weather checking with sys.argv - python

I am trying to make a weather search tool using sys.argv and just wanted some help. I have the current code
The problem is when I search using the command line I need to type in the country. Is there a way to do it searching only the city?:
#! /usr/bin/env python3
import webbrowser
import sys
import pyperclip
import re
if len(sys.argv) > 1:
#Get address from command line.
address = ' '.join(sys.argv[1:])
else:
address = pyperclip.paste()
webbrowser.open('https://www.timeanddate.com/weather/' + address)
command line:
./weather.py spain/madrid
./weather.py uk/london

As was mentioned, there are probably a number of packages that will do the trick, and likely none of them will work for certain city names. However, geonamescache is very easy to use and will do the trick for unique names. Here is an example (will return "Canada" for "Toronto" as input)
pip install geonamescache
import geonamescache as gnc
gc = gnc.GeonamesCache()
query = 'Toronto'
citykey = list(gc.get_cities_by_name(query)[0])[0]
ccode = gc.get_cities_by_name(query)[0][citykey]['countrycode']
countries = gc.get_countries()
country_name = countries[ccode]['name']
print(country_name)

1-) Register geonames to use API
Create a new user account https://www.geonames.org/login
Activate your account from mail
On the redirected page after clicking activation link, activate web services
2-) Install geocoder
pip install geocoder
3-) Use API
import geocoder
g = geocoder.geonames('madrid', key='YOURUSERNAMEHERE')
...
webbrowser.open('https://www.timeanddate.com/weather/' + g.country + address)
As #Kalma mentioned, g.country returns 'United Kingdom' instead of 'UK'. You might need to map these values to the ones that timeanddate.com accepts.

Related

Issues / question with batch update with pygsheets / google sheets

Ok I'm new to python but...I really like it. I have been trying to figure this out for awhile and thought someone could help that knows a lot more than I.
So what I would like to do is use pygsheets and combine batch the updates with one api call vs several. I have been searching for examples or ideas and found if you unlink and link it will do this? I tried and it speed it up only a little bit, then I looked and you could use update.values vs update.value. I have got it to work with the something like this wk1.update_values('A2:C4',[[1,2,3],[4,5,6],[7,8,9]]) but what if you want the updates to be in specific cell locations vs a range like a2:c4? I appreciate any advice in advance.
https://pygsheets.readthedocs.io/en/latest/worksheet.html#pygsheets.Worksheet.update_values
https://pygsheets.readthedocs.io/en/latest/sheet_api.html?highlight=batch_updates#pygsheets.sheet.SheetAPIWrapper.values_batch_update
import pygsheets
gc = pygsheets.authorize() # This will create a link to authorize
# Open spreadsheet
GS_ID = ''
File_Tab_Name = 'File1'
Main_Topic = 'Main Topic'
Actual_Company_Name = 'Company Name'
Street = 'Street Address'
City_State_Zip = 'City State Zip'
Phone_Number = 'Phone Number'
# 2. Open spreadsheet by key
sh = gc.open_by_key(GS_ID)
sh.title = File_Tab_Name
wk1 = sh[0]
wk1.title = File_Tab_Name
#wk1.update_values('A2:C4',[[1,2,3],[4,5,6],[7,8,9]])
wk1.update_values([['a1'],['h1'],['i3']],[[Main_Topic],[Actual_Company_Name],[Street]]) ### is this possible
#wk1.unlink()
#wk1.title = File_Tab_Name
#wk1.update_value("a1",Main_Topic) ###Topic
#wk1.update_value("h1",Actual_Company_Name) ###Company Name
#wk1.update_value("i3",Street) ###Street Address
#wk1.update_value("i4",City_State_Zip) ###City State Zip
#wk1.update_value("i5",Phone_Number) ### Phone Number
#wk1.link() # will do all the updates
From what I could undersand you want to batch update values. you can use the update_values_batch function.
wks.update_values_batch(['A1:A2', 'B1:B2'], [[[1],[2]], [[3],[4]]])
# or
wks.update_values_batch([((1,1), (2,1)), 'B1:B2'], [[[1,2]], [[3,4]]], 'COLUMNS')
# or
wks.update_values_batch(['A1:A2', 'B1:B2'], [[[1,2]], [[3,4]]], 'COLUMNS')
see doc here.
NB: update pygsheets to latest version or install from gitub
pip install --upgrade https://github.com/nithinmurali/pygsheets/archive/staging.zip
Unfortunately, pygsheets has no method for updating multiple ranges in batch. Instead, you can use gspread.
gspread has batch_update method where you can update multiple cell or range at once.
Example:
Code:
import gspread
gc = gspread.service_account()
sh = gc.open_by_key("insert spreadsheet key here").sheet1
sh.batch_update([{
'range': 'A1:B1',
'values': [['42', '43']],
}, {
'range': 'A2:B2',
'values': [['44', '45']],
}])
Output:
References:
gspread:batch_update()
gspread Authentication

Pulling Zillow Rent Data from Zillow API

I am playing around with the Zillow API, but I am having trouble retrieving the rent data. Currently I am using a Python Zillow wrapper, but I am not sure if it works for pulling the rent data.
This is the help page I am using for the Zillow API:
https://www.zillow.com/howto/api/GetSearchResults.htm
import pyzillow
from pyzillow.pyzillow import ZillowWrapper, GetDeepSearchResults
import pandas as pd
house = pd.read_excel('Housing_Output.xlsx')
### Login to Zillow API
address = ['123 Test Street City, State Abbreviation'] # Fill this in with an address
zip_code = ['zip code'] # fill this in with a zip code
zillow_data = ZillowWrapper(API KEY)
deep_search_response = zillow_data.get_deep_search_results(address, zip_code)
result = GetDeepSearchResults(deep_search_response)
# These API calls work, but I am not sure how to retrieve the rent data
print(result.zestimate_amount)
print(result.tax_value)
ADDING ADDITIONAL INFO:
Chapter 2 talks how to pull rent data by creating a XML function called zillowProperty. My skills going into XML aren't great, but I think I need to either:
a) import some xml package to help read it
b) save the code as an XML file and use the open function to read the file
https://www.amherst.edu/system/files/media/Comprehensive_Evaluation_-_Ningyue_Christina_Wang.pdf
I am trying to provide the code in here, but it won't let me break to the next line for some reason.
We can see that rent is not a field one can get using the pyzillow package, by looking into the attributes of your result by running dir(result), as well as the code here: Pyzillow source code.
However, thanks to the beauty of open source, you can edit the source code of this package and get the functionality you are looking for. Here is how:
First, locate where the code sits in your hard drive. Import pyzillow, and run:
pyzillow?
The File field shows this for me:
c:\programdata\anaconda3\lib\site-packages\pyzillow\__init__.py
Hence go to c:\programdata\anaconda3\lib\site-packages\pyzillow (or whatever it shows for you) and open the pyzillow.py file with a text editor.
Now we need to do two changes.
One: Inside the get_deep_search_results function, you'll see params. We need to edit that to turn the rentzestimate feature on. So change that function to:
def get_deep_search_results(self, address, zipcode):
"""
GetDeepSearchResults API
"""
url = 'http://www.zillow.com/webservice/GetDeepSearchResults.htm'
params = {
'address': address,
'citystatezip': zipcode,
'zws-id': self.api_key,
'rentzestimate': True # This is the only line we add
}
return self.get_data(url, params)
Two: Go to class GetDeepSearchResults(ZillowResults), and add the following into the attribute_mapping dictionary:
'rentzestimate_amount': 'result/rentzestimate/amount'
Voila! The customized&updated Python package now returns the Rent Zestimate! Let's try:
from pyzillow.pyzillow import ZillowWrapper, GetDeepSearchResults
address = ['11 Avenue B, Johnson City, NY']
zip_code = ['13790']
zillow_data = ZillowWrapper('X1-ZWz1835knufc3v_38l6u')
deep_search_response = zillow_data.get_deep_search_results(address, zip_code)
result = GetDeepSearchResults(deep_search_response)
print(result.rentzestimate_amount)
Which correctly returns the Rent Zestimate of $1200, which can be validated at the Zillow page of that address.

Creating a Google shared contact using the API - contact is created but not in the shared Directory

I'm currently using the shared_contacts_profiles.py script to load contacts from an external system into our Google Shared Domain contacts. I'd like to make the process more automated so I've tried to create a shared contact (with just a full name and email address) using a basic python script. The contact is created but it gets added to the administrator's contacts and not the Directory.
My code is
#!/usr/bin/python
import atom
import gdata.data
import gdata.contacts.client
import gdata.contacts.data
def main():
admin_email = 'admin#mydomain.com'
admin_password = 'P4ssw0rd'
domain_index = admin_email.find('#')
domain = admin_email[domain_index+1:]
contacts_client = gdata.contacts.client.ContactsClient(domain=domain)
contacts_client.client_login(email=admin_email,
password=admin_password,
source='shared_contacts_profiles',
account_type='HOSTED')
new_contact = gdata.contacts.data.ContactEntry()
new_contact.name = gdata.data.Name(
full_name=gdata.data.FullName(text='John Doe'))
new_contact.email.append(gdata.data.Email(address='john.doe#example.com',
primary='true',rel=gdata.data.WORK_REL))
contact_entry = contacts_client.CreateContact(new_contact)
print "Contact's ID: %s" % contact_entry.id.text
if __name__ == '__main__':
main()
I must be missing something fairly simple, but just can't see what it is.
EDIT * I think that shared_contacts_profiles.py sets the domain contact list when it sends batches to Google. I wasn't going to use batches as there are only ever a couple of contacts to add. I also suspect I should be using gdata.contacts.service.ContactsService and not gdata.contacts.client.ContactsClient
Thanks
Dave
In the end I used the original code as shown above with some additions. I needed to get the feed uri for the shared domain contact list and then supply that uri in the CreateContact.
feed_url = contacts_client.GetFeedUri(contact_list=domain, projection='full')
contact_entry = contacts_client.CreateContact(new_contact,insert_uri=feed_url)
Thanks
Dave

How to use ebay sdk in Python?

I have found this code sample to make a query in ebay from here and also downloaded ebay-sdk for Python. How can I install the sdk and integrate this code with it?
from ebaysdk import finding, nodeText
f = finding()
f.execute('findItemsAdvanced', {'keywords': 'shoes'})
dom = f.response_dom()
mydict = f.response_dict()
myobj = f.response_obj()
print myobj.itemSearchURL
# process the response via DOM
items = dom.getElementsByTagName('item')
for item in items:
print nodeText(item.getElementsByTagName('title')[0])
It is quite a simple process
1) Go to http://developer.ebay.com/, register over there, and get
the app id key.
2) You can simply do a 'pip install ebaysdk' to
install the ebaysdk
3) Copy this file in the same directory
https://github.com/timotheus/ebaysdk-python/blob/master/ebay.yaml In
this file replace appid with what you generated in step 1
4) Execute the example, this time it will work :)

Google Analytics and Python

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>

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