Python N虽然代码在运行，但我对代码的内部部分将要发生的事情感到困惑。好的，请注意，人们通常期望您进行尝试，阅读文档等。我将努力在回答中解释它，您发布的源代码中存在问题，conn=psycopg2.connect（conn_string）cur=conn.curs

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N虽然代码在运行，但我对代码的内部部分将要发生的事情感到困惑。好的，请注意，人们通常期望您进行尝试，阅读文档等。我将努力在回答中解释它，您发布的源代码中存在问题，conn=psycopg2.connect（conn_string）cur=conn.cursor（）和cur.execute（query）data=cur.fetchall（）必须是单独的行。当我对您的代码进行注释时，我发现在您打印时，内部数据非常大，这可能不是您真正想要的代码，您的代码需要多长时间才能开始打印结果？感谢您的帮助。目前，代码开始打印结果大约需要15秒。@walecackers请让其他人知道打印语句是否是您的瓶颈。

# Imports and connection string setup
# ...

# You create a connection object and a cursor here, which are prerequisites to 
# executing queries.
conn = psycopg2.connect(conn_string)
cur = conn.cursor()

# This is your query, however this is static and you would have to manipulate 
# this query every time you want something different.
# If you want to dynamically change stuff look at the links 
# posted below the code.

query = """
        SELECT
            users.id,
            users.company_id,
            users.state,
            users.phase,
            transactions.amount
        FROM
            cases
            INNER JOIN transactions ON user.id = transactions.user_id
        WHERE users.company_id IN (9, 15)
        AND transactions.date < '2018-01-01'
"""

# The following line is unnecessary, although it may help understand what
# these columns are named
# To get all column names from the DB you can use
#   colnames = [desc[0] for desc in curs.description]
# After you executed your query below
fields = ['id', 'company_id', 'state', 'phase', 'amount']

cur.execute(query)

# Here you fetch all data, which can be a lot (you may want to check
# memory consumption)
data = cur.fetchall()

# Setting up a result list and iterate over the results of the query
internal = []
for d in data:
    # The next line is not needed, we do not need to append an empty list
    # to the results as we can just append the final result for this row
    # further += is overloading the operator, it is cleaner (IMHO) to
    # use .append() here
    internal += [[''] * 4]
    # Now the remainder in the loop is interesting, we add an empty list
    # of values to the end of the results (internal) and then use the last
    # index to update the values
    # Apart from printing the full results in the last step this will probably
    # incur some overhead compared to creating the single row's result first
    # and then appending/printing it

    # This simply assigns the value of the current rows index 1 to the last
    # item in internal (the empty list added before)
    internal[-1][0] = d[1]

    # Here we obtain the index of 'phase' from fields to know which column
    # the value is

    # If you never change the fields variable above, your can just simply index
    # it directly.

    # After knowing the index (fields.index('phase')) which would be 3 we do a
    # comparison if it is 'activated' as a value
    # So the result will be True or False for everything that is
    # not 'activated'
    internal[-1][1] = d[fields.index('phase')] == 'activated'
    # Here we simply find the column idx for state (which is 2) and add the
    # value.
    internal[-1][2] = d[fields.index('state')]
    # Here we check if the amount is > 0 and assign 'success' if so, otherwise
    # 'fail'.
    internal[-1][3] = 'success' if d[4] > 0 else 'fail'

# You are printing ALL results here, for simple check you may want to print
# only the first or last result as such:

# print(internal[0])
# or
# print(internal[-1])

print(internal)

conn = psycopg2.connect(conn_string)
cur = conn.cursor()

query = """
        SELECT
            users.id,
            users.company_id,
            users.state,
            users.phase,
            transactions.amount
        FROM
            cases
            INNER JOIN transactions ON user.id = transactions.user_id
        WHERE users.company_id IN (9, 15)
        AND transactions.date < '2018-01-01'
"""

fields = ['id', 'company_id', 'state', 'phase', 'amount']

cur.execute(query)
data = cur.fetchall()

internal = []
for d in data:
    # We simply create a list with all the same results and append it
    row = [
        d[1],
        d[fields.index('phase')] == 'activated',
        d[fields.index('state')],
        'success' if d[4] > 0 else 'fail'
    ]
    internal.append(row)

# print(internal)
print(internal[0])