def run(filename):
server = request.form.get("host")
params = request.form.get("params")
print("params: {}".format(params))
if server == "SSH":
ssh = utils.connect_ssh(app.config["rmt_host"], app.config["rmt_port"],
app.config["rmt_username"],
app.config["rmt_password"])
utils.upload_file(ssh,
os.path.join(app.config["FILE_UPLOADS"], filename),
filename)
command = "cd /itu/s06d03/user_home/isleyen16/ai_tracking/ && python " + filename + " " + params
stdin, stdout, stderr = ssh.exec_command(command)
lines = stdout.readlines()
print(lines)
ssh.close()
else:
file = app.config["FILE_UPLOADS"] + "//" + filename
Popen('python ' + file + " " + params)
files[filename].condition = "Invoked"
uname = platform.uname()
sys_name = uname.system
boot_time_timestamp = psutil.boot_time()
bt = datetime.fromtimestamp(boot_time_timestamp)
cpu_usage = psutil.cpu_percent()
freq = psutil.cpu_freq()
curr_freq = freq.current
sysInfo = SystemInfo(sys_name, bt, cpu_usage, curr_freq)
files[filename].sysInfo = sysInfo
return render_template("public/monitor_results.html",
files=files,
servers=servers)
def upload_file():
file_path = "F:/picture/"
file_path = file_path + readfrom
with open(file_path, 'w') as f:
f.write(file_source)
utils.upload_file(file_path)
pass
def write_messages_to_tsv(files, bucket_name, metadata_file=None):
"""
Consume the subscription and write results to tsv manifest
Args:
files(dict): a dictionary of object files
{
"url": "test_url",
"md5": "test_md5",
"size": 1
}
bucket_name(str): bucket for uploading the manifest to
metadata_file(str): metadata file for merging
"""
metadata_info = {}
# Default filenames without merging
fields = ["url", "size", "md5"]
# merge extra metadata info from file
if metadata_file:
with open(metadata_file, "rt") as csvfile:
csvReader = csv.DictReader(csvfile, delimiter="\t")
# Build a map with url as the key
for row in csvReader:
if "url" in row:
metadata_info[row["url"]] = {
k: v
for k, v in row.items() if k != "url"
}
# do merging if possible, and update fields
need_merge = False
first_row_need_merge = None
for row_num, fi in enumerate(files):
if fi["url"] in metadata_info:
need_merge = True
first_row_need_merge = first_row_need_merge or row_num
for k, v in metadata_info[fi["url"]].items():
fi[k] = v
if files and need_merge:
# add new fields
[
fields.append(k) for k in files[first_row_need_merge].keys()
if k not in ["url", "size", "md5"]
]
if len(files) > 0:
# part the url
parts = urlparse(files[0]["url"])
# generate unique manifest output
now = datetime.now()
current_time = now.strftime("%m_%d_%y_%H:%M:%S")
filename = "manifest_{}_{}.tsv".format(parts.netloc, current_time)
# write list of object metadata to a file
utils.write_tsv(filename, files, fields)
# Upload the file to google bucket
utils.upload_file(bucket_name, filename, filename)
logging.info("DONE!!!")
def test_python():
python_script_path = os.path.join(THIS_DIR, 'jobs', 'python', 'pi_with_include.py')
python_script_url = utils.upload_file(python_script_path)
py_file_path = os.path.join(THIS_DIR, 'jobs', 'python', 'PySparkTestInclude.py')
py_file_url = utils.upload_file(py_file_path)
utils.run_tests(app_url=python_script_url,
app_args="30",
expected_output="Pi is roughly 3",
app_name="/spark",
args=["--py-files", py_file_url])
def update_challenge():
if request.method == 'POST' and len(request.form) >= 6:
if logged_in():
errors = []
try:
eid = request.form['eid']
name = request.form['name']
category = request.form['category']
value = int(request.form['value'])
desc = request.form['description']
except:
errors.append("Error: One or more fields missing or incorrect")
if len(errors) > 0:
return "Failed to update challenge"
else:
chal = Challenge.query.filter_by(
cid=request.form['cid']).first()
if chal:
chal.name = name
chal.category = category
chal.value = value
chal.description = desc
db.session.commit()
cid = chal.cid
#try:
files = request.files.getlist('file[]')
if files and len(files) > 0:
for f in files:
if f and len(f.filename) > 0:
#try:
upload_file(f)
new_file = File(cid, f.filename)
db.session.add(new_file)
db.session.commit()
#except:
#errors.append("Something went wrong")
else:
errors.append(
"Error: something wrong with the file or filename"
)
#except:
# errors.append("No files recieved")
db.session.close()
return redirect('/challenge/{}'.format(cid))
db.session.close()
return redirect(request.url)
else:
flash('Must be logged in to do this action')
return redirect(url_for('auth.login'))
else:
return "Failed to add challenge"
def new_entry():
if request.method == 'POST':
if logged_in():
errors = []
try:
entry_type = int(request.form['type'])
except:
errors.append("Error: missing type")
flash("Error: missing type", "error")
return redirect('/challenge/{}'.format(request.form['cid']))
chal_id = request.form['cid']
name = request.form['name']
if entry_type in range(0, 2):
desc = request.form['description']
new_entry = Entry(
chal_id,
entry_type,
name,
desc,
)
elif entry_type == 2:
if 'file' in request.files:
f = request.files['file']
if f and len(f.filename) > 0:
try:
upload_file(f)
new_entry = Entry(chal_id, entry_type, name, None,
f.filename)
except:
errors.append("Something went wrong")
else:
errors.append(
"Error: something wrong with the file or filename")
else:
errors.append("No file recieved")
else:
errors.append("Error: invalid type")
if len(errors) > 0:
return str(errors)
else:
db.session.add(new_entry)
db.session.commit()
db.session.close()
return redirect('/challenge/{}'.format(chal_id))
else:
flash('Must be logged in to do this action')
return redirect(url_for('auth.login'))
else:
return "Failed to add entry"
def upload_image():
new_uuid = '{}{}'.format(uuid.uuid4(), uuid.uuid4())
try:
utils.upload_file(request, new_uuid)
except utils.ValidationError as e:
return utils.json_response(
({
'message': 'Image Upload Failed : {}'.format(e),
}), 400)
return utils.json_response({
'message': 'Image Uploaded Successfully',
'uuid': new_uuid,
})
def baidu_wenku_download(self, msg, userId):
if not self.class_database_op.get_redis_kv(userId, 'inputing'):
self.class_database_op.set_redis_kv(userId, 'inputing', 1)
return '请输入您要下载的百度文库文档地址：'
else:
self.class_database_op.delete_redis_kv(userId, 'inputing')
current_url = msg['Content']
self.class_database_op.step_back(userId)
current_url = current_url.replace('wk.baidu.com', 'wenku.baidu.com')
current_url = current_url.replace('www.baidu.com/sf_edu_wenku', 'wenku.baidu.com')
current_url = current_url.replace('m.baidu.com/sf_edu_wenku', 'wenku.baidu.com')
if current_url.find('https://wenku.baidu.com') != 0 and current_url.find('http://wenku.baidu.com') != 0:
return "非百度文库文档地址，无法下载。"
itchatmp.send("正在为您下载该文档，请稍候。", msg['FromUserName'])
request_utils_ins = request_utils.request_utils()
file_info = request_utils_ins.baidu_wenku_download(current_url)
file_url = utils.upload_file(file_info[0], file_info[1])
import os
os.remove(file_info[0])
itchatmp.send("请接收文件~由于微信限制，机器人不能给您直接发送文件，请将以下链接复制到外部浏览器下载～", msg['FromUserName'])
return file_url
def get_exam_cal(self, msg, userId):
self.class_database_op.step_back(userId)
jwxt = self.class_database_op.get_jwxt_info(userId)
if not jwxt:
return "您还没有保存您的信息，选3来输入登录信息吧~"
itchatmp.send("正在查询，请稍候。。。", msg['FromUserName'])
request_utils_ins = request_utils.request_utils()
exams = request_utils_ins.jwxt_get_exam_list(userId)
print(exams)
cal = utils.exams_list_to_cal(exams)
file_name = 'cache/' + str(userId) + '.ics'
file_show_name = utils.random_string(32) + '.ics'
with open(file_name, 'wb') as f:
f.write(cal.to_ical())
f.close()
file_url = utils.upload_file(file_name, file_show_name)
import os
os.remove(file_name)
itchatmp.send("请接收文件~由于微信限制，机器人不能给您直接发送文件，请将以下链接复制到外部浏览器下载～", msg['FromUserName'])
return file_url
def test_disconnect_from_master():
python_script_path = os.path.join(THIS_DIR, 'jobs', 'python',
'long_running.py')
python_script_url = utils.upload_file(python_script_path)
task_id = utils.submit_job(
python_script_url,
"{} {}".format(LONG_RUNNING_FW_NUM_TASKS, LONG_RUNNING_RUN_TIME_SEC), [
"--conf", "spark.mesos.driver.failoverTimeout=1800", "--conf",
"spark.cores.max=1"
])
# Wait until executor is running
utils.wait_for_executors_running(LONG_RUNNING_FW_NAME,
LONG_RUNNING_FW_NUM_TASKS)
# Block the driver's connection to Mesos master
framework_info = shakedown.get_service(LONG_RUNNING_FW_NAME)
(driver_host, port) = _parse_fw_pid_host_port(framework_info["pid"])
_block_master_connection(driver_host, port)
# The connection will timeout after 15 minutes of inactivity.
# Add 5 minutes to make sure the master has detected the disconnection.
# The framework will be considered disconnected => failover_timeout kicks in.
LOGGER.info(
"Waiting {} seconds for connection with master to timeout...".format(
MASTER_CONNECTION_TIMEOUT_SEC))
time.sleep(MASTER_CONNECTION_TIMEOUT_SEC + 5 * 60)
# Restore the connection. The driver should reconnect.
_unblock_master_connection(driver_host)
# The executor and driver should finish.
utils.check_job_output(task_id, "Job completed successfully")
def test_r():
r_script_path = os.path.join(THIS_DIR, 'jobs', 'R', 'dataframe.R')
r_script_url = utils.upload_file(r_script_path)
utils.run_tests(app_url=r_script_url,
app_args='',
expected_output="Justin",
app_name="/spark")
def new_challenge():
if request.method == 'POST' and len(request.form) >= 6:
if logged_in():
errors = []
#try:
eid = request.form['eid']
name = request.form['name']
category = request.form['category']
value = int(request.form['value'])
desc = request.form['description']
#except:
if len(errors) > 0:
return "Failed to add challenge [2]"
else:
new_chal = Challenge(eid, name, category, desc, value)
db.session.add(new_chal)
db.session.commit()
cid = new_chal.cid
#try:
files = request.files.getlist('file[]')
if files and len(files) > 0:
for f in files:
if f and len(f.filename) > 0:
#try:
upload_file(f)
new_file = File(cid, f.filename)
db.session.add(new_file)
db.session.commit()
#except:
#errors.append("Something went wrong")
else:
errors.append(
"Error: something wrong with the file or filename"
)
#except:
# errors.append("No files recieved")
db.session.close()
return redirect('/event/{}'.format(eid))
else:
flash('Must be logged in to create challenges')
return redirect(url_for('auth.login'))
else:
return "Failed to add challenge"
async def upload(self, ctx, file_name=""):
"""Uploads a file and prints out the download url"""
if not file_name:
file_name = ctx.guild.name
path = (dirs.PDF_EXPORT_DIR / file_name).with_suffix(".pdf")
url = utils.upload_file(path)
await ctx.send(url)
def uploadFiles():
user_id = get_jwt_identity()
user = User.query.get(user_id)
teacher = user.teacher
if (not teacher):
return "Forbidden", 403
files = request.files.getlist('files')
course_id = request.form['id']
if (not files):
return 'No files', 400
added_files = []
for file in files:
if file and CourseMaterials.allowed_file(file.filename):
filename = CourseMaterials.get_filename(
secure_filename(file.filename))
dir = os.path.join('static', 'course', 'materials', course_id)
if not os.path.exists(dir):
os.makedirs(dir)
file_loc = os.path.join(dir, filename)
file.save(file_loc)
# upload to API & save record to db
try:
utils.upload_file(course_id, file_loc)
file_db = CourseMaterial(filename=filename,
course_id=int(course_id))
db.session.add(file_db)
db.session.commit()
added_files.append(filename)
except requests.exceptions.RequestException as err:
os.remove(file_loc)
db.session.rollback()
return jsonify({
'filenames':
added_files,
'status':
"not saved" if len(added_files) == 0 else 'success'
})
def install_vplx(self):
result = utils.upload_file("vplx", "/tmp", self.conn)
if result["st"]:
# cmd_pip = f'pip3 install -r /tmp/vplx/requirements.txt'
# result_pip = utils.exec_cmd(cmd_pip, self.conn)
# if not result_pip["st"]:
# print("Please install python module on /tmp/requirements.txt")
return True
def create_predictor():
# Collecting fields. Target and file are mandatories
target = request.form.get("target")
file = request.files.get("file")
employee_id = request.form.get("employee_id")
length_of_service = request.form.get("length_of_service")
age = request.form.get("age")
job_title = request.form.get("job_title")
if target is None or file is None:
abort(400)
# Save the training dataset
filename = 'data_train.csv'
upload_file(file, filename)
# Train the model
selected_feats, woe_dicts, clf, scaler, valid_metrics, dict_A5 = pandoras_box.create_predictor(
filename,
target,
employee_id=employee_id,
length_of_service=length_of_service,
age=age,
job_title=job_title)
# Save the trained model for future use
upload_object(selected_feats, "selected_feats.obj")
upload_object(woe_dicts, "woe_dicts.obj")
upload_object(clf, "clf.obj")
upload_object(scaler, "scaler.obj")
upload_object(valid_metrics, "valid_metrics.obj")
upload_object(dict_A5, "dict_A5.obj")
# Response body
response = jsonify({'Result': 'Model successfully trained'})
# Managing response CORS
response.headers.add('Access-Control-Allow-Methods',
'POST, GET, OPTIONS, DELETE, PUT')
response.headers.add('Access-Control-Max-Age', '5000')
response.headers.add(
'Access-Control-Allow-Headers',
'x-requested-with, Content-Type, Accept-Encoding, Accept-Language, Cookie, Referer'
)
response.headers.add('Access-Control-Allow-Credentials', 'true')
return response
def upload_file(request):
# if not utils.check_permission(request.user.extra, 'banner_list_index'):
# return JsonResponse(NO_PERMISSION)
if request.method == "POST":
is_ok, img_url = utils.upload_file(request, 'mysite')
if is_ok:
return JsonResponse({"status": 0, "message":"", "url": img_url}, safe = False)
else:
return JsonResponse({"status": 1, "message":"上传失败"})
def test_jar(app_name="/spark"):
master_url = ("https" if utils.is_strict() else "http") + "://leader.mesos:5050"
spark_job_runner_args = '{} dcos \\"*\\" spark:only 2 --auth-token={}'.format(
master_url,
shakedown.dcos_acs_token())
jar_url = utils.upload_file(os.getenv('TEST_JAR_PATH'))
utils.run_tests(app_url=jar_url,
app_args=spark_job_runner_args,
expected_output="All tests passed",
app_name=app_name,
args=["--class", 'com.typesafe.spark.test.mesos.framework.runners.SparkJobRunner'])
def get_group_msg_img(self, uin, info):
res = self.webqq.get_group_msg_img(uin, info)
path = tempfile.mktemp()
fp = open(path, 'wb')
fp.write(res.read())
fp.close()
filename = info.get("name")
name, typ = filename.split(".")
name = random.sample(name, 3)
filename = "{0}.{1}".format("".join(name), typ)
res = upload_file(filename, path)
return res.geturl()
def upload_to_s3(file: FileStorage,
prefix: str = 'images',
bucket: str = BUCKET) -> Tuple[bool, str, str]:
key, local_file = save_file(file)
ok, name = upload_file(key=f'{prefix}/{key}',
filename=local_file,
bucket=bucket)
if ok:
os.remove(local_file)
return ok, name, bucket
def get_check_img(self, vcode):
""" 获取验证图片 """
url = "https://ssl.captcha.qq.com/getimage"
params = [("aid", self.aid), ("r", random.random()), ("uin", self.qid)]
helper = HttpHelper(url, params, jar=http_sock.cookiejar)
res = helper.open()
path = tempfile.mktemp()
fp = open(path, 'wb')
fp.write(res.read())
fp.close()
res = upload_file("check.jpg", path)
print res.geturl()
check_code = None
while not check_code:
check_code = raw_input("打开上面连接输出图片上的验证码: ")
return check_code.strip()
def get_check_img(self, vcode):
""" 获取验证图片 """
url = "https://ssl.captcha.qq.com/getimage"
params = [("aid", self.aid), ("r", random.random()),
("uin", self.qid)]
helper = HttpHelper(url, params, jar = http_sock.cookiejar)
res = helper.open()
path = tempfile.mktemp()
fp = open(path, 'wb')
fp.write(res.read())
fp.close()
res = upload_file("check.jpg", path)
print res.geturl()
check_code = None
while not check_code:
check_code = raw_input("打开上面连接输出图片上的验证码: ")
return check_code.strip()
def export_to_ical(self, msg, userId):
self.class_database_op.step_back(userId)
itchatmp.send("正在查询，请稍候。。。", msg['FromUserName'])
card = self.class_database_op.get_jwxt_info(userId)
if not card:
return "您还没有保存您的信息，选 3 来输入登录信息吧~"
request_utils_ins = request_utils.request_utils()
results = request_utils_ins.jwxt_total_login(userId)
if not results[0]:
return "登录教务系统失败!"
lessons = request_utils_ins.jwxt_get_lesson_table(userId)
lessons_list = []
for key in lessons:
lesson = lessons[key]
if lesson['time'] != '':
time_list = lesson['time'].split(';')
room_list = lesson['room'].split(';')
for i in range(0, len(time_list)):
ret_dict = {}
ret_dict['name'] = lesson['name']
ret_dict['teacher'] = lesson['teacher_name']
key_list = re.compile(r"(.*){(.*)}",
flags=re.M).findall(time_list[i])
ret_dict['time'] = key_list[0][0]
ret_dict['week'] = key_list[0][1]
ret_dict['room'] = room_list[i]
lessons_list.append(ret_dict)
cal = utils.lessons_list_to_cal(lessons_list)
file_name = 'cache/' + str(userId) + '.ics'
file_show_name = utils.random_string(32) + '.ics'
with open(file_name, 'wb') as f:
f.write(cal.to_ical())
f.close()
file_url = utils.upload_file(file_name, file_show_name)
import os
os.remove(file_name)
itchatmp.send("请接收文件~由于微信限制，机器人不能给您直接发送文件，请将以下链接复制到外部浏览器下载～",
msg['FromUserName'])
return file_url
def get_reaction_probabilities(app, fasta_id=None, fasta_file=None):
session = session_management.get_session_id()
if session is None:
return session_management.bad_or_missing_session()
template = None
if request.method == GET:
fasta_id = request.args[FASTA_ID] if fasta_id is None else fasta_id
# check cache
if fasta_id is not None and fasta_id != '':
likelihoods = db.find_probanno(fasta_id)
if likelihoods is not None:
job = Job(session, CALCULATE_PROBANNO_JOB, fasta_id, status=COMPLETE)
# add a record of us calculating this job unless we already have
if db.retrieve_probanno(session, fasta_id) is None:
db.insert_probanno_record(fasta_id, session, likelihoods[2])
return jsonify(job.to_dict_dto())
# download fasta file from Uniprot and continue
try:
fasta_file = get_fasta_by_id(app, fasta_id) if fasta_file is None else fasta_file
except probanno.FastaNotFoundError:
return not_found(fasta_id + " not found")
template = request.args[TEMPLATE] if TEMPLATE in request.args else DEFAULT_TEMPLATE
if request.method == PUT:
fasta_id = request.form[FASTA_ID] if fasta_id is None else fasta_id
if fasta_id is None:
return missing_argument(FASTA_ID)
if FASTA in request.files:
fasta_file = app.config['UPLOAD_FOLDER'] + utils.upload_file(app, request.files[FASTA])
else:
return missing_argument(FASTA_ID)
template = request.form[TEMPLATE] if TEMPLATE in request.form else DEFAULT_TEMPLATE
template_file = TEMPLATE_FILES[template] if template in TEMPLATE_FILES else TEMPLATE_FILES[DEFAULT_TEMPLATE]
gen_id = request.args[FASTA_ID] if FASTA_ID in request.args and request.args[FASTA_ID] is not None else fasta_file
fasta_name = get_name_from_fasta(fasta_file)
template_model_file = app.config['MODEL_TEMPLATES'] + template_file
job = Job(session, CALCULATE_PROBANNO_JOB, fasta_id)
probanno_queue.enqueue(_async_get_reaction_probabilities,
job, fasta_id, fasta_name, session, fasta_file, template_model_file, gen_id,
job_id=job.id, timeout=600)
return jsonify(retrieve_job(job.id).to_dict_dto())
def load_model(app):
session = session_management.get_session_id()
if session is None:
return session_management.bad_or_missing_session()
if 'file' not in request.files:
return missing_argument('file')
file = request.files['file']
filename = utils.upload_file(app, file, ALLOWED_EXTENSIONS)
# load model w/ cobra
model = None
try:
model = cobra_modeling.from_json_file(os.path.join(app.config['UPLOAD_FOLDER'], filename))
except BaseException as e:
return bad_request("Invalid CobraPy Model. Not in proper cobra.io.json deserializable format")
os.remove(os.path.join(app.config['UPLOAD_FOLDER'], filename))
if MODEL_ID not in request.form:
return missing_argument(MODEL_ID)
model_id = request.form[MODEL_ID]
if db.find_model(session, model_id) is not None:
db.delete_model(session, model_id)
db.insert_model(session, model_id, cobra_modeling.model_to_json(model))
return Response()
def main():
# Read config file
config = ConfigParser.ConfigParser()
config.read('process_last_photo.cfg')
img_dir = config.get('Motion', 'img_dir', "/home/pi/motion")
server = config.get('Serving', 'server', "localhost:9000")
bucket_name = config.get('S3', 'bucket', "rpizero-smart-camera-archive")
user = config.get('Email', 'user')
pwd = config.get('Email', 'pwd')
# Find the latest image
files = os.listdir(img_dir)
full_paths = [os.path.join(img_dir, basename) for basename in files]
filename_local = max(full_paths, key=os.path.getctime)
# Identify objects in the picture using TensorFlow Serving
classes, scores = query_mobilenet_server(filename_local, server)
human_detected = False
print("\n".join(
["{0}: {1:.2f}".format(c, s) for (c, s) in zip(classes, scores)]))
for (c, s) in zip(classes, scores):
if c == 'person' and s > 0.5:
human_detected = True
break
print("human_detected = {}".format(human_detected))
# Upload file to S3 and remove the local copy
url = upload_file(filename_local, bucket_name, human_detected)
# Send e-mail notification
if human_detected:
subject = "Human detected"
body = "\n".join(
["{0}: {1:.2f}".format(c, s) for (c, s) in zip(classes, scores)])
body += "\n\n{}".format(url)
send_email(user, pwd, user, subject, body)
def predict():
# The csv file is mandatory:
# if it's missing you have a 'bad request' error
file = request.files.get("file")
if file is None:
abort(400)
# It is mandatory to have a trained model
# Without that, you have a 'bad request' error
if object_exists("selected_feats.obj") is False \
or object_exists("woe_dicts.obj") is False \
or object_exists("clf.obj") is False \
or object_exists("scaler.obj") is False \
or object_exists("valid_metrics.obj") is False:
abort(400)
#Save the test dataset
filename = 'data_test.csv'
employee_id = request.form.get("employee_id")
length_of_service = request.form.get("length_of_service")
age = request.form.get("age")
job_title = request.form.get("job_title")
filename = 'data_test.csv'
upload_file(file, filename)
# Download the trained model
selected_feats = download_object("selected_feats.obj")
woe_dicts = download_object("woe_dicts.obj")
clf = download_object("clf.obj")
scaler = download_object("scaler.obj")
valid_metrics = download_object("valid_metrics.obj")
# Get the predictions
score, y_hat = pandoras_box.get_prediction(
filename,
selected_feats,
woe_dicts,
clf,
scaler,
employee_id=employee_id,
length_of_service=length_of_service,
age=age,
job_title=job_title)
# Save predictions
upload_object(score, "predict_score.obj")
# Save predictions
upload_object(score, "predict_score.obj")
csv = str(employee_id) + ',score\n'
for index, row in y_hat.iterrows():
csv += str(row[employee_id]) + "," + str(row['score']) + "\n"
response = make_response(csv)
cd = 'attachment; filename=mycsv.csv'
response.headers['Content-Disposition'] = cd
response.mimetype = 'text/csv'
response.headers.add('Access-Control-Allow-Methods',
'POST, GET, OPTIONS, DELETE, PUT')
response.headers.add('Access-Control-Max-Age', '5000')
response.headers.add(
'Access-Control-Allow-Headers',
'x-requested-with, Content-Type, Accept-Encoding, Accept-Language, Cookie, Referer'
)
response.headers.add('Access-Control-Allow-Credentials', 'true')
return response
from utils import make_tarfile, upload_file, file_exists_in_bucket, purge_backups
import os
import sys
import datetime as dt
log = open("backup.log", "a")
sys.stdout = log
DIRECTORY = os.environ['BACKUP_DIR']
output_path = make_tarfile(DIRECTORY)
print('Starting job @ {}'.format(dt.datetime.now()))
print('Successfully compressed {} into {}'.format(DIRECTORY, output_path))
print('Beginning upload...')
upload_file(output_path)
if not file_exists_in_bucket(output_path):
print('\nVerification of file upload to s3 failed...exiting')
exit()
print('\nVerified file upload to s3...Cleaning up')
print('Removing backup archive {}'.format(output_path))
os.remove(output_path)
purge_backups()
def main():
# Note: It is important to import the libraries needed within the function
# so Spark does not attempt serializing the libraries to all the workers,
# otherwise it could fail during Serialization/Deserialization
# using the pickle methods.
from mxinfer import load_images
from mxinfer import predict
from utils import get_args
from utils import get_s3client
from utils import fetch_s3_keys
from utils import download_objects
from utils import upload_file
args = get_args()
logger.info('received arguments:{}'.format(args))
conf = SparkConf().setAppName("Distributed Inference using MXNet and Spark")
# we will set the number of cores per executor to 1 to force Spark to create
# only one task per executor since MXNet efficiently uses all the cpus on the
# system for inference
conf.set('spark.executor.cores', '1')
sc = pyspark.SparkContext(conf=conf)
logger.info("Spark Context created")
s3_client = get_s3client(args['access_key'], args['secret_key'])
keys = fetch_s3_keys(args['bucket'], args['prefix'], s3_client)
# filter out only png images.
# you can also choose to check the content-type headers by doing
# a head call against each S3-Key
keys = filter(lambda x: x.endswith('.png'), keys)
# number of keys
n_keys = len(keys)
if n_keys < args['batch']:
args['batch'] = n_keys
n_partitions = n_keys // args['batch']
logger.info('number of keys from s3: {}'.format(n_keys))
# if keys cannot be divided by args['batch'] .
if (n_partitions * args['batch'] != n_keys):
keys.extend(keys[: args['batch'] - (n_keys - n_partitions * args['batch'])])
logger.debug('Keys:{}'.format(keys))
n_partitions = len(keys) // args['batch']
logger.info("number of keys:{}, n_partitions:{}".format(len(keys), n_partitions))
# we will create partitions of args['batch']
rdd = sc.parallelize(keys, numSlices=n_partitions)
logger.info('created rdd with {} partitions'.format(rdd.getNumPartitions()))
sc.broadcast(args['bucket'])
rdd = rdd.mapPartitions(lambda k : download_objects(args['bucket'], k))
rdd = rdd.mapPartitions(load_images)
sc.broadcast(args)
rdd = rdd.mapPartitions(lambda imgs: predict(imgs, args))
output = rdd.collect()
# drop the extra keys that we added to fill the last batch
keys = keys[:n_keys]
output = output[:n_keys]
logger.info("predictions: {}".format(output))
if args['output_s3_key'] and args['output_s3_bucket']:
with open('/tmp/' + args['output_s3_key'] , 'w+') as f:
for k, o in zip(keys, output):
f.write("Key %s: Prediction: %s\n" % (k, o))
upload_file(args['output_s3_bucket'], args['output_s3_key'], '/tmp/' + args['output_s3_key'], s3_client)
def upload_repositories_file(repositories_file):
utils.print_group("Uploading {} file".format(repositories_file))
utils.upload_file(repositories_file)
def save_user_content():
if not request.files:
abort(400, 'No files present!')
must_have_key_list = ['title',
'description',
'creator_name']
form = request.form
keys = form.keys()
# Check that we have a full language specific set of fields
must_have_keys = {
'_en': {'missing': None, 'error': None},
'_he': {'missing': None, 'error': None}
}
for lang in must_have_keys:
must_have_list = [k+lang for k in must_have_key_list]
must_have_set = set(must_have_list)
must_have_keys[lang]['missing'] = list(must_have_set.difference(set(keys)))
if must_have_keys[lang]['missing']:
missing_keys = must_have_keys[lang]['missing']
must_have_keys[lang]['error'] = gen_missing_keys_error(missing_keys)
if must_have_keys['_en']['missing'] and must_have_keys['_he']['missing']:
em_base = 'You must provide a full list of keys in English or Hebrew. '
em = em_base + must_have_keys['_en']['error'] + ' ' + must_have_keys['_he']['error']
abort(400, em)
# Set metadata language(s) to the one(s) without missing fields
md_languages = []
for lang in must_have_keys:
if not must_have_keys[lang]['missing']:
md_languages.append(lang)
user_oid = current_user.id
file_obj = request.files['file']
filename = secure_filename(file_obj.filename)
metadata = dict(form)
metadata['user_id'] = str(user_oid)
metadata['original_filename'] = filename
metadata['Content-Type'] = mimetypes.guess_type(filename)[0]
# Pick the first item for all the list fields in the metadata
clean_md = {}
for key in metadata:
if type(metadata[key]) == list:
clean_md[key] = metadata[key][0]
else:
clean_md[key] = metadata[key]
# Make sure there are no empty keys for at least one of the md_languages
empty_keys = {'_en': [], '_he': []}
for lang in md_languages:
for key in clean_md:
if key.endswith(lang):
if not clean_md[key]:
empty_keys[lang].append(key)
# Check for empty keys of the single language with the full list of fields
if len(md_languages) == 1 and empty_keys[md_languages[0]]:
abort(400, "'{}' field couldn't be empty".format(empty_keys[md_languages[0]][0]))
# Check for existence of empty keys in ALL the languages
elif len(md_languages) > 1:
if (empty_keys['_en'] and empty_keys['_he']):
abort(400, "'{}' field couldn't be empty".format(empty_keys[md_languages[0]][0]))
# Create a version of clean_md with the full fields only
full_md = {}
for key in clean_md:
if clean_md[key]:
full_md[key] = clean_md[key]
# Get the magic file info
file_info_str = magic.from_buffer(file_obj.stream.read())
if not _validate_filetype(file_info_str):
abort(415, "File type '{}' is not supported".format(file_info_str))
# Rewind the file object
file_obj.stream.seek(0)
# Convert user specified metadata to BHP6 format
bhp6_md = _convert_meta_to_bhp6(clean_md, file_info_str)
bhp6_md['owner'] = str(user_oid)
# Create a thumbnail and add it to bhp metadata
try:
binary_thumbnail = binarize_image(file_obj)
bhp6_md['thumbnail'] = {}
bhp6_md['thumbnail']['data'] = urllib.quote(binary_thumbnail.encode('base64'))
except IOError as e:
current_app.logger.debug('Thumbnail creation failed for {} with error: {}'.format(
file_obj.filename, e.message))
# Add ugc flag to the metadata
bhp6_md['ugc'] = True
# Insert the metadata to the ugc collection
new_ugc = Ugc(bhp6_md)
new_ugc.save()
file_oid = new_ugc.id
bucket = ugc_bucket
saved_uri = upload_file(file_obj, bucket, file_oid, full_md, make_public=True)
user_email = current_user.email
user_name = current_user.name
if saved_uri:
console_uri = 'https://console.developers.google.com/m/cloudstorage/b/{}/o/{}'
http_uri = console_uri.format(bucket, file_oid)
mjs = get_mjs(user_oid)['mjs']
if mjs == {}:
current_app.logger.debug('Creating mjs for user {}'.format(user_email))
# Add main_image_url for images (UnitType 1)
if bhp6_md['UnitType'] == 1:
ugc_image_uri = 'https://storage.googleapis.com/' + saved_uri.split('gs://')[1]
new_ugc['ugc']['main_image_url'] = ugc_image_uri
new_ugc.save()
# Send an email to editor
subject = 'New UGC submission'
with open('editors_email_template') as fh:
template = jinja2.Template(fh.read())
body = template.render({'uri': http_uri,
'metadata': clean_md,
'user_email': user_email,
'user_name': user_name})
sent = send_gmail(subject, body, editor_address, message_mode='html')
if not sent:
current_app.logger.error('There was an error sending an email to {}'.format(editor_address))
clean_md['item_page'] = '/item/ugc.{}'.format(str(file_oid))
return humanify({'md': clean_md})
else:
abort(500, 'Failed to save {}'.format(filename))
def setup_module(module):
if utils.hdfs_enabled():
utils.require_hdfs()
utils.require_spark()
utils.upload_file(os.environ["SCALA_TEST_JAR_PATH"])