mongodbshell 1.0.15

mongodbshell is a class that makes it easy to use MongoDB in the python shell

mongodbshell : A module that makes it easy to use MongoDB in the python shell

The Python shell is the ideal environment for Python developers to interact with MongoDB. However output cursors and interacting with the database requires a little more boilerplate than is convenient. the mongodbshell package provides a set a convenience functions and objects to allow easier interaction with MongoDB via the Python interpreter.

Installation

you can install the software with pip3 or pipenv. The mongodbshell only supports Python 3.

$ pip3 install mongodbshell

A complete set of API docs can be found on read the docs

Using the mongodbshell

First we create a MongoDB object. This is a proxy for all the commands we can run using MongoDBShell.

>>> client=mongodbshell.MongoDB()
>>> client
mongodbshell.MongoDB('test', 'test', 'mongodb://localhost:27017')

As you can see a MongoDB object embeds the default database test and collection test. We can also access the native MongoClient object.

Each MongoDB object has host of standard properties:

>>> client
mongodbshell.MongoDB('test', 'test', 'mongodb://localhost:27017')
>>> client.client
MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True)
>>> client.database
Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'test')
>>> client.collection
Collection(Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'test'), 'test')
>>> client.uri
'mongodb://localhost:27017'
>>>

There are also convenience functions for the most popular operations:

>>> client.is_master()
{'ismaster': True,
 'localTime': datetime.datetime(2019, 1, 16, 15, 15, 41, 87000),
 'logicalSessionTimeoutMinutes': 30,
 'maxBsonObjectSize': 16777216,
 'maxMessageSizeBytes': 48000000,
 'maxWireVersion': 7,
 'maxWriteBatchSize': 100000,
 'minWireVersion': 0,
 'ok': 1.0,
 'readOnly': False}
 
>>> mongo_client.insert_one({"name" : "Joe Drumgoole", "twitter_handle" : "@jdrumgoole"})
ObjectId('5c3f4f2fc3b498d6674b08f0')
>>> mongo_client.find_one( {"name" : "Joe Drumgoole"})
1    {'_id': ObjectId('5c3f4b04c3b498d4a1c6ce22'),
2     'name': 'Joe Drumgoole',
3     'twitter_handle': '@jdrumgoole'}

Line Numbers on Output

Line numbers are added to output by default. You can turn off line numbers by setting the line_numbers flag to false.

>>> client.insert_one({"name" : "Joe Drumgoole", "twitter_handle" : "@jdrumgoole"})
ObjectId('5c3f4f2fc3b498d6674b08f0')
>>> client.find_one( {"name" : "Joe Drumgoole"})
1    {'_id': ObjectId('5c3f4b04c3b498d4a1c6ce22'),
2     'name': 'Joe Drumgoole',
3     'twitter_handle': '@jdrumgoole'}
>>> client.line_numbers = False                      # Turn off line numbers
>>> client.find_one( {"name" : "Joe Drumgoole"})
{'_id': ObjectId('5c3f4b04c3b498d4a1c6ce22'),
 'name': 'Joe Drumgoole',
 'twitter_handle': '@jdrumgoole'}
>>>

Connecting to a specific MongoDB URI

You can connect to a different database by using the MongoDB class. Here is an example connection to a MongoDB Atlas hosted datbase.

>>> from mongodbshell import MongoDB
>>> atlas=MongoDB(uri="mongodb+srv://readonly:[e-mail]/test?retryWrites=true", database="demo", collection="zipcodes")
>>> atlas.find_one()
1    {'_id': '01069',
2     'city': 'PALMER',
3     'loc': [-72.328785, 42.176233],
4     'pop': 9778,
5     'state': 'MA'}

Looking at large volumes of output

If you run a query in the python shell it will return a cursor and to look at the objects in the cursor you need to either write a loop to consume the cursor or explicitly call next() on each cursor item.

>>> c=pymongo.MongoClient("mongodb+srv://readonly:[e-mail]/test?retryWrites=true")
>>> db=c["demo"]
>>> collection=db["zipcodes"]
>>> collection.find()
<pymongo.cursor.Cursor object at 0x105bf1d68>
>>> cursor=collection.find()
>>> next(cursor)
{'_id': '01069', 'city': 'PALMER', 'loc': [-72.328785, 42.176233], 'pop': 9778, 'state': 'MA'}
>>> next(cursor)
{'_id': '01002', 'city': 'CUSHMAN', 'loc': [-72.51565, 42.377017], 'pop': 36963, 'state': 'MA'}
>>>

This is tedious and becomes even more so when the objects are large enough to scroll off the screen. This is not a problem with the mongodbshell as the MongoDB object will automatically handle pretty printing and paginating outing.

>>> atlas.find()
1    {'_id': '01069', 'city': 'PALMER', 'loc': [-72.328785, 42.176233], 'pop': 9778, 'state': 'MA'}
2    {'_id': '01002', 'city': 'CUSHMAN', 'loc': [-72.51565, 42.377017], 'pop': 36963, 'state': 'MA'}
3    {'_id': '01012', 'city': 'CHESTERFIELD', 'loc': [-72.833309, 42.38167], 'pop': 177, 'state': 'MA'}
4    {'_id': '01073', 'city': 'SOUTHAMPTON', 'loc': [-72.719381, 42.224697], 'pop': 4478, 'state': 'MA'}
5    {'_id': '01096', 'city': 'WILLIAMSBURG', 'loc': [-72.777989, 42.408522], 'pop': 2295, 'state': 'MA'}
6    {'_id': '01262', 'city': 'STOCKBRIDGE', 'loc': [-73.322263, 42.30104], 'pop': 2200, 'state': 'MA'}
7    {'_id': '01240', 'city': 'LENOX', 'loc': [-73.271322, 42.364241], 'pop': 5001, 'state': 'MA'}
8    {'_id': '01370', 'city': 'SHELBURNE FALLS', 'loc': [-72.739059, 42.602203], 'pop': 4525, 'state': 'MA'}
9    {'_id': '01340', 'city': 'COLRAIN', 'loc': [-72.726508, 42.67905], 'pop': 2050, 'state': 'MA'}
10   {'_id': '01462', 'city': 'LUNENBURG', 'loc': [-71.726642, 42.58843], 'pop': 9117, 'state': 'MA'}
11   {'_id': '01473', 'city': 'WESTMINSTER', 'loc': [-71.909599, 42.548319], 'pop': 6191, 'state': 'MA'}
12   {'_id': '01510', 'city': 'CLINTON', 'loc': [-71.682847, 42.418147], 'pop': 13269, 'state': 'MA'}
13   {'_id': '01569', 'city': 'UXBRIDGE', 'loc': [-71.632869, 42.074426], 'pop': 10364, 'state': 'MA'}
14   {'_id': '01775', 'city': 'STOW', 'loc': [-71.515019, 42.430785], 'pop': 5328, 'state': 'MA'}
Hit Return to continue (q or quit to exit)

Pagination will dynamically adjust to screen height.

Outputting to a file

The MongoDB class can send output to a file by setting the output_file property on the MongoDB class.

>>> atlas.output_file="zipcodes.txt"
>>> atlas.find()
Output is also going to 'zipcodes.txt'
1    {'_id': '01069', 'city': 'PALMER', 'loc': [-72.328785, 42.176233], 'pop': 9778, 'state': 'MA'}
2    {'_id': '01002', 'city': 'CUSHMAN', 'loc': [-72.51565, 42.377017], 'pop': 36963, 'state': 'MA'}
3    {'_id': '01012', 'city': 'CHESTERFIELD', 'loc': [-72.833309, 42.38167], 'pop': 177, 'state': 'MA'}
4    {'_id': '01073', 'city': 'SOUTHAMPTON', 'loc': [-72.719381, 42.224697], 'pop': 4478, 'state': 'MA'}
5    {'_id': '01096', 'city': 'WILLIAMSBURG', 'loc': [-72.777989, 42.408522], 'pop': 2295, 'state': 'MA'}
6    {'_id': '01262', 'city': 'STOCKBRIDGE', 'loc': [-73.322263, 42.30104], 'pop': 2200, 'state': 'MA'}
7    {'_id': '01240', 'city': 'LENOX', 'loc': [-73.271322, 42.364241], 'pop': 5001, 'state': 'MA'}
8    {'_id': '01370', 'city': 'SHELBURNE FALLS', 'loc': [-72.739059, 42.602203], 'pop': 4525, 'state': 'MA'}
9    {'_id': '01340', 'city': 'COLRAIN', 'loc': [-72.726508, 42.67905], 'pop': 2050, 'state': 'MA'}
10   {'_id': '01462', 'city': 'LUNENBURG', 'loc': [-71.726642, 42.58843], 'pop': 9117, 'state': 'MA'}
11   {'_id': '01473', 'city': 'WESTMINSTER', 'loc': [-71.909599, 42.548319], 'pop': 6191, 'state': 'MA'}
12   {'_id': '01510', 'city': 'CLINTON', 'loc': [-71.682847, 42.418147], 'pop': 13269, 'state': 'MA'}
13   {'_id': '01569', 'city': 'UXBRIDGE', 'loc': [-71.632869, 42.074426], 'pop': 10364, 'state': 'MA'}
14   {'_id': '01775', 'city': 'STOW', 'loc': [-71.515019, 42.430785], 'pop': 5328, 'state': 'MA'}
>>> print(open('zipcodes.txt').read())
{'_id': '01069', 'city': 'PALMER', 'loc': [-72.328785, 42.176233], 'pop': 9778, 'state': 'MA'}
{'_id': '01002', 'city': 'CUSHMAN', 'loc': [-72.51565, 42.377017], 'pop': 36963, 'state': 'MA'}
{'_id': '01012', 'city': 'CHESTERFIELD', 'loc': [-72.833309, 42.38167], 'pop': 177, 'state': 'MA'}
{'_id': '01073', 'city': 'SOUTHAMPTON', 'loc': [-72.719381, 42.224697], 'pop': 4478, 'state': 'MA'}
{'_id': '01096', 'city': 'WILLIAMSBURG', 'loc': [-72.777989, 42.408522], 'pop': 2295, 'state': 'MA'}
{'_id': '01262', 'city': 'STOCKBRIDGE', 'loc': [-73.322263, 42.30104], 'pop': 2200, 'state': 'MA'}
{'_id': '01240', 'city': 'LENOX', 'loc': [-73.271322, 42.364241], 'pop': 5001, 'state': 'MA'}
{'_id': '01370', 'city': 'SHELBURNE FALLS', 'loc': [-72.739059, 42.602203], 'pop': 4525, 'state': 'MA'}
{'_id': '01340', 'city': 'COLRAIN', 'loc': [-72.726508, 42.67905], 'pop': 2050, 'state': 'MA'}
{'_id': '01462', 'city': 'LUNENBURG', 'loc': [-71.726642, 42.58843], 'pop': 9117, 'state': 'MA'}
{'_id': '01473', 'city': 'WESTMINSTER', 'loc': [-71.909599, 42.548319], 'pop': 6191, 'state': 'MA'}
{'_id': '01510', 'city': 'CLINTON', 'loc': [-71.682847, 42.418147], 'pop': 13269, 'state': 'MA'}
{'_id': '01569', 'city': 'UXBRIDGE', 'loc': [-71.632869, 42.074426], 'pop': 10364, 'state': 'MA'}
{'_id': '01775', 'city': 'STOW', 'loc': [-71.515019, 42.430785], 'pop': 5328, 'state': 'MA'}

Output will continue to be sent to the output_file until the output_file is assigned None or the empty string ("").

Options

You can set the following options on the MongoDB class objects.

MongoDB.line_numbers : Bool. True to display line numbers in output, False to remove them.

MongoDB.pretty_print : Bool. True to use pprint.pprint to output documents. False to write them out as the database returned them.

MongoDB.paginate : Bool. True to paginate output based on screen height. False to just send all output directly to console.

MongoDB.output_file : Str. Define a file to write results to. All output is appended to the file. Each line is flushed so content is not lost. Set output_file ton None or the emtpy string ("") to stop output going to a file.