i am having a simple app example here:
say i have this piece of code which handles requests from user to get a list of books stored in a database.
from .handlers import all_books
#apps.route('/show/all', methods=['GET'])
#jwt_required
def show_books():
user_name = get_jwt_identity()['user_name']
all_books(user_name=user_name)
and in handlers.py i have :
def all_books(user_name):
db = get_db('books')
books = []
for book in db.books.find():
books.append(book)
return books
but while writing unit tests i realised if i use get_db() inside all_books() it would be harder to unit test the method.
so i thought this would be the good way.
from .handlers import all_books
#apps.route('/show/all', methods=['GET'])
#jwt_required
def show_books():
user_name = get_jwt_identity()['user_name']
db = get_db('books')
collection = db.books
all_books(collection=collection)
def all_books(collection):
books = []
for book in collection.find():
books.append(book)
return books
i want to know what is the good design to use?
have all code doing one thing at one place like the first example or the second example is good.
To me first one seems more clear as it has all related logic at one place. but its easier to pass a fake collection in second case to unit test it.
you should probably use the mock library see: https://docs.python.org/3/library/unittest.mock.html#quick-guide
(if you use python2 you will need pip install mock)
def test_it():
from unittest.mock import Mock,patch
with patch.object(get_db,'function',Mock(return_value=Mock(books=[1,2,3]))) as mocked_db:
x = get_db("ASDASD")
console.log(x.books)
# you can also do cool stuff like this
assert mocked_db.calledwith("ASDASD")
of coarse for yours you will have to construct a slightly more complex object
my_mocked_get_db = Mock(return_value=Mock(books=Mock(find=[1,2,3,4])))
with patch.object(get_db,'function',my_mocked_get_db) as mocked_db:
x = get_db("ASDASD")
print(x.books.find())
I am trying to add memcache to my webapp deployed on GAE, and to do this I am using memcache.Client() to prevent damage from any racing conditions:
from google.appengine.api import memcache
client = memcache.Client()
class BlogFront(BlogHandler):
def get(self):
global client
val = client.gets(FRONT_PAGE_KEY)
posts = list()
if val is not None:
posts = list(val)
else:
posts = db.GqlQuery("select * from Post order by created desc limit 10")
client.cas(FRONT_PAGE_KEY, list(posts))
self.render('front.html', posts = posts)
To test the problem I have a front page for a blog that displays the 10 most recent entries. If there is nothing in the cache, I hit the DB with a request, otherwise I just present the cached results to the user.
The problem is that no matter what I do, I always get val == None, thus meaning that I always hit the database with a useless request.
I have sifted through the documentation:
https://developers.google.com/appengine/docs/python/memcache/
https://developers.google.com/appengine/docs/python/memcache/clientclass
http://neopythonic.blogspot.pt/2011/08/compare-and-set-in-memcache.html
And it appears that I am doing everything correctly. What am I missing?
(PS: I am a python newb, if this is a retarded error, please bear with me xD )
from google.appengine.api import memcache
class BlogFront(BlogHandler):
def get(self):
client = memcache.Client()
client.gets(FRONT_PAGE_KEY)
client.cas(FRONT_PAGE_KEY, 'my content')
For a reason I cannot yet possible understand, the solution lies in having a gets right before having a cas call ...
I think I will stick with the memcache non-thread-safe version of the code for now ...
I suspect that the client.cas call is failing because there is no object. Perhaps client.cas only works to update and existing object (not to set a new object if there is none currently)? You might try client.add() (which will fail if an object already exists with the specified key, which I think is what you want?) instead of client.cas()
I'm having some problems using SQLAlchemy in Pyramid. Although I can find examples of what I need, they're normally very short and lacking. So I've ended up with patchy code that barely makes any sense. So I'm hoping someone could give a fuller example of what I need to do.
I have 4 databases all with the same schema. I want to be able to work on them from one Pyramid app, sometimes listing all "orders" from all 4 databases, sometimes just listing all "orders" from "site1". As the schemas are the same, I also use the same model classes for the databases.
I've tried it with both sqlahelper and plain SQLAlchemy with no luck. The code below uses sqlahelper but I'm happy to use anything that works:
__init__.py
site1_eng = engine_from_config(settings, prefix='site1.')
site2_eng = engine_from_config(settings, prefix='site2.')
site3_eng = engine_from_config(settings, prefix='site3.')
sqlahelper.add_engine(site1_eng, 'site1_eng')
sqlahelper.add_engine(site2_eng, 'site2_eng')
views.py
def site_orders(request):
site = request.matchdict['site']
db_eng = sqlahelper.get_engine(("%s_eng" % (site)))
conn = db_eng.connect()
dbsession = sqlahelper.get_session()
dbsession.configure(bind=conn)
orders = dbsession.query(Order).order_by(Order.cdate.desc())[:100]
return dict(orders=orders, pagetitle=(site+" Orders"))
What Happens?
Well I'd hoped it would switch database depending on the URL and it does! However, it seems completely random as to which is chooses. So /orders/site1/ will sometimes go to site2 database and sometimes site3. Refreshing will often switch the database it chooses each time. Same for other URL's.
Its almost as if the session isn't binding to the database and its picking whichever happens to be in the session at the time? That may not make sense - my understanding of SQLAlchemy isn't great.
Really hope someone can help as it all hinges on the ability to quickly and easily switch databases within a view and at the moment it seems completely impossible to control it.
NOTE:
I did originally try following and altering the Pyramid SQLA+URL Dispatcher tutorial which used:
DBSession = scoped_session(sessionmaker(extension=ZopeTransactionExtension()))
But I removed that when finding sqlahelper. If I should be using it let me know.
Configuring and connection for each request seems like a lot of work to me. I would create four session handlers in my model module and just choose from them.
Example:
models/__init__.py
DBSession1 = scoped_session(sessionmaker(extension=ZopeTransactionExtension()))
DBSession2 = scoped_session(sessionmaker(extension=ZopeTransactionExtension()))
DBSession3 = scoped_session(sessionmaker(extension=ZopeTransactionExtension()))
DBSession4 = scoped_session(sessionmaker(extension=ZopeTransactionExtension()))
metadata1 = MetaData()
metadata2 = MetaData()
metadata3 = MetaData()
metadata4 = MetaData()
def initialize_sql(engines, drop_db=False):
DBSession1.configure(bind=engine[0])
DBSession2.configure(bind=engine[1])
DBSession3.configure(bind=engine[2])
DBSession4.configure(bind=engine[3])
metadata1.bind = engine[0]
metadata2.bind = engine[1]
metadata3.bind = engine[2]
metadata4.bind = engine[3]
and then in your view:
from mypackage.models import DBSession1, DBSession2, DBSession3, DBSession4
def site_orders(request)
site = request.matchdict['site']
dbsession = globals().get("DBSession%d" % site)
orders = dbsession.query(Order).order_by(Order.cdate.desc())[:100]
return dict(orders=orders, pagetitle=(site+" Orders"))
You can set engine to the sqlalchemy session directly
Example for listing all "orders" from all 4 databases:
def site_orders(request):
...
orders = []
for engine in engines:
dbsession.bind = engine
orders += dbsession.query(Order).order_by(Order.cdate.desc())[:100]
return dict(orders=orders, pagetitle=(site+" Orders"))
I'm brand new at Python and I'm trying to write an extension to an app that imports GA information and parses it into MySQL. There is a shamfully sparse amount of infomation on the topic. The Google Docs only seem to have examples in JS and Java...
...I have gotten to the point where my user can authenticate into GA using SubAuth. That code is here:
import gdata.service
import gdata.analytics
from django import http
from django import shortcuts
from django.shortcuts import render_to_response
def authorize(request):
next = 'http://localhost:8000/authconfirm'
scope = 'https://www.google.com/analytics/feeds'
secure = False # set secure=True to request secure AuthSub tokens
session = False
auth_sub_url = gdata.service.GenerateAuthSubRequestUrl(next, scope, secure=secure, session=session)
return http.HttpResponseRedirect(auth_sub_url)
So, step next is getting at the data. I have found this library: (beware, UI is offensive) http://gdata-python-client.googlecode.com/svn/trunk/pydocs/gdata.analytics.html
However, I have found it difficult to navigate. It seems like I should be gdata.analytics.AnalyticsDataEntry.getDataEntry(), but I'm not sure what it is asking me to pass it.
I would love a push in the right direction. I feel I've exhausted google looking for a working example.
Thank you!!
EDIT: I have gotten farther, but my problem still isn't solved. The below method returns data (I believe).... the error I get is: "'str' object has no attribute '_BecomeChildElement'" I believe I am returning a feed? However, I don't know how to drill into it. Is there a way for me to inspect this object?
def auth_confirm(request):
gdata_service = gdata.service.GDataService('iSample_acctSample_v1.0')
feedUri='https://www.google.com/analytics/feeds/accounts/default?max-results=50'
# request feed
feed = gdata.analytics.AnalyticsDataFeed(feedUri)
print str(feed)
Maybe this post can help out. Seems like there are not Analytics specific bindings yet, so you are working with the generic gdata.
I've been using GA for a little over a year now and since about April 2009, i have used python bindings supplied in a package called python-googleanalytics by Clint Ecker et al. So far, it works quite well.
Here's where to get it: http://github.com/clintecker/python-googleanalytics.
Install it the usual way.
To use it: First, so that you don't have to manually pass in your login credentials each time you access the API, put them in a config file like so:
[Credentials]
google_account_email = youraccount#gmail.com
google_account_password = yourpassword
Name this file '.pythongoogleanalytics' and put it in your home directory.
And from an interactive prompt type:
from googleanalytics import Connection
import datetime
connection = Connection() # pass in id & pw as strings **if** not in config file
account = connection.get_account(<*your GA profile ID goes here*>)
start_date = datetime.date(2009, 12, 01)
end_data = datetime.date(2009, 12, 13)
# account object does the work, specify what data you want w/
# 'metrics' & 'dimensions'; see 'USAGE.md' file for examples
account.get_data(start_date=start_date, end_date=end_date, metrics=['visits'])
The 'get_account' method will return a python list (in above instance, bound to the variable 'account'), which contains your data.
You need 3 files within the app. client_secrets.json, analytics.dat and google_auth.py.
Create a module Query.py within the app:
class Query(object):
def __init__(self, startdate, enddate, filter, metrics):
self.startdate = startdate.strftime('%Y-%m-%d')
self.enddate = enddate.strftime('%Y-%m-%d')
self.filter = "ga:medium=" + filter
self.metrics = metrics
Example models.py: #has the following function
import google_auth
service = googleauth.initialize_service()
def total_visit(self):
object = AnalyticsData.objects.get(utm_source=self.utm_source)
trial = Query(object.date.startdate, object.date.enddate, object.utm_source, ga:sessions")
result = service.data().ga().get(ids = 'ga:<your-profile-id>', start_date = trial.startdate, end_date = trial.enddate, filters= trial.filter, metrics = trial.metrics).execute()
total_visit = result.get('rows')
<yr save command, ColumnName.object.create(data=total_visit) goes here>
I would like to wipe out all data for a specific kind in Google App Engine. What is the
best way to do this?
I wrote a delete script (hack), but since there is so much data is
timeout's out after a few hundred records.
I am currently deleting the entities by their key, and it seems to be faster.
from google.appengine.ext import db
class bulkdelete(webapp.RequestHandler):
def get(self):
self.response.headers['Content-Type'] = 'text/plain'
try:
while True:
q = db.GqlQuery("SELECT __key__ FROM MyModel")
assert q.count()
db.delete(q.fetch(200))
time.sleep(0.5)
except Exception, e:
self.response.out.write(repr(e)+'\n')
pass
from the terminal, I run curl -N http://...
You can now use the Datastore Admin for that: https://developers.google.com/appengine/docs/adminconsole/datastoreadmin#Deleting_Entities_in_Bulk
If I were a paranoid person, I would say Google App Engine (GAE) has not made it easy for us to remove data if we want to. I am going to skip discussion on index sizes and how they translate a 6 GB of data to 35 GB of storage (being billed for). That's another story, but they do have ways to work around that - limit number of properties to create index on (automatically generated indexes) et cetera.
The reason I decided to write this post is that I need to "nuke" all my Kinds in a sandbox. I read about it and finally came up with this code:
package com.intillium.formshnuker;
import java.io.IOException;
import java.util.ArrayList;
import javax.servlet.http.HttpServlet;
import javax.servlet.http.HttpServletRequest;
import javax.servlet.http.HttpServletResponse;
import com.google.appengine.api.datastore.Key;
import com.google.appengine.api.datastore.Query;
import com.google.appengine.api.datastore.Entity;
import com.google.appengine.api.datastore.FetchOptions;
import com.google.appengine.api.datastore.DatastoreService;
import com.google.appengine.api.datastore.DatastoreServiceFactory;
import com.google.appengine.api.labs.taskqueue.QueueFactory;
import com.google.appengine.api.labs.taskqueue.TaskOptions.Method;
import static com.google.appengine.api.labs.taskqueue.TaskOptions.Builder.url;
#SuppressWarnings("serial")
public class FormsnukerServlet extends HttpServlet {
public void doGet(final HttpServletRequest request, final HttpServletResponse response) throws IOException {
response.setContentType("text/plain");
final String kind = request.getParameter("kind");
final String passcode = request.getParameter("passcode");
if (kind == null) {
throw new NullPointerException();
}
if (passcode == null) {
throw new NullPointerException();
}
if (!passcode.equals("LONGSECRETCODE")) {
response.getWriter().println("BAD PASSCODE!");
return;
}
System.err.println("*** deleting entities form " + kind);
final long start = System.currentTimeMillis();
int deleted_count = 0;
boolean is_finished = false;
final DatastoreService dss = DatastoreServiceFactory.getDatastoreService();
while (System.currentTimeMillis() - start < 16384) {
final Query query = new Query(kind);
query.setKeysOnly();
final ArrayList<Key> keys = new ArrayList<Key>();
for (final Entity entity: dss.prepare(query).asIterable(FetchOptions.Builder.withLimit(128))) {
keys.add(entity.getKey());
}
keys.trimToSize();
if (keys.size() == 0) {
is_finished = true;
break;
}
while (System.currentTimeMillis() - start < 16384) {
try {
dss.delete(keys);
deleted_count += keys.size();
break;
} catch (Throwable ignore) {
continue;
}
}
}
System.err.println("*** deleted " + deleted_count + " entities form " + kind);
if (is_finished) {
System.err.println("*** deletion job for " + kind + " is completed.");
} else {
final int taskcount;
final String tcs = request.getParameter("taskcount");
if (tcs == null) {
taskcount = 0;
} else {
taskcount = Integer.parseInt(tcs) + 1;
}
QueueFactory.getDefaultQueue().add(
url("/formsnuker?kind=" + kind + "&passcode=LONGSECRETCODE&taskcount=" + taskcount).method(Method.GET));
System.err.println("*** deletion task # " + taskcount + " for " + kind + " is queued.");
}
response.getWriter().println("OK");
}
}
I have over 6 million records. That's a lot. I have no idea what the cost will be to delete the records (maybe more economical not to delete them). Another alternative would be to request a deletion for the entire application (sandbox). But that's not realistic in most cases.
I decided to go with smaller groups of records (in easy query). I know I could go for 500 entities, but then I started receiving very high rates of failure (re delete function).
My request from GAE team: please add a feature to delete all entities of a kind in a single transaction.
Presumably your hack was something like this:
# Deleting all messages older than "earliest_date"
q = db.GqlQuery("SELECT * FROM Message WHERE create_date < :1", earliest_date)
results = q.fetch(1000)
while results:
db.delete(results)
results = q.fetch(1000, len(results))
As you say, if there's sufficient data, you're going to hit the request timeout before it gets through all the records. You'd have to re-invoke this request multiple times from outside to ensure all the data was erased; easy enough to do, but hardly ideal.
The admin console doesn't seem to offer any help, as (from my own experience with it), it seems to only allow entities of a given type to be listed and then deleted on a page-by-page basis.
When testing, I've had to purge my database on startup to get rid of existing data.
I would infer from this that Google operates on the principle that disk is cheap, and so data is typically orphaned (indexes to redundant data replaced), rather than deleted. Given there's a fixed amount of data available to each app at the moment (0.5 GB), that's not much help for non-Google App Engine users.
Try using App Engine Console then you dont even have to deploy any special code
I've tried db.delete(results) and App Engine Console, and none of them seems to be working for me. Manually removing entries from Data Viewer (increased limit up to 200) didn't work either since I have uploaded more than 10000 entries. I ended writing this script
from google.appengine.ext import db
from google.appengine.ext import webapp
from google.appengine.ext.webapp.util import run_wsgi_app
import wsgiref.handlers
from mainPage import YourData #replace this with your data
class CleanTable(webapp.RequestHandler):
def get(self, param):
txt = self.request.get('table')
q = db.GqlQuery("SELECT * FROM "+txt)
results = q.fetch(10)
self.response.headers['Content-Type'] = 'text/plain'
#replace yourapp and YouData your app info below.
self.response.out.write("""
<html>
<meta HTTP-EQUIV="REFRESH" content="5; url=http://yourapp.appspot.com/cleanTable?table=YourData">
<body>""")
try:
for i in range(10):
db.delete(results)
results = q.fetch(10, len(results))
self.response.out.write("<p>10 removed</p>")
self.response.out.write("""
</body>
</html>""")
except Exception, ints:
self.response.out.write(str(inst))
def main():
application = webapp.WSGIApplication([
('/cleanTable(.*)', CleanTable),
])
wsgiref.handlers.CGIHandler().run(application)
The trick was to include redirect in html instead of using self.redirect. I'm ready to wait overnight to get rid of all the data in my table. Hopefully, GAE team will make it easier to drop tables in the future.
The official answer from Google is that you have to delete in chunks spread over multiple requests. You can use AJAX, meta refresh, or request your URL from a script until there are no entities left.
The fastest and efficient way to handle bulk delete on Datastore is by using the new mapper API announced on the latest Google I/O.
If your language of choice is Python, you just have to register your mapper in a mapreduce.yaml file and define a function like this:
from mapreduce import operation as op
def process(entity):
yield op.db.Delete(entity)
On Java you should have a look to this article that suggests a function like this:
#Override
public void map(Key key, Entity value, Context context) {
log.info("Adding key to deletion pool: " + key);
DatastoreMutationPool mutationPool = this.getAppEngineContext(context)
.getMutationPool();
mutationPool.delete(value.getKey());
}
One tip. I suggest you get to know the remote_api for these types of uses (bulk deleting, modifying, etc.). But, even with the remote api, batch size can be limited to a few hundred at a time.
Unfortunately, there's no way to easily do a bulk delete. Your best bet is to write a script that deletes a reasonable number of entries per invocation, and then call it repeatedly - for example, by having your delete script return a 302 redirect whenever there's more data to delete, then fetching it with "wget --max-redirect=10000" (or some other large number).
With django, setup url:
url(r'^Model/bdelete/$', v.bulk_delete_models, {'model':'ModelKind'}),
Setup view
def bulk_delete_models(request, model):
import time
limit = request.GET['limit'] or 200
start = time.clock()
set = db.GqlQuery("SELECT __key__ FROM %s" % model).fetch(int(limit))
count = len(set)
db.delete(set)
return HttpResponse("Deleted %s %s in %s" % (count,model,(time.clock() - start)))
Then run in powershell:
$client = new-object System.Net.WebClient
$client.DownloadString("http://your-app.com/Model/bdelete/?limit=400")
If you are using Java/JPA you can do something like this:
em = EntityManagerFactoryUtils.getTransactionalEntityManager(entityManagerFactory)
Query q = em.createQuery("delete from Table t");
int number = q.executeUpdate();
Java/JDO info can be found here: http://code.google.com/appengine/docs/java/datastore/queriesandindexes.html#Delete_By_Query
Yes you can:
Go to Datastore Admin, and then select the Entitiy type you want to delete and click Delete.
Mapreduce will take care of deleting!
On a dev server, one can cd to his app's directory then run it like this:
dev_appserver.py --clear_datastore=yes .
Doing so will start the app and clear the datastore. If you already have another instance running, the app won't be able to bind to the needed IP and therefore fail to start...and to clear your datastore.
You can use the task queues to delete chunks of say 100 objects.
Deleting objects in GAE shows how limited the Admin capabilities are in GAE. You have to work with batches on 1000 entities or less. You can use the bulkloader tool that works with csv's but the documentation does not cover java.
I am using GAE Java and my strategy for deletions involves having 2 servlets, one for doing the actually delete and another to load the task queues. When i want to do a delete, I run the queue loading servlet, it loads the queues and then GAE goes to work executing all the tasks in the queue.
How to do it:
Create a servlet that deletes a small number of objects.
Add the servlet to your task queues.
Go home or work on something else ;)
Check the datastore every so often ...
I have a datastore with about 5000 objects that i purge every week and it takes about 6 hours to clean out, so i run the task on Friday night.
I use the same technique to bulk load my data which happens to be about 5000 objects, with about a dozen properties.
This worked for me:
class ClearHandler(webapp.RequestHandler):
def get(self):
self.response.headers['Content-Type'] = 'text/plain'
q = db.GqlQuery("SELECT * FROM SomeModel")
self.response.out.write("deleting...")
db.delete(q)
Thank you all guys, I got what I need. :D
This may be useful if you have lots db models to delete, you can dispatch it in your terminal. And also, you can manage the delete list in DB_MODEL_LIST yourself.
Delete DB_1:
python bulkdel.py 10 DB_1
Delete All DB:
python bulkdel.py 11
Here is the bulkdel.py file:
import sys, os
URL = 'http://localhost:8080'
DB_MODEL_LIST = ['DB_1', 'DB_2', 'DB_3']
# Delete Model
if sys.argv[1] == '10' :
command = 'curl %s/clear_db?model=%s' % ( URL, sys.argv[2] )
os.system( command )
# Delete All DB Models
if sys.argv[1] == '11' :
for model in DB_MODEL_LIST :
command = 'curl %s/clear_db?model=%s' % ( URL, model )
os.system( command )
And here is the modified version of alexandre fiori's code.
from google.appengine.ext import db
class DBDelete( webapp.RequestHandler ):
def get( self ):
self.response.headers['Content-Type'] = 'text/plain'
db_model = self.request.get('model')
sql = 'SELECT __key__ FROM %s' % db_model
try:
while True:
q = db.GqlQuery( sql )
assert q.count()
db.delete( q.fetch(200) )
time.sleep(0.5)
except Exception, e:
self.response.out.write( repr(e)+'\n' )
pass
And of course, you should map the link to model in a file(like main.py in GAE), ;)
In case some guys like me need it in detail, here is part of main.py:
from google.appengine.ext import webapp
import utility # DBDelete was defined in utility.py
application = webapp.WSGIApplication([('/clear_db',utility.DBDelete ),('/',views.MainPage )],debug = True)
To delete all entities in a given kind in Google App Engine you only need to do as follows:
from google.cloud import datastore
query = datastore.Client().query(kind = <KIND>)
results = query.fetch()
for result in results:
datastore.Client().delete(result.key)
In javascript, the following will delete all the entries for on page:
document.getElementById("allkeys").checked=true;
checkAllEntities();
document.getElementById("delete_button").setAttribute("onclick","");
document.getElementById("delete_button").click();
given that you are on the admin-page (.../_ah/admin) with the entities you want to delete.