y, norm_gather_ind), tf.float32) norm_x, norm_y = tf.squeeze(norm_x), tf.squeeze(norm_y) norm_value = tf.pow(tf.pow(norm_x[0] - norm_x[1], 2.) + tf.pow(norm_y[0] - norm_y[1], 2.), .5) if config.DEBUG: save_image_op = tf.py_func(save_image_with_heatmap, [image, targets, config.left_right_group_map[category][0], config.left_right_group_map[category][1], config.left_right_group_map[category][2], [output_height, output_width], heatmap_size], tf.int64, stateful=True) with tf.control_dependencies([save_image_op]): normarlized_image = _mean_image_subtraction(image, [_R_MEAN, _G_MEAN, _B_MEAN]) else: normarlized_image = _mean_image_subtraction(image, [_R_MEAN, _G_MEAN, _B_MEAN]) if data_format == 'NCHW': normarlized_image = tf.transpose(normarlized_image, perm=(2, 0, 1)) return normarlized_image/255., targets, key_v, isvalid, norm_value
Example #23
Source File: log.py From certitude with GNU General Public License v2.0 | 4 votes |
def init(): try: chemin = path.dirname(path.abspath(__file__)) except: chemin = "" # relatif logging.basicConfig(filename=path.join(chemin, '..', LOG_DIRECTORY, 'certitude-core.log'), format=FORMAT_LOGS, filemode='a') formatter = logging.Formatter(FORMAT_LOGS) if DEBUG: logging.getLogger('').setLevel(logging.DEBUG) else: logging.getLogger('').setLevel(logging.INFO) # Database loggingdb = logging.getLogger('sqlalchemy.engine') loggingdb.setLevel(logging.WARNING) handler_logdb = logging.FileHandler(path.join(chemin, '..', LOG_DIRECTORY, 'db.log')) handler_logdb.setFormatter(formatter) loggingdb.addHandler(handler_logdb) # API Server loggingserver = logging.getLogger('api') handler_logapi = logging.FileHandler(path.join(chemin, '..', LOG_DIRECTORY, 'api.log')) handler_logapi.setFormatter(formatter) loggingserver.addHandler(handler_logapi) # IOCScanners loggingiocscan = logging.getLogger('iocscanner') handler_logiocscan = logging.FileHandler(path.join(chemin, '..', LOG_DIRECTORY, 'iocscanners.log')) handler_logiocscan.setFormatter(formatter) loggingiocscan.addHandler(handler_logiocscan) # Hashscanners logginghashscan = logging.getLogger('hashscanner') handler_loghashscan = logging.FileHandler(path.join(chemin, '..', LOG_DIRECTORY, 'hashscanners.log')) handler_loghashscan.setFormatter(formatter) logginghashscan.addHandler(handler_loghashscan) # Console output # define a Handler which writes INFO messages or higher to the sys.stderr console = logging.StreamHandler() console.setLevel(CONSOLE_DEBUG_LEVEL) # set a format which is simpler for console use formatter = logging.Formatter('%(name)-20s : %(levelname)-8s %(message)s') # tell the handler to use this format console.setFormatter(formatter) # add the handler to the root logger logging.getLogger('').addHandler(console)