def main(client, image_filename):
# Initialize appropriate service.
media_service = client.GetMediaService(version='v201309')
image_data = Utils.ReadFile(image_filename)
image_data = base64.encodestring(image_data)
# Construct media and upload image.
media = [{
'xsi_type': 'Image',
'data': image_data,
'type': 'IMAGE'
}]
media = media_service.Upload(media)[0]
# Display results.
if media:
dimensions = Utils.GetDictFromMap(media['dimensions'])
print ('Image with id \'%s\', dimensions \'%sx%s\', and MimeType \'%s\' was'
' uploaded.' % (media['mediaId'], dimensions['FULL']['height'],
dimensions['FULL']['width'], media['mimeType']))
else:
print 'No images were uploaded.'
print
print ('Usage: %s units, %s operations' % (client.GetUnits(),
client.GetOperations()))
def main(client):
# Initialize appropriate service.
media_service = client.GetMediaService(version='v201406')
# Construct selector and get all images.
offset = 0
selector = {
'fields': ['MediaId', 'Type', 'Width', 'Height', 'MimeType'],
'predicates': [{
'field': 'Type',
'operator': 'IN',
'values': ['IMAGE', 'VIDEO']
}],
'paging': {
'startIndex': str(offset),
'numberResults': str(PAGE_SIZE)
}
}
more_pages = True
while more_pages:
page = media_service.Get(selector)[0]
# Display results.
if 'entries' in page:
for media in page['entries']:
# Handle image
if media.get('dimensions'):
dimensions = Utils.GetDictFromMap(media['dimensions'])
print(
'Image with id \'%s\', dimensions \'%sx%s\', and MimeType'
' \'%s\' was found.' %
(media['mediaId'], dimensions['FULL']['height'],
dimensions['FULL']['width'], media['mimeType']))
else: # Handle video
print 'Video with id \'%s\' was found.' % media['mediaId']
else:
print 'No images/videos were found.'
offset += PAGE_SIZE
selector['paging']['startIndex'] = str(offset)
more_pages = offset < int(page['totalNumEntries'])
print
print('Usage: %s units, %s operations' %
(client.GetUnits(), client.GetOperations()))
# Import appropriate classes from the client library.
from adspygoogle.adwords.AdWordsClient import AdWordsClient
from adspygoogle.common import Utils
# Initialize client object.
client = AdWordsClient(path=os.path.join('..', '..', '..', '..'))
# Initialize appropriate service.
media_service = client.GetMediaService('https://adwords-sandbox.google.com',
'v201003')
# Construct selector and get all images.
selector = {'mediaType': 'IMAGE'}
images = media_service.Get(selector)[0]
# Display results.
if 'media' in images:
for image in images['media']:
dimensions = Utils.GetDictFromMap(image['dimensions'])
print(
'Image with id \'%s\', dimensions \'%sx%s\', and MIME type \'%s\' '
'was found.' % (image['mediaId'], dimensions['FULL']['height'],
dimensions['FULL']['width'], image['mimeType']))
else:
print 'No images were found.'
print
print('Usage: %s units, %s operations' %
(client.GetUnits(), client.GetOperations()))
# Initialize appropriate service.
media_service = client.GetMediaService(
'https://adwords-sandbox.google.com', 'v201101')
image_data = Utils.ReadFile('INSERT_IMAGE_PATH_HERE')
if client.soap_lib == SOAPPY:
image_data = base64.encodestring(image_data)
# Construct media and upload image.
media = [{
# TODO: SOAPpy needs an xsi_type here, but SOAPpy has other problems
'data': image_data,
'type': 'IMAGE'
}]
media = media_service.Upload(media)[0]
# Display results.
if media:
dimensions = Utils.GetDictFromMap(media['dimensions'])
# WARNING: SOAPpy turns the dimensions field into a list, so this won't work
print ('Image with id \'%s\', dimensions \'%sx%s\', and MIME type \'%s\' was '
'uploaded.' % (media['mediaId'], dimensions['FULL']['height'],
dimensions['FULL']['width'], media['mimeType']))
else:
print 'No images were uploaded.'
print
print ('Usage: %s units, %s operations' % (client.GetUnits(),
client.GetOperations()))
def get_keyword_info(keyword, mode='BROAD'):
selector = {
'searchParameters': [{
'type': 'RelatedToKeywordSearchParameter',
'keywords': [{
'text': keyword,
'matchType': mode
}]
},{
'type': 'KeywordMatchTypeSearchParameter',
'keywordMatchTypes': [mode]
},{
'type': 'LanguageTargetSearchParameter',
'languageTargets': [{'languageCode':'it'}]
},{
'type': 'CountryTargetSearchParameter',
'countryTargets': [{'countryCode':'IT'}]
}],
'ideaType': 'KEYWORD',
'requestType': 'STATS',
'requestedAttributeTypes': ['GLOBAL_MONTHLY_SEARCHES', 'AVERAGE_TARGETED_MONTHLY_SEARCHES'],
'paging': {
'startIndex': '0',
'numberResults': '1000'
}
}
selector_estimator_service = {
'campaignEstimateRequests': [{
'adGroupEstimateRequests': [{
'keywordEstimateRequests': [
{
'keyword': {
'xsi_type': 'Keyword',
'matchType': mode,
'text': keyword
}
}
],
'maxCpc': {
'xsi_type': 'Money',
'microAmount': '1000000'
}
}],
'targets': [
{
'xsi_type': 'CountryTarget',
'countryCode': 'IT'
},
{
'xsi_type': 'LanguageTarget',
'languageCode': 'it'
}
]
}]
}
estimates = None
ret = None
ret = targeting_idea_service.Get(selector)[0]
#do not get cpc for now
#estimates = traffic_estimator_service.Get(selector_estimator_service)[0]
global_searches = None
regional_searches = None
if ret is not None and 'entries' in ret and ret['entries']:
for key in ret['entries']:
data = Utils.GetDictFromMap(key['data'])
if 'value' in data['GLOBAL_MONTHLY_SEARCHES']:
global_searches = int(data['GLOBAL_MONTHLY_SEARCHES']['value'])
if 'value' in data['AVERAGE_TARGETED_MONTHLY_SEARCHES']:
regional_searches = int(data['AVERAGE_TARGETED_MONTHLY_SEARCHES']['value'])
if estimates is not None:
ad_group_estimate = estimates['campaignEstimates'][0]['adGroupEstimates'][0]
keyword_estimates = ad_group_estimate['keywordEstimates']
for index in xrange(len(keyword_estimates)):
estimate = keyword_estimates[index]
# Find the mean of the min and max values.
mean_avg_cpc = (long(estimate['max']['averageCpc']['microAmount']) +
long(estimate['max']['averageCpc']['microAmount'])) / 2
mean_avg_pos = (float(estimate['min']['averagePosition']) +
float(estimate['max']['averagePosition'])) / 2
mean_clicks = (float(estimate['min']['clicksPerDay']) +
float(estimate['max']['clicksPerDay'])) / 2
mean_total_cost = (long(estimate['min']['totalCost']['microAmount']) +
long(estimate['max']['totalCost']['microAmount'])) / 2
print ('Results for the keyword with text \'%s\' and match type \'%s\':'
% (keyword, keyword))
print ' Estimated average CPC: %s' % mean_avg_cpc
print ' Estimated ad position: %s' % mean_avg_pos
print ' Estimated daily clicks: %s' % mean_clicks
print ' Estimated daily cost: %s' % mean_total_cost
return dict(global_searches = global_searches, regional_searches = regional_searches)
