Related
Probably this is a simple question, but my experience in for loop is very limited.
I was trying to adapt the solution in this page https://www.mediawiki.org/wiki/API:Geosearch with some simple examples that i have, but the result is not what i expected.
For example:
I have this simple data frame:
df= pd.DataFrame({'City':['Sesimbra','Ciudad Juárez','31100 Treviso','Ramada Portugal','Olhão'],
'Country':['Portugal','México','Itália','Portugal','Portugal']})
I created a list based on cities:
lista_cidades = list(df['City'])
and i would like to iterate over this list to get the coordinates (decimal, preferably)
So far i tried this approach:
import requests
lng_dict = {}
lat_dict = {}
S = requests.Session()
URL = "https://en.wikipedia.org/w/api.php"
PARAMS = {
"action": "query",
"format": "json",
"titles": [lista_cidades],
"prop": "coordinates"
}
R = S.get(url=URL, params=PARAMS)
DATA = R.json()
PAGES = DATA['query']['pages']
for i in range(len(lista_cidades)):
for k, v in PAGES.items():
try:
lat_dict[lista_cidades[i]] = str(v['coordinates'][0]['lat'])
lng_dict[lista_cidades[i]] = str(v['coordinates'][0]['lon'])
except:
pass
but it looks like the code doesn't iterate over the list and always returns the same coordinate
For example, when i call the dictionary with latitude coordinates, this is what i get
lng_dict
{'Sesimbra': '-7.84166667',
'Ciudad Juárez': '-7.84166667',
'31100 Treviso': '-7.84166667',
'Ramada Portugal': '-7.84166667',
'Olhão': '-7.84166667'}
What should i do to solve this?
Thanks in advance
I think the query returns only one result, it will take only the last city from you list (in your cas the "Olhão" coordinates).
You can check it by logging the DATA content.
I do not know about wikipedia API, but either your call lack a parameter (documentation should give you the information) or you have to call the API for each city like :
import pandas as pd
import requests
df = pd.DataFrame({'City': ['Sesimbra', 'Ciudad Juárez', '31100 Treviso', 'Ramada Portugal', 'Olhão'],
'Country': ['Portugal', 'México', 'Itália', 'Portugal', 'Portugal']})
lista_cidades = list(df['City'])
lng_dict = {}
lat_dict = {}
S = requests.Session()
URL = "https://en.wikipedia.org/w/api.php"
for city in lista_cidades:
PARAMS = {
"action": "query",
"format": "json",
"titles": city,
"prop": "coordinates"
}
R = S.get(url=URL, params=PARAMS)
DATA = R.json()
PAGES = DATA['query']['pages']
for k, v in PAGES.items():
try:
lat_dict[city] = str(v['coordinates'][0]['lat'])
lng_dict[city] = str(v['coordinates'][0]['lon'])
except:
pass
*New to Programming
Question: I need to use the below "Data" (two rows as arrays) queried from sql and use it to create the message structure below.
data from sql using fetchall()
Data = [[100,1,4,5],[101,1,4,6]]
##expected message structure
message = {
"name":"Tom",
"Job":"IT",
"info": [
{
"id_1":"100",
"id_2":"1",
"id_3":"4",
"id_4":"5"
},
{
"id_1":"101",
"id_2":"1",
"id_3":"4",
"id_4":"6"
},
]
}
I tried to create below method to iterate over the rows and then input the values, this is was just a starting, but this was also not working
def create_message(data)
for row in data:
{
"id_1":str(data[0][0],
"id_2":str(data[0][1],
"id_3":str(data[0][2],
"id_4":str(data[0][3],
}
Latest Code
def create_info(data):
info = []
for row in data:
temp_dict = {"id_1_tom":"","id_2_hell":"","id_3_trip":"","id_4_clap":""}
for i in range(0,1):
temp_dict["id_1_tom"] = str(row[i])
temp_dict["id_2_hell"] = str(row[i+1])
temp_dict["id_3_trip"] = str(row[i+2])
temp_dict["id_4_clap"] = str(row[i+3])
info.append(temp_dict)
return info
Edit: Updated answer based on updates to the question and comment by original poster.
This function might work for the example you've given to get the desired output, based on the attempt you've provided:
def create_info(data):
info = []
for row in data:
temp_dict = {}
temp_dict['id_1_tom'] = str(row[0])
temp_dict['id_2_hell'] = str(row[1])
temp_dict['id_3_trip'] = str(row[2])
temp_dict['id_4_clap'] = str(row[3])
info.append(temp_dict)
return info
For the input:
[[100, 1, 4, 5],[101,1,4,6]]
This function will return a list of dictionaries:
[{"id_1_tom":"100","id_2_hell":"1","id_3_trip":"4","id_4_clap":"5"},
{"id_1_tom":"101","id_2_hell":"1","id_3_trip":"4","id_4_clap":"6"}]
This can serve as the value for the key info in your dictionary message. Note that you would still have to construct the message dictionary.
I am trying to extract the "mobility index" values for each state and county from this webpage:
https://www.cuebiq.com/visitation-insights-mobility-index/
The preferred output would be a panel data of place (state/county) by date for all available places and dates.
There is another thread (How can I scrape tooltips value from a Tableau graph embedded in a webpage) with a similar question. I tried to follow the solution there but it doesn't seem to work for my case.
Thanks a lot in advance.
(A way that I have tried is to download PDF files generated from Tableau, which would contain all counties' value on a specific date. However, I still need to find a way to make request for each date in the data. Anyway, let me know if you have a better idea than this route).
This tableau data url doesn't return any data. In fact, it only render images of the values (canvas probably) and I'm guessing it detects click based on coordinate. Probably, it's made this way to cache the value and render quickly.
But when you click on a state, it actually returns data but it seems it doesn't always returns the result for the state (but works the individual county).
The solution I've found is to use the tooltip to get the data for the state. When you click the state, it generates a request like this :
POST https://public.tableau.com/{path}/{session_id}/commands/tabsrv/render-tooltip-server
with the following form param :
worksheet: US Map - State - CMI
dashboard: CMI
tupleIds: [18]
vizRegionRect: {"r":"viz","x":496,"y":148,"w":0,"h":0,"fieldVector":null}
allowHoverActions: false
allowPromptText: true
allowWork: false
useInlineImages: true
where tupleIds: [18] refers to the index of the state in a list of states in reverse alphabetical order like this :
stateNames = ["Wyoming","Wisconsin","West Virginia","Washington","Virginia","Vermont","Utah","Texas","Tennessee","South Dakota","South Carolina","Rhode Island","Pennsylvania","Oregon","Oklahoma","Ohio","North Dakota","North Carolina","New York","New Mexico","New Jersey","New Hampshire","Nevada","Nebraska","Montana","Missouri","Mississippi","Minnesota","Michigan","Massachusetts","Maryland","Maine","Louisiana","Kentucky","Kansas","Iowa","Indiana","Illinois","Idaho","Georgia","Florida","District of Columbia","Delaware","Connecticut","Colorado","California","Arkansas","Arizona","Alabama"]
It gives a json with the html of the tooltip which has the CMI and YoY values you want to extract :
{
"vqlCmdResponse": {
"cmdResultList": [{
"commandName": "tabsrv:render-tooltip-server",
"commandReturn": {
"tooltipText": "{\"htmlTooltip\": \"<HTML HERE WITH THE VALUES>\"}]},\"overlayAnchors\":[]}"
}
}]
}
}
The only caveat is that you'll hava to make one request per state :
import requests
from bs4 import BeautifulSoup
import json
import time
data_host = "https://public.tableau.com"
r = requests.get(
f"{data_host}/views/CMI-2_0/CMI",
params= {
":showVizHome":"no",
}
)
soup = BeautifulSoup(r.text, "html.parser")
tableauData = json.loads(soup.find("textarea",{"id": "tsConfigContainer"}).text)
dataUrl = f'{data_host}{tableauData["vizql_root"]}/bootstrapSession/sessions/{tableauData["sessionid"]}'
r = requests.post(dataUrl, data= {
"sheet_id": tableauData["sheetId"],
})
data = []
stateNames = ["Wyoming","Wisconsin","West Virginia","Washington","Virginia","Vermont","Utah","Texas","Tennessee","South Dakota","South Carolina","Rhode Island","Pennsylvania","Oregon","Oklahoma","Ohio","North Dakota","North Carolina","New York","New Mexico","New Jersey","New Hampshire","Nevada","Nebraska","Montana","Missouri","Mississippi","Minnesota","Michigan","Massachusetts","Maryland","Maine","Louisiana","Kentucky","Kansas","Iowa","Indiana","Illinois","Idaho","Georgia","Florida","District of Columbia","Delaware","Connecticut","Colorado","California","Arkansas","Arizona","Alabama"]
for stateIndex, state in enumerate(stateNames):
time.sleep(0.5) #for throttling
r = requests.post(f'{data_host}{tableauData["vizql_root"]}/sessions/{tableauData["sessionid"]}/commands/tabsrv/render-tooltip-server',
data = {
"worksheet": "US Map - State - CMI",
"dashboard": "CMI",
"tupleIds": f"[{stateIndex+1}]",
"vizRegionRect": json.dumps({"r":"viz","x":496,"y":148,"w":0,"h":0,"fieldVector":None}),
"allowHoverActions": "false",
"allowPromptText": "true",
"allowWork": "false",
"useInlineImages": "true"
})
tooltip = json.loads(r.json()["vqlCmdResponse"]["cmdResultList"][0]["commandReturn"]["tooltipText"])["htmlTooltip"]
soup = BeautifulSoup(tooltip, "html.parser")
rows = [
t.find("tr").find_all("td")
for t in soup.find_all("table")
]
entry = { "state": state }
for row in rows:
if (row[0].text == "Mobility Index:"):
entry["CMI"] = "".join([t.text.strip() for t in row[1:]])
if row[0].text == "YoY (%):":
entry["YoY"] = "".join([t.text.strip() for t in row[1:]])
print(entry)
data.append(entry)
print(data)
Try this on repl.it
To get the county information it's the same as this post using the select endpoint which gives you the data with the same format as the post you've linked in your question
The following will extract data for all county and state :
import requests
from bs4 import BeautifulSoup
import json
import time
data_host = "https://public.tableau.com"
worksheet = "US Map - State - CMI"
dashboard = "CMI"
r = requests.get(
f"{data_host}/views/CMI-2_0/CMI",
params= {
":showVizHome":"no",
}
)
soup = BeautifulSoup(r.text, "html.parser")
tableauData = json.loads(soup.find("textarea",{"id": "tsConfigContainer"}).text)
dataUrl = f'{data_host}{tableauData["vizql_root"]}/bootstrapSession/sessions/{tableauData["sessionid"]}'
r = requests.post(dataUrl, data= {
"sheet_id": tableauData["sheetId"],
})
data = []
stateNames = ["Wyoming","Wisconsin","West Virginia","Washington","Virginia","Vermont","Utah","Texas","Tennessee","South Dakota","South Carolina","Rhode Island","Pennsylvania","Oregon","Oklahoma","Ohio","North Dakota","North Carolina","New York","New Mexico","New Jersey","New Hampshire","Nevada","Nebraska","Montana","Missouri","Mississippi","Minnesota","Michigan","Massachusetts","Maryland","Maine","Louisiana","Kentucky","Kansas","Iowa","Indiana","Illinois","Idaho","Georgia","Florida","District of Columbia","Delaware","Connecticut","Colorado","California","Arkansas","Arizona","Alabama"]
for stateIndex, state in enumerate(stateNames):
time.sleep(0.5) #for throttling
r = requests.post(f'{data_host}{tableauData["vizql_root"]}/sessions/{tableauData["sessionid"]}/commands/tabsrv/render-tooltip-server',
data = {
"worksheet": worksheet,
"dashboard": dashboard,
"tupleIds": f"[{stateIndex+1}]",
"vizRegionRect": json.dumps({"r":"viz","x":496,"y":148,"w":0,"h":0,"fieldVector":None}),
"allowHoverActions": "false",
"allowPromptText": "true",
"allowWork": "false",
"useInlineImages": "true"
})
tooltip = json.loads(r.json()["vqlCmdResponse"]["cmdResultList"][0]["commandReturn"]["tooltipText"])["htmlTooltip"]
soup = BeautifulSoup(tooltip, "html.parser")
rows = [
t.find("tr").find_all("td")
for t in soup.find_all("table")
]
entry = { "state": state }
for row in rows:
if (row[0].text == "Mobility Index:"):
entry["CMI"] = "".join([t.text.strip() for t in row[1:]])
if row[0].text == "YoY (%):":
entry["YoY"] = "".join([t.text.strip() for t in row[1:]])
r = requests.post(f'{data_host}{tableauData["vizql_root"]}/sessions/{tableauData["sessionid"]}/commands/tabdoc/select',
data = {
"worksheet": worksheet,
"dashboard": dashboard,
"selection": json.dumps({
"objectIds":[stateIndex+1],
"selectionType":"tuples"
}),
"selectOptions": "select-options-simple"
})
entry["county_data"] = r.json()["vqlCmdResponse"]["layoutStatus"]["applicationPresModel"]["dataDictionary"]["dataSegments"]
print(entry)
data.append(entry)
print(data)
When I query the AdWords API to get search volume data and trends through their TargetingIdeaSelector using the Python client library the returned data looks like this:
(TargetingIdeaPage){
totalNumEntries = 1
entries[] =
(TargetingIdea){
data[] =
(Type_AttributeMapEntry){
key = "KEYWORD_TEXT"
value =
(StringAttribute){
Attribute.Type = "StringAttribute"
value = "keyword phrase"
}
},
(Type_AttributeMapEntry){
key = "TARGETED_MONTHLY_SEARCHES"
value =
(MonthlySearchVolumeAttribute){
Attribute.Type = "MonthlySearchVolumeAttribute"
value[] =
(MonthlySearchVolume){
year = 2016
month = 2
count = 2900
},
...
(MonthlySearchVolume){
year = 2015
month = 3
count = 2900
},
}
},
},
}
This isn't JSON and appears to just be a messy Python list. What's the easiest way to flatten the monthly data into a Pandas dataframe with a structure like this?
Keyword | Year | Month | Count
keyword phrase 2016 2 10
The output is a sudsobject. I found that this code does the trick:
import suds.sudsobject as sudsobject
import pandas as pd
a = [sudsobject.asdict(x) for x in output]
df = pd.DataFrame(a)
Addendum: This was once correct but new versions of the API (I tested
201802) now return a zeep.objects. However, zeep.helpers.serialize_object should do the same trick.
link
Here's the complete code that I used to query the TargetingIdeaSelector, with requestType STATS, and the method I used to parse the data to a useable dataframe; note the section starting "Parse results to pandas dataframe" as this takes the output given in the question above and converts it to a dataframe. Probably not the fastest or best, but it works! Tested with Python 2.7.
"""This code pulls trends for a set of keywords, and parses into a dataframe.
The LoadFromStorage method is pulling credentials and properties from a
"googleads.yaml" file. By default, it looks for this file in your home
directory. For more information, see the "Caching authentication information"
section of our README.
"""
from googleads import adwords
import pandas as pd
adwords_client = adwords.AdWordsClient.LoadFromStorage()
PAGE_SIZE = 10
# Initialize appropriate service.
targeting_idea_service = adwords_client.GetService(
'TargetingIdeaService', version='v201601')
# Construct selector object and retrieve related keywords.
offset = 0
stats_selector = {
'searchParameters': [
{
'xsi_type': 'RelatedToQuerySearchParameter',
'queries': ['donald trump', 'bernie sanders']
},
{
# Language setting (optional).
# The ID can be found in the documentation:
# https://developers.google.com/adwords/api/docs/appendix/languagecodes
'xsi_type': 'LanguageSearchParameter',
'languages': [{'id': '1000'}],
},
{
# Location setting
'xsi_type': 'LocationSearchParameter',
'locations': [{'id': '1027363'}] # Burlington,Vermont
}
],
'ideaType': 'KEYWORD',
'requestType': 'STATS',
'requestedAttributeTypes': ['KEYWORD_TEXT', 'TARGETED_MONTHLY_SEARCHES'],
'paging': {
'startIndex': str(offset),
'numberResults': str(PAGE_SIZE)
}
}
stats_page = targeting_idea_service.get(stats_selector)
##########################################################################
# Parse results to pandas dataframe
stats_pd = pd.DataFrame()
if 'entries' in stats_page:
for stats_result in stats_page['entries']:
stats_attributes = {}
for stats_attribute in stats_result['data']:
#print (stats_attribute)
if stats_attribute['key'] == 'KEYWORD_TEXT':
kt = stats_attribute['value']['value']
else:
for i, val in enumerate(stats_attribute['value'][1]):
data = {'keyword': kt,
'year': val['year'],
'month': val['month'],
'count': val['count']}
data = pd.DataFrame(data, index = [i])
stats_pd = stats_pd.append(data, ignore_index=True)
print(stats_pd)
Let me start by stating that I am new to python. I wrote a script that will convert a .json file to csv format. I managed to write a script to do the job, however I don't think that my script will work if the format of the json file was to change. My script assumes that the json file will be in the same format at all times.
<json file example>
{
"Order":
{
"order_id":"8251662",
"order_date":"2012-08-20 13:17:37",
"order_date_shipped":"0000-00-00 00:00:00",
"order_status":"fraudreview",
"order_ship_firstname":"pam",
"order_ship_lastname":"Gregorio",
"order_ship_address1":"1533 E. Dexter St",
"order_ship_address2":"",
"order_ship_city":"Covina",
"order_ship_state":"CA",
"order_ship_zip":"91746",
"order_ship_country":"US United States",
"order_ship_phone":"6268936923",
"order_ship_email":"pgregorio#brighton.com",
"order_bill_firstname":"pam",
"order_bill_lastname":"Gregorio",
"order_bill_address1":"1533 E. Dexter St",
"order_bill_address2":"",
"order_bill_city":"Covina",
"order_bill_state":"CA",
"order_bill_zip":"91746",
"order_bill_country":"US United States",
"order_bill_phone":"6268936923",
"order_bill_email":"pgregorio#brighton.com",
"order_gift_message":"",
"order_giftwrap":"0",
"order_gift_charge":"0",
"order_shipping":"Standard (Within 5-10 Business Days)",
"order_tax_charge":"62.83",
"order_tax_shipping":"0",
"order_tax_rate":"0.0875",
"order_shipping_charge":"7.5",
"order_total":"788.33",
"order_item_count":"12",
"order_tracking":"",
"order_carrier":"1"
},
"Items":
[
{
"item_id":"25379",
"item_date_shipped":"",
"item_code":"17345-J3553-J35532",
"item_quantity":"2","item_taxable":"YES",
"item_unit_price":"32","item_shipping":"0.67",
"item_addcharge_price":"0",
"item_description":" ABC Slide Bracelet: : Size: OS: Silver Sku: J35532",
"item_quantity_returned":"0",
"item_quantity_shipped":"0",
"item_quantity_canceled":"0",
"item_status":"pending",
"item_product_id":"17345",
"item_product_kit_id":"0",
"item_product_sku":"J35532",
"item_product_barcode":"881934310775",
"item_tracking":"",
"item_carrier":"0",
"item_source_orderid":""
},
{
"item_id":"25382",
"item_date_shipped":"",
"item_code":"17608-J3809-J3809C",
"item_quantity":"1",
"item_taxable":"YES",
"item_unit_price":"22",
"item_shipping":"0.23",
"item_addcharge_price":"0",
"item_description":" \"ABC Starter Bracelet 7 1\/4\"\"\": : Size: OS: Silver Sku: J3809C",
"item_quantity_returned":"0",
"item_quantity_shipped":"0",
"item_quantity_canceled":"0",
"item_status":"pending",
"item_product_id":"17608",
"item_product_kit_id":"0",
"item_product_sku":"J3809C",
"item_product_barcode":"881934594175",
"item_tracking":"",
"item_carrier":"0",
"item_source_orderid":""
},
{
"item_id":"25385",
"item_date_shipped":"",
"item_code":"17687-J9200-J92000",
"item_quantity":"2",
"item_taxable":"YES",
"item_unit_price":"12",
"item_shipping":"0.25",
"item_addcharge_price":"0",
"item_description":" ABC Cathedral Bead: : Size: OS: Silver Sku: J92000",
"item_quantity_returned":"0",
"item_quantity_shipped":"0",
"item_quantity_canceled":"0",
"item_status":"pending",
"item_product_id":"17687",
"item_product_kit_id":"0",
"item_product_sku":"J92000",
"item_product_barcode":"881934602832",
"item_tracking":"",
"item_carrier":"0",
"item_source_orderid":""
},
{
"item_id":"25388",
"item_date_shipped":"",
"item_code":"17766-J9240-J92402",
"item_quantity":"2",
"item_taxable":"YES",
"item_unit_price":"22",
"item_shipping":"0.46",
"item_addcharge_price":"0",
"item_description":" ABC Ice Diva Bead: : Size: OS: Silver Sku: J92402",
"item_quantity_returned":"0",
"item_quantity_shipped":"0",
"item_quantity_canceled":"0",
"item_status":"pending",
"item_product_id":"17766",
"item_product_kit_id":"0",
"item_product_sku":"J92402",
"item_product_barcode":"881934655838",
"item_tracking":"",
"item_carrier":"0",
"item_source_orderid":""
},
],
"FraudReasons":
[
{
"order_id":"11957",
"fraud_reason":"order total exceeds max amount"
},
{
"order_id":"11957",
"fraud_reason":"order exceeds max item count"
}
]
}
My script currently works fine with this json file but It wont work if there is only one item or one fraudreason. Here is the code to my script.
<script code>
#!/usr/bin/python
import simplejson as json
import optparse
import pycurl
import sys
import csv
json_data = open(file)
data = json.load(json_data)
json_data.close()
csv_file = '/tmp/' + str(options.orderId) + '.csv'
orders = data['Order']
items = data['Items']
frauds = data['FraudReasons']
o = csv.writer(open(csv_file, 'w'), lineterminator=',')
o.writerow([orders['order_id'],orders['order_date'],orders['order_date_shipped'],orders['order_status'],orders['order_ship_firstname'],orders['order_ship_lastname'],orders['order_ship_address1'],orders['order_ship_address2'],orders['order_ship_city'],orders['order_ship_state'],orders['order_ship_zip'],orders['order_ship_country'],orders['order_ship_phone'],orders['order_ship_email'],orders['order_bill_firstname'],orders['order_bill_lastname'],orders['order_bill_address1'],orders['order_bill_address2'],orders['order_bill_city'],orders['order_bill_state'],orders['order_bill_zip'],orders['order_bill_country'],orders['order_bill_phone'],orders['order_bill_email'],orders['order_gift_message'],orders['order_giftwrap'],orders['order_gift_charge'],orders['order_shipping'],orders['order_tax_charge'],orders['order_tax_shipping'],orders['order_tax_rate'],orders['order_shipping_charge'],orders['order_total'],orders['order_item_count'],orders['order_tracking'],orders['order_carrier']])
for item in items:
o.writerow([item['item_id'],item['item_date_shipped'],item['item_code'],item['item_quantity'],item['item_taxable'],item['item_unit_price'],item['item_shipping'],item['item_addcharge_price'],item['item_description'],item['item_quantity_returned'],item['item_quantity_shipped'],item['item_quantity_canceled'],item['item_status'],item['item_product_id'],item['item_product_kit_id'],item['item_product_sku'],item['item_product_barcode'],item['item_tracking'],item['item_carrier'],item['item_source_orderid']])
for fraud in frauds:
o.writerow([fraud['fraud_reason']],)
I also have not been able to figure out how not to use the labels I hope someone can help me with this
thanks in advance.
You may want to use csv.DictWriter:
# It's considered best to stash the main logic of your script
# in a main() function like this.
def main(filename, options):
with open(filename) as fi:
data = json.load(fi)
csv_file = '/tmp/' + str(options.orderId) + '.csv'
order = data['Order']
items = data['Items']
frauds = data['FraudReasons']
# Here's one way to keep this maintainable if the JSON
# format changes, and you don't care too much about the
# order of the fields...
orders_fields = sorted(orders.keys())
item_fields = sorted(items[0].keys()) if items else ()
fraud_fields = sorted(fraud[0].keys()) if fraud else ()
csv_options = dict(lineterminator=',')
with open(csv_file, 'w') as fo:
o = csv.DictWriter(fo, order_fields, **csv_options)
o.writeheader()
o.writerow(orders)
fo.write('\n') # Optional, if you want to keep them separated.
o = csv.DictWriter(fo, item_fields, **csv_options)
o.writeheader()
o.writerows(items)
fo.write('\n') # Optional, if you want to keep them separated.
o = csv.DictWriter(fo, fraud_fields, **csv_options)
o.writeheader()
o.writerows(frauds)
# If this script is run from the command line, just run
# main(). Here's the place to use `optparse`.
if __name__ == '__main__':
main(...) # You'll need to fill in the main() arguments...
If you need to specify the order of fields, assign them to a tuple like this:
orders_fields = (
'order_id',
'order_date',
'order_date_shipped',
# ... etc.
)
You should ask the json-generated object (data) for the names of the fields. To retain the input order, tell json to use collections.OrderedDict instead of plain dict (requires python 2.7):
import json
from collections import OrderedDict as ordereddict
data = json.loads(open('mydata.json', object_pairs_hook=ordereddict)
orders = data['Order']
print orders.keys() # Will print the keys in the order they were read
You can then use orders.keys() instead of your hard-coded list, either with writerow or (simpler) with csv.DictWriter.
Note that this uses the default json, not simplejson, and requires python 2.7 for the ordered_pairs_hook argument and the OrderedDict type.
Edit: Yeah, I see from the comments that you're stuck with 2.4. You can download an ordereddict from PyPi, and you can extend the JSONDecoder class and pass it with the cls argument (see here), instead of object_pairs_hook, but that's uglier and more work...