I have the following code to query a database using an ADO COMObject in python. This is connecting to a Time series database (OSIPI) and this is the only way we've been able to get Python connected to the database.
from win32com.client import Dispatch
oConn = Dispatch('ADODB.Connection')
oRS = Dispatch('ADODB.RecordSet')
oConn.ConnectionString = <my connection string>
oConn.Open()
oRS.ActiveConnection = oConn
if oConn.State == adStateOpen:
print "Connected to DB"
else:
raise SystemError('Database Connection Failed')
cmd = """SELECT tag, dataowner FROM pipoint WHERE tag LIKE 'TEST_TAG1%'"""
self.oRS.Open(cmd)
result = oRS.GetRows(1)
print result
result2 = oRS.GetRows(2)
print result2
if oConn.State == adStateOpen:
oConn.Close()
oConn = None
This code returns the following two lines as results to the query:
result ((u'TEST_TAG1.QTY.BLACK',), (u'piadmin',))
result2 = ((u'TEST_TAG1.QTY.BLACK', u'TEST_TAG1.QTY.PINK'), (u'piadmin', u'piuser'))
This is not the expected format. In this case, I was expecting something like this:
result = ((u'TEST_TAG1.QTY.BLACK',u'piadmin'))
result2 = ((u'TEST_TAG1.QTY.BLACK',u'piadmin'),
(u'TEST_TAG1.QTY.PINK',u'piuser'))
Is there a way to adjust the results of an ADO query so everything related to row 1 is in the same tuple and everything in row 2 is in the same tuple?
What you're seeing is not really a Python thing but the output of GetRows(), which returns a two-dimensional array, which is organized by by field and then row.
Fortunately, Python has the zip() function that will make the relevant change for you. Try changing your code from:
result = oRS.GetRows(1)
to:
result = zip(*oRS.GetRows(1))
etc.
Related
I wrote a code in python to manipulate a table I have in my database. I am doing so using SQL Alchemy. Basically I have table 1 that has 2 500 000 entries. I have another table 2 with 200 000 entries. Basically what I am trying to do, is compare my source ip and dest ip in table 1 with source ip and dest ip in table 2. if there is a match, I replace the ip source and ip dest in table 1 with a data that matches ip source and ip dest in table 2 and I add the entry in table 3. My code also checks if the entry isn't already in the new table. If so, it skips it and then goes on with the next row.
My problem is its extremely slow. I launched my script yesterday and in 24 hours it only went through 47 000 entries out of 2 500 000. I am wondering if there are anyways I can speed up the process. It's a postgres db and I can't tell if the script taking this much time is reasonable or if something is up. If anyone had a similar experience with something like this, how much time did it take before completion ?
Many thanks.
session = Session()
i = 0
start_id = 1
flows = session.query(Table1).filter(Table1.id >= start_id).all()
result_number = len(flows)
vlan_list = {"['0050']", "['0130']", "['0120']", "['0011']", "['0110']"}
while i < result_number:
for flow in flows:
if flow.vlan_destination in vlan_list:
usage = session.query(Table2).filter(Table2.ip ==
str(flow.ip_destination)).all()
if len(usage) > 0:
usage = usage[0].usage
else:
usage = str(flow.ip_destination)
usage_ip_src = session.query(Table2).filter(Table2.ip ==
str(flow.ip_source)).all()
if len(usage_ip_src) > 0:
usage_ip_src = usage_ip_src[0].usage
else:
usage_ip_src = str(flow.ip_source)
if flow.protocol == "17":
protocol = func.REPLACE(flow.protocol, "17", 'UDP')
elif flow.protocol == "1":
protocol = func.REPLACE(flow.protocol, "1", 'ICMP')
elif flow.protocol == "6":
protocol = func.REPLACE(flow.protocol, "6", 'TCP')
else:
protocol = flow.protocol
is_in_db = session.query(Table3).filter(Table3.protocol ==
protocol)\
.filter(Table3.application == flow.application)\
.filter(Table3.destination_port == flow.destination_port)\
.filter(Table3.vlan_destination == flow.vlan_destination)\
.filter(Table3.usage_source == usage_ip_src)\
.filter(Table3.state == flow.state)\
.filter(Table3.usage_destination == usage).count()
if is_in_db == 0:
to_add = Table3(usage_ip_src, usage, protocol, flow.application, flow.destination_port,
flow.vlan_destination, flow.state)
session.add(to_add)
session.flush()
session.commit()
print("added " + str(i))
else:
print("usage already in DB")
i = i + 1
session.close()
EDIT As requested, here are more details : Table 1 has 11 columns, the two we are interested in are source ip and dest ip.
Table 1
Here, I have Table 2 :Table 2. It has an IP and a Usage. What my script is doing is that it takes source ip and dest ip from table one and looks up if there is a match in Table 2. If so, it replaces the ip address by usage, and adds this along with some of the columns of Table 1 in Table 3 :[Table3][3]
Along doing this, when adding the protocol column into Table 3, it writes the protocol name instead of the number, just to make it more readable.
EDIT 2 I am trying to think about this differently, so I did a diagram of my problem Diagram (X problem)
What I am trying to figure out is if my code (Y solution) is working as intended. I've been coding in python for a month only and I feel like I am messing something up. My code is supposed to take every row from my Table 1, compare it to Table 2 and add data to table 3. My Table one has over 2 million entries and it's understandable that it should take a while but its too slow. For example, when I had to load the data from the API to the db, it went faster than the comparisons im trying to do with everything that is already in the db. I am running my code on a virtual machine that has sufficient memory so I am sure it's my code that is lacking and I need direction to as what can be improved. Screenshots of my tables:
Table 2
Table 3
Table 1
EDIT 3 : Postgresql QUERY
SELECT
coalesce(table2_1.usage, table1.ip_source) AS coalesce_1,
coalesce(table2_2.usage, table1.ip_destination) AS coalesce_2,
CASE table1.protocol WHEN %(param_1) s THEN %(param_2) s WHEN %(param_3) s THEN %(param_4) s WHEN %(param_5) s THEN %(param_6) s ELSE table1.protocol END AS anon_1,
table1.application AS table1_application,
table1.destination_port AS table1_destination_port,
table1.vlan_destination AS table1_vlan_destination,
table1.state AS table1_state
FROM
table1
LEFT OUTER JOIN table2 AS table2_2 ON table2_2.ip = table1.ip_destination
LEFT OUTER JOIN table2 AS table2_1 ON table2_1.ip = table1.ip_source
WHERE
table1.vlan_destination IN (
%(vlan_destination_1) s,
%(vlan_destination_2) s,
%(vlan_destination_3) s,
%(vlan_destination_4) s,
%(vlan_destination_5) s
)
AND NOT (
EXISTS (
SELECT
1
FROM
table3
WHERE
table3.usage_source = coalesce(table2_1.usage, table1.ip_source)
AND table3.usage_destination = coalesce(table2_2.usage, table1.ip_destination)
AND table3.protocol = CASE table1.protocol WHEN %(param_1) s THEN %(param_2) s WHEN %(param_3) s THEN %(param_4) s WHEN %(param_5) s THEN %(param_6) s ELSE table1.protocol END
AND table3.application = table1.application
AND table3.destination_port = table1.destination_port
AND table3.vlan_destination = table1.vlan_destination
AND table3.state = table1.state
)
)
Given the current question, I think this at least comes close to what you might be after. The idea is to perform the entire operation in the database, instead of fetching everything – the whole 2,500,000 rows – and filtering in Python etc.:
from sqlalchemy import func, case
from sqlalchemy.orm import aliased
def newhotness(session, vlan_list):
# The query needs to join Table2 twice, so it has to be aliased
dst = aliased(Table2)
src = aliased(Table2)
# Prepare required SQL expressions
usage = func.coalesce(dst.usage, Table1.ip_destination)
usage_ip_src = func.coalesce(src.usage, Table1.ip_source)
protocol = case({"17": "UDP",
"1": "ICMP",
"6": "TCP"},
value=Table1.protocol,
else_=Table1.protocol)
# Form a query producing the data to insert to Table3
flows = session.query(
usage_ip_src,
usage,
protocol,
Table1.application,
Table1.destination_port,
Table1.vlan_destination,
Table1.state).\
outerjoin(dst, dst.ip == Table1.ip_destination).\
outerjoin(src, src.ip == Table1.ip_source).\
filter(Table1.vlan_destination.in_(vlan_list),
~session.query(Table3).
filter_by(usage_source=usage_ip_src,
usage_destination=usage,
protocol=protocol,
application=Table1.application,
destination_port=Table1.destination_port,
vlan_destination=Table1.vlan_destination,
state=Table1.state).
exists())
stmt = insert(Table3).from_select(
["usage_source", "usage_destination", "protocol", "application",
"destination_port", "vlan_destination", "state"],
flows)
return session.execute(stmt)
If the vlan_list is selective, or in other words filters out most rows, this will perform a lot less operations in the database. Depending on the size of Table2 you may benefit from indexing Table2.ip, but do test first. If it is relatively small, I would guess that PostgreSQL will perform a hash or nested loop join there. If some column of the ones used to filter out duplicates in Table3 is unique, you could perform an INSERT ... ON CONFLICT ... DO NOTHING instead of removing duplicates in the SELECT using the NOT EXISTS subquery expression (which PostgreSQL will perform as an antijoin). If there is a possibility that the flows query may produce duplicates, add a call to Query.distinct() to it.
I'm trying to port to Python a SAP table download script, that already works on Excel VBA, but I want a command line version and I would prefer to avoid VBScript for a number of reasons that go beyond the goal of this post.
I'm stuck at the moment in which I need to fill the values in a table
from win32com.client import Dispatch
Functions = Dispatch("SAP.Functions")
Functions.Connection.Client = "400"
Functions.Connection.ApplicationServer = "myserver"
Functions.Connection.Language = "EN"
Functions.Connection.User = "myuser"
Functions.Connection.Password = "mypwd"
Functions.Connection.SystemNumber = "00"
Functions.Connection.UseSAPLogonIni = False
if (Functions.Connection.Logon (0,True) == True):
print("Logon OK")
RFC = Functions.Add("RFC_READ_TABLE")
RFC.exports("QUERY_TABLE").Value = "USR02"
RFC.exports("DELIMITER").Value = "~"
#RFC.exports("ROWSKIPS").Value = 2000
#RFC.exports("ROWCOUNT").Value = 10
tblOptions = RFC.Tables("OPTIONS")
#RETURNED DATA
tblData = RFC.Tables("DATA")
tblFields = RFC.Tables("FIELDS")
tblFields.AppendRow ()
print(tblFields.RowCount)
print(tblFields(1,"FIELDNAME"))
# the 2 lines above print 1 and an empty string, so the row in the table exists
Until here it is basically copied from VBA adapting the syntax.
In VBA at this point I'm able to do
tblFields(1,"FIELDNAME") = "BNAME"
if I do the same I get an error because the left part is a function and written that way it returns a string. In VBA it is probably a bi-dimensional array.
I unsuccessfully tried various approaches like
tblFields.setValue([{"FIELDNAME":"BNAME"}])
tblFields(1,"FIELDNAME").Value = "BNAME"
tblFields(1,"FIELDNAME").setValue("BNAME")
tblFields.FieldName = "BNAME" ##kinda desperate
The script works, without setting the FIELDS table, for outputs that produce rows shorter than 500 chars. This is a SAP limit in the function.
I know that this is not the best way, but I can't use the SAPNWRFC library and I can't use librfc32.dll.
I must be able to solve this way, or revert to the VB version.
Thanks to anyone who will provide a hint
After a lot of trial and error, i found a solution.
Instead of adding row by row to the "OPTIONS" or "FIELDS" tables, you can just submit a prefilled table.
This should work:
tblFields.Data = (('VBELN', '000000', '000000', '', ''),
('POSNR', '000000', '000000', '', ''))
same here:
tblOptions.Data = (("VBELN EQ '2557788'",),)
I have an objectlistview. I remove a line from it and then I want to update the list without the removed line. I fill the list with data from a database. I tried repopulatelist, but then it seems to use the data that is already in the list.
I think I can solve it with clearAll (clearing the list) and then addobjects and add the database again. But it seems that it should be possible to just update the list. This is my code:
def deletemeas(self):
MAid = self.objectma.id
MAname = self.pagename
objectsRemList = self.tempmeasurements.GetCheckedObjects()
print 'objectremlist', objectsRemList
for measurement in objectsRemList:
print measurement
Measname = measurement.filename
Measid = database.Measurement.select(database.Measurement.q.filename == Measname)[0].id
deleteMeas = []
deleteMeas.append(MAid)
deleteMeas.append(Measid)
pub.sendMessage('DELETE_MEAS', Container(data=deleteMeas)) #to microanalyse controller
#here I get the latest information from the database what should be viewed in the objectlist self.tempmeasurements
MeasInListFromDB = list(database.Microanalysismeasurement.select(database.Microanalysismeasurement.q.microanalysisid == MAid))
print 'lijstmetingen:', MeasInListFromDB
#this doesn't work
self.tempmeasurements.RefreshObjects(MeasInListFromDB)
Ok, this was actually easier than I thought ...
I added this line:
self.tempmeasurements.RemoveObject(measurement)
So I first removed the data from my database table and then I just removed the line in my objectlistview.
I am migrating my ETL code to Python and was using pyhs2, but am going to switch to pyhive since it is actively supported and maintained and no one has taken ownership of pyhs2.
My question is how to structure the fetchmany method to iterate over dataset.
Here is how I did it using pyhs2:
while hive_cur.hasMoreRows:
hive_stg_result = hive_cur.fetchmany(size=200000)
hive_stg_df = pd.DataFrame(hive_stg_result)
hive_stg_df[27] = etl_load_key
if len(hive_stg_df) == 0:
call("rm -f /tmp/{0} ".format(filename), shell=True)
print ("No data delta")
else:
print (str(len(hive_stg_df)) + " delta records identified")
for i, row in hive_stg_df.iterrows():
I had fetchmany(size=100000), but it fails when it returns empty set.
hive_stg_result = pyhive_cur.fetchmany(size=100000)
hive_stg_df = pd.DataFrame(hive_stg_result)
[Edit 2: More information and debugging in answer below...]
I'm writing a python script to export MS Access databases into a series of text files to allow for more meaningful version control (I know - why Access? Why aren't I using existing solutions? Let's just say the restrictions aren't of a technical nature).
I've successfully exported the full contents and structure of the database using ADO and ADOX via the comtypes library, but I'm getting a problem re-importing the data.
I'm exporting the contents of each table into a text file with a list on each line, like so:
[-9, u'No reply']
[1, u'My home is as clean and comfortable as I want']
[2, u'My home could be more clean or comfortable than it is']
[3, u'My home is not at all clean or comfortable']
And the following function to import the said file:
import os
import sys
import datetime
import comtypes.client as client
from ADOconsts import *
from access_consts import *
class Db:
def create_table_contents(self, verbosity = 0):
conn = client.CreateObject("ADODB.Connection")
rs = client.CreateObject("ADODB.Recordset")
conn.ConnectionString = self.new_con_string
conn.Open()
for fname in os.listdir(self.file_path):
if fname.startswith("Table_"):
tname = fname[6:-4]
if verbosity > 0:
print "Filling table %s." % tname
conn.Execute("DELETE * FROM [%s];" % tname)
rs.Open("SELECT * FROM [%s];" % tname, conn,
adOpenDynamic, adLockOptimistic)
f = open(self.file_path + os.path.sep + fname, "r")
data = f.readline()
print repr(data)
while data != '':
data = eval(data.strip())
print data[0]
print rs.Fields.Count
rs.AddNew()
for i in range(rs.Fields.Count):
if verbosity > 1:
print "Into field %s (type %s) insert value %s." % (
rs.Fields[i].Name, str(rs.Fields[i].Type),
data[i])
rs.Fields[i].Value = data[i]
data = f.readline()
print repr(data)
rs.Update()
rs.Close()
conn.Close()
Everything works fine except that numerical values (double and int) are being inserted as zeros. Any ideas on whether the problem is with my code, eval, comtypes, or ADO?
Edit: I've fixed the problem with inserting numbers - casting them as strings(!) seems to solve the problem for both double and integer fields.
However, I now have a different issue that had previously been obscured by the above: the first field in every row is being set to 0 regardless of data type... Any ideas?
And found an answer.
rs = client.CreateObject("ADODB.Recordset")
Needs to be:
rs = client.CreateObject("ADODB.Recordset", dynamic=True)
Now I just need to look into why. Just hope this question saves someone else a few hours...
Is data[i] being treated as a string? What happens if you specifically cast it as a int/double when you set rs.Fields[i].Value?
Also, what happens when you print out the contents of rs.Fields[i].Value after it is set?
Not a complete answer yet, but it appears to be a problem during the update. I've added some further debugging code in the insertion process which generates the following (example of a single row being updated):
Inserted into field ID (type 3) insert value 1, field value now 1.
Inserted into field TextField (type 202) insert value u'Blah', field value now Blah.
Inserted into field Numbers (type 5) insert value 55.0, field value now 55.0.
After update: [0, u'Blah', 55.0]
The last value in each "Inserted..." line is the result of calling rs.Fields[i].Value before calling rs.Update(). The "After..." line shows the results of calling rs.Fields[i].Value after calling rs.Update().
What's even more annoying is that it's not reliably failing. Rerunning the exact same code on the same records a few minutes later generated:
Inserted into field ID (type 3) insert value 1, field value now 1.
Inserted into field TextField (type 202) insert value u'Blah', field value now Blah.
Inserted into field Numbers (type 5) insert value 55.0, field value now 55.0.
After update: [1, u'Blah', 2.0]
As you can see, results are reliable until you commit them, then... not.