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ffm-baseline
Commits
d638fb58
Commit
d638fb58
authored
Aug 30, 2019
by
张彦钊
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0ef3def9
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18 additions
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10 deletions
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-10
rerank_esmm.py
rerank_esmm.py
+18
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rerank_esmm.py
View file @
d638fb58
...
@@ -3,9 +3,11 @@ import datetime
...
@@ -3,9 +3,11 @@ import datetime
import
json
import
json
import
redis
import
redis
import
pandas
as
pd
import
pandas
as
pd
import
time
def
get_esmm_users
():
def
get_esmm_users
():
try
:
db
=
pymysql
.
connect
(
host
=
'172.16.40.158'
,
port
=
4000
,
user
=
'root'
,
db
=
pymysql
.
connect
(
host
=
'172.16.40.158'
,
port
=
4000
,
user
=
'root'
,
passwd
=
'3SYz54LS9#^9sBvC'
,
db
=
'jerry_prod'
)
passwd
=
'3SYz54LS9#^9sBvC'
,
db
=
'jerry_prod'
)
cursor
=
db
.
cursor
()
cursor
=
db
.
cursor
()
...
@@ -16,6 +18,9 @@ def get_esmm_users():
...
@@ -16,6 +18,9 @@ def get_esmm_users():
result
=
list
(
cursor
.
fetchall
())
result
=
list
(
cursor
.
fetchall
())
db
.
close
()
db
.
close
()
return
result
return
result
except
:
return
[]
def
get_user_profile
(
device_id
):
def
get_user_profile
(
device_id
):
...
@@ -46,8 +51,6 @@ def get_user_profile(device_id):
...
@@ -46,8 +51,6 @@ def get_user_profile(device_id):
return
[]
return
[]
def
get_searchworlds_to_tagid
():
def
get_searchworlds_to_tagid
():
try
:
try
:
sql
=
'select id, name from api_tag where is_online = 1 and tag_type < 4'
sql
=
'select id, name from api_tag where is_online = 1 and tag_type < 4'
...
@@ -63,22 +66,26 @@ def get_searchworlds_to_tagid():
...
@@ -63,22 +66,26 @@ def get_searchworlds_to_tagid():
return
searchworlds_to_tagid
return
searchworlds_to_tagid
except
Exception
as
e
:
except
Exception
as
e
:
print
(
e
)
return
{}
def
get_queues
(
device_id
,
city_id
):
def
get_queues
(
device_id
,
city_id
):
try
:
db
=
pymysql
.
connect
(
host
=
'172.16.40.158'
,
port
=
4000
,
user
=
'root'
,
db
=
pymysql
.
connect
(
host
=
'172.16.40.158'
,
port
=
4000
,
user
=
'root'
,
passwd
=
'3SYz54LS9#^9sBvC'
,
db
=
'jerry_test'
)
passwd
=
'3SYz54LS9#^9sBvC'
,
db
=
'jerry_test'
)
cursor
=
db
.
cursor
()
cursor
=
db
.
cursor
()
sql
=
"select native_queue, nearby_queue, nation_queue, megacity_queue from esmm_device_diary_queue "
\
sql
=
"select native_queue, nearby_queue, nation_queue, megacity_queue from esmm_device_diary_queue "
\
"where device_id = '{}' and city_id = '{}'"
.
format
(
device_id
,
city_id
)
"where device_id = '{}' and city_id = '{}'"
.
format
(
device_id
,
city_id
)
cursor
.
execute
(
sql
)
cursor
.
execute
(
sql
)
result
=
cursor
.
fetchone
()
result
=
cursor
.
fetchone
()
db
.
close
()
db
.
close
()
if
len
(
result
)
>
0
:
if
result
is
not
None
:
return
list
(
result
)
return
list
(
result
)
else
:
else
:
return
[]
return
[]
except
:
return
[]
def
tag_boost
(
cid_str
,
tag_list
):
def
tag_boost
(
cid_str
,
tag_list
):
...
@@ -96,6 +103,7 @@ def tag_boost(cid_str, tag_list):
...
@@ -96,6 +103,7 @@ def tag_boost(cid_str, tag_list):
cursor
=
db
.
cursor
()
cursor
=
db
.
cursor
()
cursor
.
execute
(
sql
)
cursor
.
execute
(
sql
)
result
=
cursor
.
fetchall
()
result
=
cursor
.
fetchall
()
db
.
close
()
if
len
(
result
)
>
0
:
if
len
(
result
)
>
0
:
tag_cids
=
{}
tag_cids
=
{}
left_cids
=
[]
left_cids
=
[]
...
@@ -157,19 +165,19 @@ if __name__ == "__main__":
...
@@ -157,19 +165,19 @@ if __name__ == "__main__":
for
i
in
users_list
[:
6
]:
for
i
in
users_list
[:
6
]:
tag_list
=
get_user_profile
(
i
[
0
])
tag_list
=
get_user_profile
(
i
[
0
])
queues
=
get_queues
(
i
[
0
],
i
[
1
])
queues
=
get_queues
(
i
[
0
],
i
[
1
])
if
len
(
queues
)
>
0
:
if
len
(
queues
)
>
0
and
len
(
tag_list
)
>
0
:
new_native
=
tag_boost
(
queues
[
0
],
tag_list
)
new_native
=
tag_boost
(
queues
[
0
],
tag_list
)
new_nearby
=
tag_boost
(
queues
[
1
],
tag_list
)
new_nearby
=
tag_boost
(
queues
[
1
],
tag_list
)
sample
=
[
i
[
0
],
i
[
1
],
new_native
,
new_nearby
,
queues
[
2
],
queues
[
3
]]
sample
=
[
i
[
0
],
i
[
1
],
new_native
,
new_nearby
,
queues
[
2
],
queues
[
3
]
,
int
(
time
.
time
())
]
total_samples
.
append
(
sample
)
total_samples
.
append
(
sample
)
if
len
(
total_samples
)
>
0
:
if
len
(
total_samples
)
>
0
:
df
=
pd
.
DataFrame
(
total_samples
)
df
=
pd
.
DataFrame
(
total_samples
)
df
=
df
.
rename
(
columns
=
{
0
:
"device_id"
,
1
:
"city_id"
,
2
:
"native_queue"
,
df
=
df
.
rename
(
columns
=
{
0
:
"device_id"
,
1
:
"city_id"
,
2
:
"native_queue"
,
3
:
"nearby_queue"
,
4
:
"nation_queue"
,
5
:
", megacity_queue"
})
3
:
"nearby_queue"
,
4
:
"nation_queue"
,
5
:
", megacity_queue"
,
6
:
"insert_time"
})
print
(
total_samples
)
print
(
total_samples
[:
2
]
)
print
(
df
.
head
(
6
))
print
(
df
.
head
(
2
))
# to_data_base(df)
# to_data_base(df)
# to kv
# to kv
...
...
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