1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
|
#!/usr/bin/python
# -*- coding: utf-8 -*-
#
# Copyright 2015 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Example for using the Google Search Analytics API (part of Search Console API).
A basic python command-line example that uses the searchAnalytics.query method
of the Google Search Console API. This example demonstrates how to query Google
search results data for your property. Learn more at
https://developers.google.com/webmaster-tools/
To use:
1) Install the Google Python client library, as shown at https://developers.google.com/webmaster-tools/v3/libraries.
2) Sign up for a new project in the Google APIs console at https://code.google.com/apis/console.
3) Register the project to use OAuth2.0 for installed applications.
4) Copy your client ID, client secret, and redirect URL into the client_secrets.json file included in this package.
5) Run the app in the command-line as shown below.
Sample usage:
$ python search_analytics_api_sample.py 'https://www.example.com/' '2015-05-01' '2015-05-30'
"""
from __future__ import print_function
import argparse
import sys
from googleapiclient import sample_tools
# Declare command-line flags.
argparser = argparse.ArgumentParser(add_help=False)
argparser.add_argument(
"property_uri",
type=str,
help=("Site or app URI to query data for (including " "trailing slash)."),
)
argparser.add_argument(
"start_date",
type=str,
help=("Start date of the requested date range in " "YYYY-MM-DD format."),
)
argparser.add_argument(
"end_date",
type=str,
help=("End date of the requested date range in " "YYYY-MM-DD format."),
)
def main(argv):
service, flags = sample_tools.init(
argv,
"searchconsole",
"v1",
__doc__,
__file__,
parents=[argparser],
scope="https://www.googleapis.com/auth/webmasters.readonly",
)
# First run a query to learn which dates we have data for. You should always
# check which days in a date range have data before running your main query.
# This query shows data for the entire range, grouped and sorted by day,
# descending; any days without data will be missing from the results.
request = {
"startDate": flags.start_date,
"endDate": flags.end_date,
"dimensions": ["date"],
}
response = execute_request(service, flags.property_uri, request)
print_table(response, "Available dates")
# Get totals for the date range.
request = {"startDate": flags.start_date, "endDate": flags.end_date}
response = execute_request(service, flags.property_uri, request)
print_table(response, "Totals")
# Get top 10 queries for the date range, sorted by click count, descending.
request = {
"startDate": flags.start_date,
"endDate": flags.end_date,
"dimensions": ["query"],
"rowLimit": 10,
}
response = execute_request(service, flags.property_uri, request)
print_table(response, "Top Queries")
# Get top 11-20 mobile queries for the date range, sorted by click count, descending.
request = {
"startDate": flags.start_date,
"endDate": flags.end_date,
"dimensions": ["query"],
"dimensionFilterGroups": [
{"filters": [{"dimension": "device", "expression": "mobile"}]}
],
"rowLimit": 10,
"startRow": 10,
}
response = execute_request(service, flags.property_uri, request)
print_table(response, "Top 11-20 Mobile Queries")
# Get top 10 pages for the date range, sorted by click count, descending.
request = {
"startDate": flags.start_date,
"endDate": flags.end_date,
"dimensions": ["page"],
"rowLimit": 10,
}
response = execute_request(service, flags.property_uri, request)
print_table(response, "Top Pages")
# Get the top 10 queries in India, sorted by click count, descending.
request = {
"startDate": flags.start_date,
"endDate": flags.end_date,
"dimensions": ["query"],
"dimensionFilterGroups": [
{"filters": [{"dimension": "country", "expression": "ind"}]}
],
"rowLimit": 10,
}
response = execute_request(service, flags.property_uri, request)
print_table(response, "Top queries in India")
# Group by both country and device.
request = {
"startDate": flags.start_date,
"endDate": flags.end_date,
"dimensions": ["country", "device"],
"rowLimit": 10,
}
response = execute_request(service, flags.property_uri, request)
print_table(response, "Group by country and device")
# Group by total number of Search Appearance count.
# Note: It is not possible to use searchAppearance with other
# dimensions.
request = {
"startDate": flags.start_date,
"endDate": flags.end_date,
"dimensions": ["searchAppearance"],
"rowLimit": 10,
}
response = execute_request(service, flags.property_uri, request)
print_table(response, "Search Appearance Features")
def execute_request(service, property_uri, request):
"""Executes a searchAnalytics.query request.
Args:
service: The searchconsole service to use when executing the query.
property_uri: The site or app URI to request data for.
request: The request to be executed.
Returns:
An array of response rows.
"""
return service.searchanalytics().query(siteUrl=property_uri, body=request).execute()
def print_table(response, title):
"""Prints out a response table.
Each row contains key(s), clicks, impressions, CTR, and average position.
Args:
response: The server response to be printed as a table.
title: The title of the table.
"""
print("\n --" + title + ":")
if "rows" not in response:
print("Empty response")
return
rows = response["rows"]
row_format = "{:<20}" + "{:>20}" * 4
print(row_format.format("Keys", "Clicks", "Impressions", "CTR", "Position"))
for row in rows:
keys = ""
# Keys are returned only if one or more dimensions are requested.
if "keys" in row:
keys = ",".join(row["keys"]).encode("utf-8").decode()
print(
row_format.format(
keys, row["clicks"], row["impressions"], row["ctr"], row["position"]
)
)
if __name__ == "__main__":
main(sys.argv)
|
