Develop Reference

Sort operation used more than the maximum 33.5 MB of RAM

In Pymongo, I have the following block of code. I would need to bring in all of the data associated with my time search query into memory for further handling. To do that, I use the following block of code.
search_query = {"time" : {"$lte" : datetime.datetime.now()}}
search_result = mongo_collection.find(search_query)
ascending_search_result = search_result.sort("time", 1)
oldest_time = ascending_search_result[0]["time"]
descending_search_result = search_result.sort("time",-1)
latest_time = descending_search_result[0]["time"]
list_search_result = list(search_result)
It:
Searches for the matching records
Sorts them to find the start and end time points
Use list(search_result) to bring it into memory and convert it into a list
However, when I run list(search_result), the following error is returned.
Sort operation used more than the maximum 33554432 bytes of RAM. Add an index, or specify a smaller limit.', 'code': 96, 'codeName': 'OperationFailed'}
What can I do to resolve this error?
Edit I was wondering if grabbing the items in the search result individually would solve the problem. Unfortunately, this did not solve the problem. Same error thrown. I thought this would only bring in one item at a time, which would be the smallest step in importing the records.
list_search_result = list()
for item in search_result:
list_search_result.append(item)

I was able to successfully achieve the same thing I wanted to do above with the following. The key is using aggregate and allowDiskUse option.
pipeline = [{"$match" : search_query}]
search_result = mongo_collection.aggregate(pipeline, allowDiskUse=True)
list_search_result = list(search_result)
search_result2 = psd_stream_record.find(search_query)
ascending_search_result = search_result2.sort("time", 1)
oldest_time = ascending_search_result[0]["time"]
descending_search_result = search_result2.sort("time",-1)
latest_time = descending_search_result[0]["time"]

Making comparing 2 tables faster (Postgres/SQLAlchemy)

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.

Set query parameters of RFC_READ_TABLE using win32com module?

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'",),)

Python Unit Testing using Doctest not working as expected

I have created a python module to generate weather data(Latitude, Longitude, Elevation and other details) by taking particular location as input.
Updated it as per standards and "pycodestyle" package for checking PEP8 standards does not throw any error or warnings.
My Code is given below :
def fetch_location_info(input_list, err_file):
# URL which gives us Latitude, Longitude values
LatLong_URL = (
'http://maps.googleapis.com/maps/api/geocode/json?sensor=false&address='
)
# URL which gives us Elevation values
Elevation_URL = (
'https://maps.googleapis.com/maps/api/elevation/json?locations='
)
# Initializing Error Logs with relevant title for writing error records
err_line_header = "Logging Location Data Errors"
print(err_line_header, file=err_file)
# Insert a new line in the error file after the Error Header
print("\n", file=err_file)
# Fetch and Extract Location details from google maps
input_info = []
for location in input_list:
temp_info = {'Location': location}
latlong_response = requests.get(LatLong_URL + location).json()
if latlong_response.get('results'):
for latlong_results in latlong_response.get('results'):
latlong = (
latlong_results
.get('geometry', '0')
.get('location', '0')
)
temp_info['Latitude'] = latlong.get('lat', '0')
temp_info['Longitude'] = latlong.get('lng', '0')
elevation_response = requests.get(
Elevation_URL
+ str(temp_info['Latitude'])
+ ','
+ str(temp_info['Longitude'])
).json()
if elevation_response.get('results'):
for elevation_results in elevation_response.get('results'):
temp_info['Elevation'] = (
elevation_results.get('elevation', '0'))
input_info.append(temp_info)
break
else:
print("Elevation_URL is not fetching values for {}"
.format(location),
file=err_file
)
break
else:
print("LatLong_URL is not fetching values for {}"
.format(location),
file=err_file
)
print("\n", file=err_file)
return input_info
Now as a next step, I am trying to do Unit Testing using doctest. I chose to keep the test cases in a separate file. So I created the following .txt file and kept in the same directory as the code.
This is a doctest based regression suite for Test_Weather.py
Each '>>' line is run as if in a python shell, and counts as a test.
The next line, if not '>>' is the expected output of the previous line.
If anything doesn't match exactly (including trailing spaces), the test fails.
>>> from Test_Weather import fetch_location_info
>>> fetch_location_info(["Sydney,Australia"], open('data/error_log.txt', 'w'))
print(input_info)
As seen above, the expected condition should return the contents of the list / dataframe / variable that is created within the function being tested. For a try I just tried to print the contents of the list but my unit test output throws error like below since the expected value and got value is not matching :
PS C:\Users\JKC> python -m doctest testcases.txt
********************************************************************** File "testcases.txt", line 7, in testcases.txt Failed example:
fetch_location_info(["Sydney,Australia"], open('data/error_log.txt', 'w'))
Expected:
print(input_info)
Got:
[{'Location': 'Sydney,Australia', 'Latitude': -33.8688197, 'Longitude': 151. 2092955, 'Elevation': 24.5399284362793}]
So here as you can see that the Test Case worked fine but since I am not able to print the contents of the list, it is failing the test case.
My question is How can I display the contents of list in the expected section of the unit test case ?
If I am not wrong, do I need to literally mention the output value in the expected section of the unit test case ?
Any inputs will be helpful

You need to have the doctest look exactly as if you ran it at the Python REPL:
>>> from Test_Weather import fetch_location_info
>>> fetch_location_info(["Sydney,Australia"], open('data/error_log.txt', 'w'))
[{'Location': 'Sydney,Australia', 'Latitude': -33.8688197, 'Longitude': 151.2092955, 'Elevation': 24.5399284362793}]

Problem Inserting data into MS Access database using ADO via Python

[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.