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  • How do you calculate expanding mean on time series using pandas?

    - by mlo
    How would you create a column(s) in the below pandas DataFrame where the new columns are the expanding mean/median of 'val' for each 'Mod_ID_x'. Imagine this as if were time series data and 'ID' 1-2 was on Day 1 and 'ID' 3-4 was on Day 2. I have tried every way I could think of but just can't seem to get it right. left4 = pd.DataFrame({'ID': [1,2,3,4],'val': [10000, 25000, 20000, 40000],'Mod_ID': [15, 35, 15, 42], 'car': ['ford','honda', 'ford', 'lexus']}) right4 = pd.DataFrame({'ID': [3,1,2,4],'color': ['red', 'green', 'blue', 'grey'], 'wheel': ['4wheel','4wheel', '2wheel', '2wheel'], 'Mod_ID': [15, 15, 35, 42]}) df1 = pd.merge(left4, right4, on='ID').drop('Mod_ID_y', axis=1)

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  • How to create a non-persistent Elixir/SQLAlchemy object?

    - by siebert
    Hi, because of legacy data which is not available in the database but some external files, I want to create a SQLAlchemy object which contains data read from the external files, but isn't written to the database if I execute session.flush() My code looks like this: try: return session.query(Phone).populate_existing().filter(Phone.mac == ident).one() except: return self.createMockPhoneFromLicenseFile(ident) def createMockPhoneFromLicenseFile(self, ident): # Some code to read necessary data from file deleted.... phone = Phone() phone.mac = foo phone.data = bar phone.state = "Read from legacy file" phone.purchaseOrderPosition = self.getLegacyOrder(ident) # SQLAlchemy magic doesn't seem to work here, probably because we don't insert the created # phone object into the database. So we set the id fields manually. phone.order_id = phone.purchaseOrderPosition.order_id phone.order_position_id = phone.purchaseOrderPosition.order_position_id return phone Everything works fine except that on a session.flush() executed later in the application SQLAlchemy tries to write the created Phone object to the database (which fortunatly doesn't succeed, because phone.state is longer than the data type allows), which breaks the function which issues the flush. Is there any way to prevent SQLAlchemy from trying to write such an object? Ciao, Steffen

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  • how to fetch more than 1000 entities NON keybased?

    - by user291071
    If I should be approaching this problem through a different method, please suggest so. I am creating an item based collaborative filter. I populate the db with the LinkRating2 class and for each link there are more than a 1000 users that I need to call and collect their ratings to perform calculations which I then use to create another table. So I need to call more than 1000 entities for a given link. For instance lets say there are over a 1000 users rated 'link1' there will be over a 1000 instances of this class for the given link property that I need to call. How would I complete this example? class LinkRating2(db.Model): user = db.StringProperty() link = db.StringProperty() rating2 = db.FloatProperty() query =LinkRating2.all() link1 = 'link string name' a = query.filter('link = ', link1) aa = a.fetch(1000)##how would i get more than 1000 for a given link1 as shown? ##keybased over 1000 in other post example i need method for a subset though not key class MyModel(db.Expando): @classmethod def count_all(cls): """ Count *all* of the rows (without maxing out at 1000) """ count = 0 query = cls.all().order('__key__') while count % 1000 == 0: current_count = query.count() if current_count == 0: break count += current_count if current_count == 1000: last_key = query.fetch(1, 999)[0].key() query = query.filter('__key__ > ', last_key) return count

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  • Wrong values reported by pyPDF for various box regions

    - by romor
    Using pyPdf, for most files I get matched results concerning various box's dimensions compared to what Acrobat reports. However for some files I get different values reported by pyPdf and Acrobat, like: pyPdf: artBox: 595.3 x 841.9 bleedBox: 595.3 x 841.9 cropBox: 595.3 x 841.9 trimBox: 517.3 x 754 Acrobat: artBox: 439.35 x 666.13 pt bleedBox: 439.35 x 666.13 pt cropBox: 439.35 x 666.13 pt trimBox: 439.35 x 666.13 pt I thought it's units issue, but then ratio between widths and heights doesn't match also, not mentioning trimBox mismatch Correct results are those reported by Acrobat of course. Does someone know why is this and is there a way I get correct dimensions by using pyPdf? Thanks couple of minutes later... After reading this question: Are PDF box coordinates relative or absolute? I figured I didn't considered uper left corner to be different then 0 (zero). It turned out that box starts at 77.95 x 87.87, so if we reduce reported values of trimBox by this values correct result is obtained. artBox: 0 x 0 bleedBox: 0 x 0 cropBox: 0 x 0 trimBox: 77.95 x 87.87 Other boxes seem with misleading values or I misinterpret them. Snippet: from pyPdf import PdfFileReader pdfread = PdfFileReader(file('my.pdf', 'rb')) page = 1 width = pdfread.getPage(page).trimBox[2]-pdfread.getPage(page).trimBox[0] height = pdfread.getPage(page).trimBox[3] - pdfread.getPage(page).trimBox[1] print width, height

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  • Transferring binary file from web server to client

    - by Yan Cheng CHEOK
    Usually, when I want to transfer a web server text file to client, here is what I did import cgi print "Content-Type: text/plain" print "Content-Disposition: attachment; filename=TEST.txt" print filename = "C:\\TEST.TXT" f = open(filename, 'r') for line in f: print line Works very fine for ANSI file. However, say, I have a binary file a.exe (This file is in web server secret path, and user shall not have direct access to that directory path). I wish to use the similar method to transfer. How I can do so? What content-type I should use? Using print seems to have corrupted content received at client side. What is the correct method?

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  • Efficient way to combine results of two database queries.

    - by ensnare
    I have two tables on different servers, and I'd like some help finding an efficient way to combine and match the datasets. Here's an example: From server 1, which holds our stories, I perform a query like: query = """SELECT author_id, title, text FROM stories ORDER BY timestamp_created DESC LIMIT 10 """ results = DB.getAll(query) for i in range(len(results)): #Build a string of author_ids, e.g. '1314,4134,2624,2342' But, I'd like to fetch some info about each author_id from server 2: query = """SELECT id, avatar_url FROM members WHERE id IN (%s) """ values = (uid_list) results = DB.getAll(query, values) Now I need some way to combine these two queries so I have a dict that has the story as well as avatar_url and member_id. If this data were on one server, it would be a simple join that would look like: SELECT * FROM members, stories WHERE members.id = stories.author_id But since we store the data on multiple servers, this is not possible. What is the most efficient way to do this? Thanks.

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  • Which style of return is "better" for a method that might return None?

    - by Daenyth
    I have a method that will either return an object or None if the lookup fails. Which style of the following is better? def get_foo(needle): haystack = object_dict() if needle not in haystack: return None return haystack[needle] or, def get_foo(needle): haystack = object_dict() try: return haystack[needle] except KeyError: # Needle not found return None I'm undecided as to which is more more desirable myself. Another choice would be return haystack[needle] if needle in haystack else None, but I'm not sure that's any better.

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  • Using Django view variables inside templates

    - by William
    Hi, this is a rather basic question (I'm new to Django) but I'm having trouble using a variable set in my view inside my template. If I initialize a string or list inside my view (i.e. h = "hello") and then attempt to call it inside a template: {{ h }} there is neither output nor errors. Similarly, if I try to use a variable inside my template that doesn't exist: {{ asdfdsadf }} there is again no error reported. Is this normal? And how can I use my variables within my templates. Thanks!

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  • how to convert a binary data into interger?

    - by kaki
    when I am using the wave_read.readframes() I am getting the result in binary data such as /x00/x00/x00:/x16#/x05" etc a very long string when asked for single frame it gives @/x00 or \xe3\xff or so I want this individual frame data in integer how can I convert them into integer to store them into array.

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  • urllib open - how to control the number of retries

    - by user1641071
    how can i control the number of retries of the "opener.open"? for example, in the following code, it will send about 6 "GET" HTTP requests (i saw it in the Wireshark sniffer) before it goes to the " except urllib.error.URLError" success/no-success lines. password_mgr = urllib.request.HTTPPasswordMgrWithDefaultRealm() password_mgr.add_password(None,url, username, password) handler = urllib.request.HTTPBasicAuthHandler(password_mgr) opener = urllib.request.build_opener(handler) try: resp = opener.open(url,None,1) except urllib.error.URLError as e: print ("no success") else: print ("success!")

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  • Model Django Poll

    - by MacPython
    I followed the django tutorial here: http://docs.djangoproject.com/en/dev/intro/tutorial01/ and now I am at creating a poll. The code below works fine until I want to create choices, where for some reason I always get this error message: line 22, in unicode return self.question AttributeError: 'Choice' object has no attribute 'question' Unfortunatley, I dont understand where I made an error. Any help would be greatly appreciated. Thanks for the time! CODE: import datetime from django.db import models class Poll(models.Model): question = models.CharField(max_length=200) pub_date = models.DateTimeField('date published') def __unicode__(self): return self.question def was_published_today(self): return self.pub_date.date() == datetime.date.today() class Choice(models.Model): poll = models.ForeignKey(Poll) choice = models.CharField(max_length=200) votes = models.IntegerField() def __unicode__(self): return self.question

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  • Short snippet summarizing a webpage?

    - by Legend
    Is there a clean way of grabbing the first few lines of a given link that summarizes that link? I have seen this being done in some online bookmarking applications but have no clue on how they were implemented. For instance, if I give this link, I should be able to get a summary which is roughly like: I'll admit it, I was intimidated by MapReduce. I'd tried to read explanations of it, but even the wonderful Joel Spolsky left me scratching my head. So I plowed ahead trying to build decent pipelines to process massive amounts of data Nothing complex at first sight but grabbing these is the challenging part. Just the first few lines of the actual post should be fine. Should I just use a raw approach of grabbing the entire html and parsing the meta tags or something fancy like that (which obviously and unfortunately is not generalizable to every link out there) or is there a smarter way to achieve this? Any suggestions? Update: I just found InstaPaper do this but am not sure if it is getting the information from RSS feeds or some other way.

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  • Interesting task using random numbers only

    - by psihodelia
    Given any number of the random real numbers from the interval [0,1] is there exist any method to construct a floating point number with zero decimal part? Your algorithm can use only random() function calls and no variables or constants. No constants and variables are allowed, no type casting is allowed. You can use for/while, if/else or any other programming language operands.

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  • Modify passed, nested dict/list

    - by Gerenuk
    I was thinking of writing a function to normalize some data. A simple approach is def normalize(l, aggregate=sum, norm_by=operator.truediv): aggregated=aggregate(l) for i in range(len(l)): l[i]=norm_by(l[i], aggregated) l=[1,2,3,4] normalize(l) l -> [0.1, 0.2, 0.3, 0.4] However for nested lists and dicts where I want to normalize over an inner index this doesnt work. I mean I'd like to get l=[[1,100],[2,100],[3,100],[4,100]] normalize(l, ?? ) l -> [[0.1,100],[0.2,100],[0.3,100],[0.4,100]] Any ideas how I could implement such a normalize function? Maybe it would be crazy cool to write normalize(l[...][0]) Is it possible to make this work?? Or any other ideas? Also not only lists but also dict could be nested. Hmm... EDIT: I just found out that numpy offers such a syntax (for lists however). Anyone know how I would implement the ellipsis trick myself?

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  • Passing parameter to base class constructor or using instance variable?

    - by deamon
    All classes derived from a certain base class have to define an attribute called "path". In the sense of duck typing I could rely upon definition in the subclasses: class Base: pass # no "path" variable here def Sub(Base): def __init__(self): self.path = "something/" Another possiblity would be to use the base class constructor: class Base: def __init__(self, path): self.path = path def Sub(Base): def __init__(self): super().__init__("something/") What would you prefer and why? Is there a better way?

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  • SQL Alchemy: Relationship with grandson

    - by giomasce
    I'm building a SQL Alchemy structure with three different levels of objects; for example, consider a simple database to store information about some blogs: there are some Blog object, some Post object and some Comment objects. Each Post belongs to a Blog and each Comment belongs to a Post. Using backref I can automatically have the list of all Posts belonging to a Blog and similarly for Comments. I drafted a skeleton for such a structure. What I would like to do now is to have directly in Blog an array of all the Comments belonging to that Blog. I've tried a few approaches, but they don't work or even make SQL Alchemy cry in ways I can't fix. I'd think that mine is quite a frequent need, but I couldn't find anything helpful. Colud someone suggest me how to do that? Thanks.

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  • Loading datasets from datastore and merge into single dictionary. Resource problem.

    - by fredrik
    Hi, I have a productdatabase that contains products, parts and labels for each part based on langcodes. The problem I'm having and haven't got around is a huge amount of resource used to get the different datasets and merging them into a dict to suit my needs. The products in the database are based on a number of parts that is of a certain type (ie. color, size). And each part has a label for each language. I created 4 different models for this. Products, ProductParts, ProductPartTypes and ProductPartLabels. I've narrowed it down to about 10 lines of code that seams to generate the problem. As of currently I have 3 Products, 3 Types, 3 parts for each type, and 2 languages. And the request takes a wooping 5500ms to generate. for product in productData: productDict = {} typeDict = {} productDict['productName'] = product.name cache_key = 'productparts_%s' % (slugify(product.key())) partData = memcache.get(cache_key) if not partData: for type in typeData: typeDict[type.typeId] = { 'default' : '', 'optional' : [] } ## Start of problem lines ## for defaultPart in product.defaultPartsData: for label in labelsForLangCode: if label.key() in defaultPart.partLabelList: typeDict[defaultPart.type.typeId]['default'] = label.partLangLabel for optionalPart in product.optionalPartsData: for label in labelsForLangCode: if label.key() in optionalPart.partLabelList: typeDict[optionalPart.type.typeId]['optional'].append(label.partLangLabel) ## end problem lines ## memcache.add(cache_key, typeDict, 500) partData = memcache.get(cache_key) productDict['parts'] = partData productList.append(productDict) I guess the problem lies in the number of for loops is too many and have to iterate over the same data over and over again. labelForLangCode get all labels from ProductPartLabels that match the current langCode. All parts for a product is stored in a db.ListProperty(db.key). The same goes for all labels for a part. The reason I need the some what complex dict is that I want to display all data for a product with it's default parts and show a selector for the optional one. The defaultPartsData and optionaPartsData are properties in the Product Model that looks like this: @property def defaultPartsData(self): return ProductParts.gql('WHERE __key__ IN :key', key = self.defaultParts) @property def optionalPartsData(self): return ProductParts.gql('WHERE __key__ IN :key', key = self.optionalParts) When the completed dict is in the memcache it works smoothly, but isn't the memcache reset if the application goes in to hibernation? Also I would like to show the page for first time user(memcache empty) with out the enormous delay. Also as I said above, this is only a small amount of parts/product. What will the result be when it's 30 products with 100 parts. Is one solution to create a scheduled task to cache it in the memcache every hour? It this efficient? I know this is alot to take in, but I'm stuck. I've been at this for about 12 hours straight. And can't figure out a solution. ..fredrik

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  • Can't iterate over nestled dict in django

    - by fredrik
    Hi, Im trying to iterate over a nestled dict list. The first level works fine. But the second level is treated like a string not dict. In my template I have this: {% for product in Products %} <li> <p>{{ product }}</p> {% for partType in product.parts %} <p>{{ partType }}</p> {% for part in partType %} <p>{{ part }}</p> {% endfor %} {% endfor %} </li> {% endfor %} It's the {{ part }} that just list 1 char at the time based on partType. And it seams that it's treated like a string. I can however via dot notation reach all dict but not with a for loop. The current output looks like this: Color C o l o r Style S ..... The Products object looks like this in the log: [{'product': <models.Products.Product object at 0x1076ac9d0>, 'parts': {u'Color': {'default': u'Red', 'optional': [u'Red', u'Blue']}, u'Style': {'default': u'Nice', 'optional': [u'Nice']}, u'Size': {'default': u'8', 'optional': [u'8', u'8.5']}}}] What I trying to do is to pair together a dict/list for a product from a number of different SQL queries. The web handler looks like this: typeData = Products.ProductPartTypes.all() productData = Products.Product.all() langCode = 'en' productList = [] for product in productData: typeDict = {} productDict = {} for type in typeData: typeDict[type.typeId] = { 'default' : '', 'optional' : [] } productDict['product'] = product productDict['parts'] = typeDict defaultPartsData = Products.ProductParts.gql('WHERE __key__ IN :key', key = product.defaultParts) optionalPartsData = Products.ProductParts.gql('WHERE __key__ IN :key', key = product.optionalParts) for defaultPart in defaultPartsData: label = Products.ProductPartLabels.gql('WHERE __key__ IN :key AND partLangCode = :langCode', key = defaultPart.partLabelList, langCode = langCode).get() productDict['parts'][defaultPart.type.typeId]['default'] = label.partLangLabel for optionalPart in optionalPartsData: label = Products.ProductPartLabels.gql('WHERE __key__ IN :key AND partLangCode = :langCode', key = optionalPart.partLabelList, langCode = langCode).get() productDict['parts'][optionalPart.type.typeId]['optional'].append(label.partLangLabel) productList.append(productDict) logging.info(productList) templateData = { 'Languages' : Settings.Languges.all().order('langCode'), 'ProductPartTypes' : typeData, 'Products' : productList } I've tried making the dict in a number of different ways. Like first making a list, then a dict, used tulpes anything I could think of. Any help is welcome! Bouns: If someone have an other approach to the SQL quires, that is more then welcome. I feel that it kinda stupid to run that amount of quires. What is happening that each product part has a different label base on langCode. ..fredrik

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  • Eclipse + AppEngine =? autocomplete

    - by Brandon Watson
    I was doing some beginner AppEngine dev on a Windows box and installed Eclipse for that. I liked the autocompletion I got with the objects and functions. I moved my dev environment over to my Macbook, and installed Eclipse Ganymede. I installed the AppEngine SDK and Eclipse plug in. However, when I am typing out code now, the autocomplete isn't functioning. Did I miss a step? UPDATE Just to add to this: the line: import cgi appears to give me what I need. When I type "cgi." I get all of the auto complete. However, the lines: from google.appengine.api import users from google.appengine.ext import webapp from google.appengine.ext.webapp.util import run_wsgi_app from google.appengine.ext import db don't give me any auto complete. If I type "users." there is no auto complete.

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  • can I put my sqlite connection and cursor in a function?

    - by steini
    I was thinking I'd try to make my sqlite db connection a function instead of copy/pasting the ~6 lines needed to connect and execute a query all over the place. I'd like to make it versatile so I can use the same function for create/select/insert/etc... Below is what I have tried. The 'INSERT' and 'CREATE TABLE' queries are working, but if I do a 'SELECT' query, how can I work with the values it fetches outside of the function? Usually I'd like to print the values it fetches and also do other things with them. When I do it like below I get an error Traceback (most recent call last): File "C:\Users\steini\Desktop\py\database\test3.py", line 15, in <module> for row in connection('testdb45.db', "select * from users"): ProgrammingError: Cannot operate on a closed database. So I guess the connection needs to be open so I can get the values from the cursor, but I need to close it so the file isn't always locked. Here's my testing code: import sqlite3 def connection (db, arg): conn = sqlite3.connect(db) conn.execute('pragma foreign_keys = on') cur = conn.cursor() cur.execute(arg) conn.commit() conn.close() return cur connection('testdb.db', "create table users ('user', 'email')") connection('testdb.db', "insert into users ('user', 'email') values ('joey', 'foo@bar')") for row in connection('testdb45.db', "select * from users"): print row How can I make this work?

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