问题
db = sqlite.connect("test.sqlite")
res = db.execute("select * from table")
With iteration I get lists coresponding to the rows.
for row in res:
print row
I can get name of the columns
col_name_list = [tuple[0] for tuple in res.description]
But is there some function or setting to get dictionaries instead of list?
{'col1': 'value', 'col2': 'value'}
or I have to do myself?
回答1:
You could use row_factory, as in the example in the docs:
import sqlite3
def dict_factory(cursor, row):
d = {}
for idx, col in enumerate(cursor.description):
d[col[0]] = row[idx]
return d
con = sqlite3.connect(":memory:")
con.row_factory = dict_factory
cur = con.cursor()
cur.execute("select 1 as a")
print cur.fetchone()["a"]
or follow the advice that's given right after this example in the docs:
If returning a tuple doesn’t suffice and you want name-based access to columns, you should consider setting row_factory to the highly-optimized sqlite3.Row type. Row provides both index-based and case-insensitive name-based access to columns with almost no memory overhead. It will probably be better than your own custom dictionary-based approach or even a db_row based solution.
回答2:
I thought I answer this question even though the answer is partly mentioned in both Adam Schmideg's and Alex Martelli's answers. In order for others like me that have the same question, to find the answer easily.
conn = sqlite3.connect(":memory:")
#This is the important part, here we are setting row_factory property of
#connection object to sqlite3.Row(sqlite3.Row is an implementation of
#row_factory)
conn.row_factory = sqlite3.Row
c = conn.cursor()
c.execute('select * from stocks')
result = c.fetchall()
#returns a list of dictionaries, each item in list(each dictionary)
#represents a row of the table
回答3:
Even using the sqlite3.Row class-- you still can't use string formatting in the form of:
print "%(id)i - %(name)s: %(value)s" % row
In order to get past this, I use a helper function that takes the row and converts to a dictionary. I only use this when the dictionary object is preferable to the Row object (e.g. for things like string formatting where the Row object doesn't natively support the dictionary API as well). But use the Row object all other times.
def dict_from_row(row):
return dict(zip(row.keys(), row))
回答4:
From PEP 249:
Question:
How can I construct a dictionary out of the tuples returned by
.fetch*():
Answer:
There are several existing tools available which provide
helpers for this task. Most of them use the approach of using
the column names defined in the cursor attribute .description
as basis for the keys in the row dictionary.
Note that the reason for not extending the DB API specification
to also support dictionary return values for the .fetch*()
methods is that this approach has several drawbacks:
* Some databases don't support case-sensitive column names or
auto-convert them to all lowercase or all uppercase
characters.
* Columns in the result set which are generated by the query
(e.g. using SQL functions) don't map to table column names
and databases usually generate names for these columns in a
very database specific way.
As a result, accessing the columns through dictionary keys
varies between databases and makes writing portable code
impossible.
So yes, do it yourself.
回答5:
Shorter version:
db.row_factory = lambda c, r: dict([(col[0], r[idx]) for idx, col in enumerate(c.description)])
回答6:
Fastest on my tests:
conn.row_factory = lambda c, r: dict(zip([col[0] for col in c.description], r))
c = conn.cursor()
%timeit c.execute('SELECT * FROM table').fetchall()
19.8 µs ± 1.05 µs per loop (mean ± std. dev. of 7 runs, 100000 loops each)
vs:
conn.row_factory = lambda c, r: dict([(col[0], r[idx]) for idx, col in enumerate(c.description)])
c = conn.cursor()
%timeit c.execute('SELECT * FROM table').fetchall()
19.4 µs ± 75.6 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
You decide :)
回答7:
After you connect to SQLite:
con = sqlite3.connect(.....) it is sufficient to just run:
con.row_factory = sqlite3.Row
Voila!
回答8:
Similar like before-mentioned solutions, but most compact:
db.row_factory = lambda C, R: { c[0]: R[i] for i, c in enumerate(C.description) }
回答9:
Or you could convert the sqlite3.Rows to a dictionary as follows. This will give a dictionary with a list for each row.
def from_sqlite_Row_to_dict(list_with_rows):
''' Turn a list with sqlite3.Row objects into a dictionary'''
d ={} # the dictionary to be filled with the row data and to be returned
for i, row in enumerate(list_with_rows): # iterate throw the sqlite3.Row objects
l = [] # for each Row use a separate list
for col in range(0, len(row)): # copy over the row date (ie. column data) to a list
l.append(row[col])
d[i] = l # add the list to the dictionary
return d
回答10:
A generic alternative, using just three lines
def select_column_and_value(db, sql, parameters=()):
execute = db.execute(sql, parameters)
fetch = execute.fetchone()
return {k[0]: v for k, v in list(zip(execute.description, fetch))}
con = sqlite3.connect('/mydatabase.db')
c = con.cursor()
print(select_column_and_value(c, 'SELECT * FROM things WHERE id=?', (id,)))
But if your query returns nothing, will result in error. In this case...
def select_column_and_value(self, sql, parameters=()):
execute = self.execute(sql, parameters)
fetch = execute.fetchone()
if fetch is None:
return {k[0]: None for k in execute.description}
return {k[0]: v for k, v in list(zip(execute.description, fetch))}
or
def select_column_and_value(self, sql, parameters=()):
execute = self.execute(sql, parameters)
fetch = execute.fetchone()
if fetch is None:
return {}
return {k[0]: v for k, v in list(zip(execute.description, fetch))}
回答11:
import sqlite3
db = sqlite3.connect('mydatabase.db')
cursor = db.execute('SELECT * FROM students ORDER BY CREATE_AT')
studentList = cursor.fetchall()
columnNames = list(map(lambda x: x[0], cursor.description)) #students table column names list
studentsAssoc = {} #Assoc format is dictionary similarly
#THIS IS ASSOC PROCESS
for lineNumber, student in enumerate(studentList):
studentsAssoc[lineNumber] = {}
for columnNumber, value in enumerate(student):
studentsAssoc[lineNumber][columnNames[columnNumber]] = value
print(studentsAssoc)
The result is definitely true, but I do not know the best.
回答12:
Dictionaries in python provide arbitrary access to their elements. So any dictionary with "names" although it might be informative on one hand (a.k.a. what are the field names) "un-orders" the fields, which might be unwanted.
Best approach is to get the names in a separate list and then combine them with the results by yourself, if needed.
try:
mycursor = self.memconn.cursor()
mycursor.execute('''SELECT * FROM maintbl;''')
#first get the names, because they will be lost after retrieval of rows
names = list(map(lambda x: x[0], mycursor.description))
manyrows = mycursor.fetchall()
return manyrows, names
Also remember that the names, in all approaches, are the names you provided in the query, not the names in database. Exception is the SELECT * FROM
If your only concern is to get the results using a dictionary, then definitely use the conn.row_factory = sqlite3.Row (already stated in another answer).
回答13:
As mentioned by @gandalf's answer, one has to use conn.row_factory = sqlite3.Row, but the results are not directly dictionaries. One has to add an additional "cast" to dict in the last loop:
import sqlite3
conn = sqlite3.connect(":memory:")
conn.execute('create table t (a text, b text, c text)')
conn.execute('insert into t values ("aaa", "bbb", "ccc")')
conn.execute('insert into t values ("AAA", "BBB", "CCC")')
conn.row_factory = sqlite3.Row
c = conn.cursor()
c.execute('select * from t')
for r in c.fetchall():
print(dict(r))
# {'a': 'aaa', 'b': 'bbb', 'c': 'ccc'}
# {'a': 'AAA', 'b': 'BBB', 'c': 'CCC'}
来源：https://stackoverflow.com/questions/3300464/how-can-i-get-dict-from-sqlite-query