I am trying to implement a parent/child configuration in mpi4py.
My goal is
parent : will run on 1 core
child : will run on N cores
I am trying to send data from parent to child's rank=0.
tried this:
master:
from mpi4py import MPI
import sys
def main():
datafileopls='MEDIUM2_opls.lmp'
lammpscomm = MPI.COMM_SELF.Spawn(sys.executable,
args=['/storage/home/duy42/Developer/MLReax/Src3/lammps_driver.py'
],maxprocs=9)
lammpscomm.send(datafileopls,0,0)
current_step = lammpscomm.recv(None,0,0)
print(current_step)
lammpscomm.Disconnect()
if __name__ =='__main__':
main()
Child:
def main():
parent = MPI.Comm.Get_parent()
comm = MPI.COMM_WORLD
assert parent != MPI.COMM_NULL
try:
status = MPI.Status()
any_src , any_tag = MPI.ANY_SOURCE, MPI.ANY_TAG
print(parent.Get_rank(),comm.Get_rank(),status.source)
if comm.Get_rank() == 0:
print('LAMMPS DRIVER CONNECTED')
datafileopls = parent.recv(None,any_src, any_tag, status)
current_step = 123
parent.send(current_step,status.source,0)
finally:
parent.Disconnect()
print('All done')
return
if __name__ == "__main__":
main()
the code hangs before sending data to parent.
What I am missing here?
Thanks in advance.
Related
I have a TreeView which is displaying items from an AbstractItemModel..
Now I wanted to add extra Filter functionality to my application, but somehow, the data is not visible in the TreeView (after calling newData()).
How does the interaction between the QAbstractItemModel and the QSortFilterProxyModel happens?
what should the QSortFilterProxyModel knows more the the setSource(QAbstractItemModel)
Here my code (copied from: https://stackoverflow.com/a/60910989/298487)
import logging
import sys
from PySide6 import QtCore, QtWidgets
from PySide6.QtCore import QSortFilterProxyModel
class DBObject:
def __init__(self, name, parent, children=None):
self.name = name
self.parent = parent
self.children = children or list()
def __repr__(self):
return f"name: {self.name}, parent: {self.parent.name if self.parent is not None else '-'}"
class Model(QtCore.QAbstractItemModel):
def __init__(self, parent=None):
super().__init__(parent)
self._root = DBObject("root", None)
def newData(self):
items = ["foo", "bar", "baz"]
for x in items:
child = DBObject(x + "0", self._root)
self._root.children.append(child)
for y in items:
child.children.append(DBObject(y + "1", child))
def columnCount(self, parent=QtCore.QModelIndex()):
return 1
def rowCount(self, parent=QtCore.QModelIndex()):
if not parent.isValid():
return 1
parentItem = parent.internalPointer()
rowCount = len(parentItem.children)
logging.info(f"rowCount({parentItem}): rowCount={rowCount}")
return rowCount
def parent(self, index):
if not index.isValid():
return QtCore.QModelIndex()
item = index.internalPointer()
parentItem = item.parent
logging.info(f"parent({item}): parent={parentItem}")
if parentItem is None:
return QtCore.QModelIndex()
else:
if parentItem.parent is None:
return self.createIndex(0, 0, parentItem)
else:
return self.createIndex(parentItem.parent.children.index(parentItem), 0, parentItem)
def index(self, row, column, parent=QtCore.QModelIndex()):
if not parent.isValid():
if row != 0 or column != 0:
return QtCore.QModelIndex()
else:
logging.info(f"index({row}, {column}, None): index={self._root}")
return self.createIndex(0, 0, self._root)
parentItem = parent.internalPointer()
if 0 <= row < len(parentItem.children):
logging.info(f"index({row}, {column}, {parentItem}): index={parentItem.children[row]}")
return self.createIndex(row, column, parentItem.children[row])
else:
logging.info(f"index({row}, {column}, {parentItem}): index=None")
return QtCore.QModelIndex()
def data(self, index, role=QtCore.Qt.ItemDataRole.DisplayRole):
if not index.isValid():
return None
item = index.internalPointer()
if role == QtCore.Qt.ItemDataRole.DisplayRole:
return item.name
else:
return None
def flags(self, index):
if not index.isValid():
return QtCore.Qt.ItemFlag.NoItemFlags
return (
QtCore.Qt.ItemFlag.ItemIsEnabled
| QtCore.Qt.ItemFlag.ItemIsSelectable)
class ProxyModel(QSortFilterProxyModel):
def __init__(self, parent=None):
super().__init__(parent)
self.setFilterKeyColumn(0)
self.setRecursiveFilteringEnabled(True)
class MainWindow(QtWidgets.QMainWindow):
def __init__(self):
super().__init__()
self.setMinimumSize(640, 480)
centralWidget = QtWidgets.QWidget(self)
self.setCentralWidget(centralWidget)
layout = QtWidgets.QVBoxLayout(centralWidget)
self._treeView = QtWidgets.QTreeView(self)
layout.addWidget(self._treeView)
self._model = Model()
self._proxyModel = ProxyModel()
self._proxyModel.setSourceModel(self._model)
# this line will not work
self._treeView.setModel(self._proxyModel)
# if i replace it with this line, it is working
# but the filtering will not work
self._treeView.setModel(self._model)
self._proxyModel.setFilterFixedString("bar1")
button = QtWidgets.QPushButton("Add")
layout.addWidget(button)
button.clicked.connect(self._Clicked)
def _Clicked(self):
self._model.newData()
self._treeView.expandAll()
def main():
app = QtWidgets.QApplication(sys.argv)
mainWindow = MainWindow()
mainWindow.show()
app.exec()
if __name__ == "__main__":
main()
Instead of defining a Bitbucket Cloud workspace variable that can be used by all the repos in the workspace, someone defined it in each repo, but not in all of them, of the workspace. Now I want to remove the variable in the individual repos, and define it in the workspace.
Is there a Bitbucket API that would do this pseudo-code?
def bb = Bitbucket.getInstance()
String workspace = "MyWorkspace"
String myVariable = "NEXUS_USER"
List<Repository> reposInWorkspace = bb.getWorkspace(workspace).getAllReposInWorkspace()
reposInWorkspace.each { repo ->
if (repo.hasVariable(myVariable)) {
println repo.name
}
}
I put a Bitbucket support ticket, and a sharp Atlassian support person gave me this Python3 script
from requests import Session
from time import sleep
username = 'your_username_not_email'
password = 'app_pw_not_bb_user_pw'
workspace = 'your_workspace'
variable_name = 'your_variable'
URL = f'https://api.bitbucket.org/2.0/repositories/{workspace}'
session = Session()
session.auth = (username, password)
def get_repos(page=None):
while True:
params = {'page': page, 'pagelen': 100}
r = session.get(URL, params=params)
while r.status_code == 429:
print("Hit the API rate limit. Sleeping for 10 sec...")
sleep(10)
print("Resuming...")
r = session.get(URL, params=params)
r_data = r.json()
for repo in r_data.get('values'):
yield repo.get('slug')
if not r_data.get('next'):
return
if page is None:
page = 1
page += 1
def get_variables(repo, page=None):
while True:
params = {'page': page, 'pagelen': 100}
r = session.get(f'{URL}/{repo}/pipelines_config/variables/', params=params)
while r.status_code == 429:
print("Hit the API rate limit. Sleeping for 10 sec...")
sleep(10)
print("Resuming...")
r = session.get(URL, params=params)
r_data = r.json()
for var in r_data.get('values'):
yield var.get('key')
if not r_data.get('next'):
return
if page is None:
page = 1
page += 1
def has_variable(var):
if var == variable_name:
return True
def main():
for repo in get_repos():
for var in get_variables(repo):
if has_variable(var):
print(f'{repo}')
if __name__ == '__main__':
main()
app.py
from flask import Flask, jsonify, request,render_template
import pickle
app = Flask(__name__,template_folder='template')
# load model
model = pickle.load(open("model.pkl",'rb'))
# app
#app.route('/')
def home():
return render_template('recommendation.html')
# routes
#app.route('/api', methods=['POST'])
def predict():
result=request.form
query_user_name=result["user name"]
user_input = {'query':query_user_name}
output_data=model(query_user_name)
print(output_data)
# send back to browser
output ={output_data}
return f'<html><body><h1>{output_data}</h1><form action="/"><button type="submit">back </button> </form></body></html>'
if __name__ == '__main__':
app.run(debug=True)
I am deploying it using a model made from following function,not a pre-existing model having predict attribute.
def model(user):
recommended_list=[]
top_list=[]
x = data.iloc[data.loc[data.Users == user].index[0],2:]
similar = np.array([(data.iloc[i,0],weight_factor(x,data.iloc[i, 2:])) for i in range(0,data.shape[0],1)])
index= np.argsort( similar[:,1] )
index=index[::-1]
similar=similar[index]
neighbours = similar[similar[:,1].astype(float) > 0.6] #Taking threshold as 0.6
for i in range(0,len(neighbours),1):
for j in range(2,len(data.columns),1):
if data.iloc[data.loc[data.Users == neighbours[i][0]].index[0],j]==1 and data.iloc[data.loc[data.Users == user].index[0],j]==0:
recommended_list.append(data.columns[j])
if (len(neighbours)>10):
for i in range(0,10,1): #Top 10 neighbours
top_list.append(neighbours[i][0])
else:
for i in range(len(neighbours)):
top_list.append(neighbours[i][0])
if user in top_list: #Remove the user of which we are asked to find neighbours,each user is always strongly correlated with itself and its of no use to us.
top_list.remove(user)
print(" ")
print("Top users similar to this user are:")
print(" ")
for i in range(0,len(top_list),1):
print(top_list[i])
print(" ")
print("Users similar to this user liked these products too:")
print(" ")
recommended_array=np.unique(np.array(recommended_list))
for i in range(0,len(recommended_array),1):
print(recommended_array[i])
How to deploy it using flask,my output is not being shown in the window,though on deploying the home page is being shown and input is being taken.
your function "model(user)" must return somethings
example:
def model(user):
# code
return somethings
I can't use self in a class.It seems that the data of the function after the decorator is the first parameter.
Example:
import socketio
import random
sio = socketio.Client()
class Test:
def __init__(self):
self.uid = random.randint(0, 10)
#sio.on('test')
def test(self, message):
test_message = str(self.uid) + message
print(test_message)
#staticmethod
def run():
sio.connect('ws://127.0.0.1:5000')
sio.wait()
if __name__ == '__main__':
test = Test()
test.run()
Error：
TypeError: test() missing 1 required positional argument: 'message'
By：miguelgrinberg
Right, so how is Socket.IO going to know that the value for self should be this test object you created near the bottom of the file? When you set up your handlers in this way there is really no link to the actual instance of the Test class.
Try setting the handlers once the class has been instantiated, maybe something like this:
def run(self):
sio.on('test', self.test)
sio.connect('ws://127.0.0.1:5000')
sio.wait()
Soooo I have been working on a script I took from ArcGIS Blueprints:
http://file.allitebooks.com/20151230/ArcGIS%20Blueprints.pdf
It should convert geolocated tweets into a geodatabase. I have the Twitter Streaming API already operational, and been playing with different ways to extract x/y, but keep coming back to this script, every so often, hoping I can get it running with no luck. I am stuck on a "List Index Out of Range" error. If anyone is gracious enough to offer some ideas on how I can get by this error I will be forever grateful. If nothing else this endeavor has exploited my shortcomings with Python and Arcpy, and hopefully it will round me out in the long run. For right now, I sure would like to get some mileage out of this script and the work Ive invested into it. Thank you!
from tweepy.streaming import StreamListener
from tweepy import OAuthHandler
from tweepy import Stream
import arcpy
import sys
import time
consumer_key = 'xxx'
consumer_secret = 'xxx'
token_key = 'xxx'
token_secret = 'xxx'
class StdOutListener(StreamListener):
def __init__(self, start_time, featureClass, time_limit):
super(StdOutListener, self).__init__()
self.time = start_time
self.limit = time_limit
self.featureClass = featureClass
def on_status(self, status):
while (time.time() - self.time) < self.limit:
if status.geo is not None:
dictCoords = status.geo
listCoords = dictCoords['coordinates']
latitude = listCoords[0]
longitude = listCoords[1]
cursor =arcpy.da.InsertCursor(self.featureClass,"SHAPE#XY"))
cursor.insertRow([(longitude,latitude)])
print(str(listCoords[0]) + "," + str(listCoords[1]))
return True
else:
print "No coordinates found"
return True
start_time = time.time()
arcpy.env.workspace = "c:\ArcGIS_Blueprint_Python\data\Twitter\TweetInformation.gdb" "
def main():
try: #new
featureClass = sys.argv[1]
monitorTime = sys.argv[2]
monitorTime = monitorTime * 3600
sr = arcpy.SpatialReference(4326)
arcpy.env.overwriteOutput = True
arcpy.CreateFeatureclass_management(arcpy.env.workspace,
featureClass, "POINT", spatial_reference=sr)
auth = OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(token_key, token_secret)
stream = Stream(auth, StdOutListener(start_time, featureClass,
time_limit=monitorTime)) #172800
stream.filter(track=['car'])
except Exception as e:
print(e.message)
if __name__ == '__main__':
main()