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Query a Postgress table using a large python list and Psycopg2 with speed.?

I have a python list of upwards of 2000 elements. I have a postgress table i need to query for each one of these elements, i am currently using the following.
cur.execute("SELECT * FROM patent_info WHERE patentno = ANY (%s);", (list_of_patent,))
What this does is query the table one at a time for every element in the list and i store this data in a dataframe afterwards using
data = cur.fetchall()
The issue is that with over 2000 elements the response takes a while to generate sometimes causing my webapp to timeout or the browser to timeout.
I was looking for a way to query all the elements from the table faster or more efficiently.
i thought about using a for loop for every element in the list and using cur.fetchone() but i assumed that would be slower.

Do a join in instead:
cursor.execute("""
select *
from
patent_info
inner join
unnest(%s) u(patentno) using (patentno)
""", (list_of_patent,))

Python, SQL: How to update multiple rows and columns in a single trip around the database?

Hello StackEx community.
I am implementing a relational database using SQLite interfaced with Python. My table consists of 5 attributes with around a million tuples.
To avoid large number of database queries, I wish to execute a single query that updates 2 attributes of multiple tuples. These updated values depend on the tuples' Primary Key value and so, are different for each tuple.
I am trying something like the following in Python 2.7:
stmt= 'UPDATE Users SET Userid (?,?), Neighbours (?,?) WHERE Username IN (?,?)'
cursor.execute(stmt, [(_id1, _Ngbr1, _name1), (_id2, _Ngbr2, _name2)])
In other words, I am trying to update the rows that have Primary Keys _name1 and _name2 by substituting the Neighbours and Userid columns with corresponding values. The execution of the two statements returns the following error:
OperationalError: near "(": syntax error
I am reluctant to use executemany() because I want to reduce the number of trips across the database.
I am struggling with this issue for a couple of hours now but couldn't figure out either the error or an alternate on the web. Please help.
Thanks in advance.

If the column that is used to look up the row to update is properly indexed, then executing multiple UPDATE statements would be likely to be more efficient than a single statement, because in the latter case the database would probably need to scan all rows.
Anyway, if you really want to do this, you can use CASE expressions (and explicitly numbered parameters, to avoid duplicates):
UPDATE Users
SET Userid = CASE Username
WHEN ?5 THEN ?1
WHEN ?6 THEN ?2
END,
Neighbours = CASE Username
WHEN ?5 THEN ?3
WHEN ?6 THEN ?4
END,
WHERE Username IN (?5, ?6);

MySQLdb Python prevent duplicate and optimize muliple inserts

I wrote this python script to import a specific xls file into mysql. It works fine but if it's run twice on the same data it will create duplicate entries. I'm pretty sure I need to use MySQL JOIN but I'm not clear on how to do that. Also is executemany() going to have the same overhead as doing inserts in a loop? I'm obviously trying to avoid that.
Here's the code in question...
for row in range(sheet.nrows):
"""name is in the 0th col. email is the 4th col."""
name = sheet.cell(row, 0).value
email = sheet.cell(row, 4).value
if name and email:
mailing_list[name.lstrip()] = email.strip()
for n, e in sorted(mailing_list.iteritems()):
rows.append((n, e))
db = MySQLdb.connect(host=host, user=user, db=dbname, passwd=pwd)
cursor = db.cursor()
cursor.executemany("""
INSERT IGNORE INTO mailing_list (name, email) VALUES (%s,%s)""",(rows))
CLARIFICATION...
I read here that...
To be sure, executemany() is effectively the same as simple iteration.
However, it is typically faster. It provides an optimized means of
affecting INSERT and REPLACE across multiple rows.
Also I took Unodes suggestion and used the UNIQUE constraint. But the IGNORE keyword is better than ON DUPLICATE KEY UPDATE because I want it to fail silently.
TL;DR
1. What's the best way prevent duplicate inserts?
ANSWER 1: UNIQUE contraint on column with SELECT IGNORE to fail silently or ON DUPLICATE KEY UPDATE to increment the duplicate value and insert it.
Is executemany() as expensive as INSERT in a loop?
#Unode says it's not but my research tells me otherwise. I would like a definitive answer.
Is this the best way or is it going to be really slow with bigger
tables and how would I test to be sure?

1 - What's the best way prevent duplicate inserts?
Depending on what "preventing" means in your case, you have two strategies and one requirement.
The requirement is that you add a UNIQUE constraint on the column/columns that you want to be unique. This alone will cause an error if insertion of a duplicate entry is attempted. However given you are using executemany the outcome may not be what you would expect.
Then as strategies you can do:
An initial filter step by running a SELECT statement before. This means running one SELECT statement per item in your rows to check if it exists already. This strategy works but is inefficient.
Using ON DUPLICATE KEY UPDATE. This automatically triggers an update if the data already exists. For more information refer to the official documentation.
2 - Is executemany() as expensive as INSERT in a loop?
No, executemany creates one query which inserts in bulk while doing a for loop will create as many queries as the number of elements in your rows.

Python: using pyodbc and replacing row field values

I'm trying to figure out if it's possible to replace record values in a Microsoft Access (either .accdb or .mdb) database using pyodbc. I've poured over the documentation and noted where it says that "Row Values Can Be Replaced" but I have not been able to make it work.
More specifically, I'm attempting to replace a row value from a python variable. I've tried:
setting the connection autocommit to "True"
made sure that it's not a data type issue
Here is a snippet of the code where I'm executing a SQL query, using fetchone() to grab just one record (I know with this script the query is only returning one record), then I am grabbing the existing value for a field (the field position integer is stored in the z variable), and then am getting the new value I want to write to the field by accessing it from an existing python dictionary created in the script.
pSQL = "SELECT * FROM %s WHERE %s = '%s'" % (reviewTBL, newID, basinID)
cursor.execute(pSQL)
record = cursor.fetchone()
if record:
oldVal = record[z]
val = codeCrosswalk[oldVal]
record[z] = val
I've tried everything I can think bit cannot get it to work. Am I just misunderstanding the help documentation?
The script runs successfully but the newly assigned value never seems to commit. I even tried putting "print str(record[z])this after the record[z] = val line to see if the field in the table has the new value and the new value would print like it worked...but then if I check in the table after the script has finished the old values are still in the table field.
Much appreciate any insight into this...I was hoping this would work like how using VBA in MS Access databases you can use an ADO Recordset to loop through records in a table and assign values to a field from a variable.
thanks,
Tom

The "Row values can be replaced" from the pyodbc documentation refers to the fact that you can modify the values on the returned row objects, for example to perform some cleanup or conversion before you start using them. It does not mean that these changes will automatically be persisted in the database. You will have to use sql UPDATE statements for that.

How do I use django db API to save all the elements of a given column in a dictionary?

I've used a raw SQL Query to access them, and it seems to have worked. However, I can't figure out a way to actually print the results to an array. The only thing that I can find is the cursor.fetchone() command, which gives me a single row.
Is there any way that I can return an entire column in a django query set?

dict(MyModel.objects.values_list('id', 'my_column')) will return a dictionary with all elements of my_column with the row's id as the key. But probably you're just looking for a list of all the values, which you should receive via MyModel.objects.values_list('my_column', flat=True)!

You can use cursor.fetchall() instead of cursor.fetchone() to retrieve all rows.
And then extract nessesary field:
raw_items = cursor.fetchall()
items = [ item.field for item in raw_items ]