你如何在 Python 中创建嵌套的 dict？

How do you create nested dict in Python?

提问by atams

I have 2 CSV files: 'Data' and 'Mapping':

我有 2 个 CSV 文件：“数据”和“映射”：

• 'Mapping' file has 4 columns: Device_Name, GDN, Device_Type, and Device_OS. All four columns are populated.
• 'Data' file has these same columns, with Device_Namecolumn populated and the other three columns blank.
• I want my Python code to open both files and for each Device_Namein the Data file, map its GDN, Device_Type, and Device_OSvalue from the Mapping file.

• '映射'文件有4列：Device_Name，GDN，Device_Type，和Device_OS。所有四列都已填充。
• “数据”文件具有这些相同的列，其中Device_Name填充了列，其他三列空白。
• 我希望我的Python代码来打开这两个文件并为每个Device_Name数据文件，它的映射GDN，Device_Type以及Device_OS从映射文件中值。

I know how to use dict when only 2 columns are present (1 is needed to be mapped) but I don't know how to accomplish this when 3 columns need to be mapped.

我知道当只有 2 列（需要映射 1 列）时如何使用 dict，但是当需要映射 3 列时我不知道如何实现这一点。

Following is the code using which I tried to accomplish mapping of Device_Type:

以下是我尝试完成映射的代码Device_Type：

x = dict([])
with open("Pricing Mapping_2013-04-22.csv", "rb") as in_file1:
    file_map = csv.reader(in_file1, delimiter=',')
    for row in file_map:
       typemap = [row[0],row[2]]
       x.append(typemap)

with open("Pricing_Updated_Cleaned.csv", "rb") as in_file2, open("Data Scraper_GDN.csv", "wb") as out_file:
    writer = csv.writer(out_file, delimiter=',')
    for row in csv.reader(in_file2, delimiter=','):
         try:
              row[27] = x[row[11]]
         except KeyError:
              row[27] = ""
         writer.writerow(row)

It returns Attribute Error.

它返回Attribute Error。

After some researching, I think I need to create a nested dict, but I don't have any idea how to do this.

经过一番研究，我想我需要创建一个嵌套的字典，但我不知道如何做到这一点。

采纳答案by Inbar Rose

A nested dict is a dictionary within a dictionary. A very simple thing.

嵌套字典是字典中的字典。很简单的一件事情。

>>> d = {}
>>> d['dict1'] = {}
>>> d['dict1']['innerkey'] = 'value'
>>> d
{'dict1': {'innerkey': 'value'}}

You can also use a defaultdictfrom the collectionspackage to facilitate creating nested dictionaries.

你也可以使用一个defaultdict从collections包装，以方便创建嵌套的字典。

>>> import collections
>>> d = collections.defaultdict(dict)
>>> d['dict1']['innerkey'] = 'value'
>>> d  # currently a defaultdict type
defaultdict(<type 'dict'>, {'dict1': {'innerkey': 'value'}})
>>> dict(d)  # but is exactly like a normal dictionary.
{'dict1': {'innerkey': 'value'}}

---

---

You can populate that however you want.

您可以随意填充。

I would recommend in your code something likethe following:

我建议在你的代码的东西像下面：

d = {}  # can use defaultdict(dict) instead

for row in file_map:
    # derive row key from something 
    # when using defaultdict, we can skip the next step creating a dictionary on row_key
    d[row_key] = {} 
    for idx, col in enumerate(row):
        d[row_key][idx] = col

---

---

According to your comment:

根据您的评论：

may be above code is confusing the question. My problem in nutshell: I have 2 files a.csv b.csv, a.csv has 4 columns i j k l, b.csv also has these columns. i is kind of key columns for these csvs'. j k l column is empty in a.csv but populated in b.csv. I want to map values of j k l columns using 'i` as key column from b.csv to a.csv file

可能是上面的代码混淆了这个问题。我的问题简而言之：我有 2 个文件 a.csv b.csv，a.csv 有 4 列 ijkl，b.csv 也有这些列。i 是这些 csvs 的关键列。jkl 列在 a.csv 中为空，但在 b.csv 中填充。我想将 jk l 列的值使用 'i` 作为键列从 b.csv 映射到 a.csv 文件

My suggestion would be something likethis (without using defaultdict):

我的建议是什么像这样（不使用defaultdict）：

a_file = "path/to/a.csv"
b_file = "path/to/b.csv"

# read from file a.csv
with open(a_file) as f:
    # skip headers
    f.next()
    # get first colum as keys
    keys = (line.split(',')[0] for line in f) 

# create empty dictionary:
d = {}

# read from file b.csv
with open(b_file) as f:
    # gather headers except first key header
    headers = f.next().split(',')[1:]
    # iterate lines
    for line in f:
        # gather the colums
        cols = line.strip().split(',')
        # check to make sure this key should be mapped.
        if cols[0] not in keys:
            continue
        # add key to dict
        d[cols[0]] = dict(
            # inner keys are the header names, values are columns
            (headers[idx], v) for idx, v in enumerate(cols[1:]))

Please note though, that for parsing csv files there is a csv module.

但请注意，解析 csv 文件有一个csv 模块。

回答by Junchen

UPDATE: For an arbitrary length of a nested dictionary, go to this answer.

更新：对于任意长度的嵌套字典，请转到此答案。

Use the defaultdict function from the collections.

使用集合中的 defaultdict 函数。

High performance: "if key not in dict" is very expensive when the data set is large.

高性能：当数据集很大时，“if key not in dict”非常昂贵。

Low maintenance: make the code more readable and can be easily extended.

低维护：使代码更具可读性，易于扩展。

from collections import defaultdict

target_dict = defaultdict(dict)
target_dict[key1][key2] = val

回答by andrew

For arbitrary levels of nestedness:

对于任意级别的嵌套：

In [2]: def nested_dict():
   ...:     return collections.defaultdict(nested_dict)
   ...:

In [3]: a = nested_dict()

In [4]: a
Out[4]: defaultdict(<function __main__.nested_dict>, {})

In [5]: a['a']['b']['c'] = 1

In [6]: a
Out[6]:
defaultdict(<function __main__.nested_dict>,
            {'a': defaultdict(<function __main__.nested_dict>,
                         {'b': defaultdict(<function __main__.nested_dict>,
                                      {'c': 1})})})

回答by Skysail

It is important to remember when using defaultdict and similar nested dict modules such as nested_dict, that looking up a nonexistent key may inadvertently create a new key entry in the dict and cause a lot of havoc.

在使用 defaultdict 和类似的嵌套 dict 模块（例如 ）时，请务必记住nested_dict，查找不存在的键可能会无意中在 dict 中创建一个新的键条目并造成大量破坏。

Here is a Python3 example with nested_dictmodule:

这是一个带有nested_dict模块的 Python3 示例：

import nested_dict as nd
nest = nd.nested_dict()
nest['outer1']['inner1'] = 'v11'
nest['outer1']['inner2'] = 'v12'
print('original nested dict: \n', nest)
try:
    nest['outer1']['wrong_key1']
except KeyError as e:
    print('exception missing key', e)
print('nested dict after lookup with missing key.  no exception raised:\n', nest)

# Instead, convert back to normal dict...
nest_d = nest.to_dict(nest)
try:
    print('converted to normal dict. Trying to lookup Wrong_key2')
    nest_d['outer1']['wrong_key2']
except KeyError as e:
    print('exception missing key', e)
else:
    print(' no exception raised:\n')

# ...or use dict.keys to check if key in nested dict
print('checking with dict.keys')
print(list(nest['outer1'].keys()))
if 'wrong_key3' in list(nest.keys()):

    print('found wrong_key3')
else:
    print(' did not find wrong_key3')

Output is:

输出是：

original nested dict:   {"outer1": {"inner2": "v12", "inner1": "v11"}}

nested dict after lookup with missing key.  no exception raised:  
{"outer1": {"wrong_key1": {}, "inner2": "v12", "inner1": "v11"}} 

converted to normal dict. 
Trying to lookup Wrong_key2 

exception missing key 'wrong_key2' 

checking with dict.keys 

['wrong_key1', 'inner2', 'inner1']  
did not find wrong_key3