{ "info": { "author": "Joe Drumgoole", "author_email": "joe@joedrumgoole.com", "bugtrack_url": null, "classifiers": [ "License :: OSI Approved :: MIT License", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: Implementation :: CPython", "Programming Language :: Python :: Implementation :: PyPy" ], "description": "# mongodbshell : A module that makes it easy to use MongoDB in the python shell\n\nThe Python shell is the ideal environment for Python developers to interact\nwith MongoDB. However output cursors and interacting with the database requires\na little more boilerplate than is convenient. the `mongodbshell` package \nprovides a set a convenience functions and objects to allow easier\ninteraction with MongoDB via the Python interpreter. \n\n## Installation\n\nyou can install the software with pip3 or pipenv. The `mongodbshell` only\nsupports Python 3. \n\n```python\n$ pip3 install mongodbshell\n```\n\nA complete set of API docs can be found on [read the docs](https://mongodbshell.readthedocs.io/en/latest/)\n\n## Using the mongodbshell\n\nFirst we create a `MongoDB` object. This is a proxy for all the \ncommands we can run using `MongoDBShell`.\n\n```python\n>>> client=mongodbshell.MongoDB()\n>>> client\nmongodbshell.MongoDB('test', 'test', 'mongodb://localhost:27017')\n```\n\nAs you can see a `MongoDB` object embeds the default database `test` and collection\n`test`. We can also access the native `MongoClient` object.\n\n\nEach `MongoDB` object has host of standard properties:\n```python\n>>> client\nmongodbshell.MongoDB('test', 'test', 'mongodb://localhost:27017')\n>>> client.client\nMongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True)\n>>> client.database\nDatabase(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'test')\n>>> client.collection\nCollection(Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'test'), 'test')\n>>> client.uri\n'mongodb://localhost:27017'\n>>>\n```\n\nThere are also convenience functions for the most popular operations:\n\n```python\n>>> client.is_master()\n{'ismaster': True,\n 'localTime': datetime.datetime(2019, 1, 16, 15, 15, 41, 87000),\n 'logicalSessionTimeoutMinutes': 30,\n 'maxBsonObjectSize': 16777216,\n 'maxMessageSizeBytes': 48000000,\n 'maxWireVersion': 7,\n 'maxWriteBatchSize': 100000,\n 'minWireVersion': 0,\n 'ok': 1.0,\n 'readOnly': False}\n \n>>> mongo_client.insert_one({\"name\" : \"Joe Drumgoole\", \"twitter_handle\" : \"@jdrumgoole\"})\nObjectId('5c3f4f2fc3b498d6674b08f0')\n>>> mongo_client.find_one( {\"name\" : \"Joe Drumgoole\"})\n1 {'_id': ObjectId('5c3f4b04c3b498d4a1c6ce22'),\n2 'name': 'Joe Drumgoole',\n3 'twitter_handle': '@jdrumgoole'}\n```\n\n## Line Numbers on Output\n\nLine numbers are added to output by default. You can turn off line numbers by\nsetting the `line_numbers` flag to false.\n\n```python\n>>> client.insert_one({\"name\" : \"Joe Drumgoole\", \"twitter_handle\" : \"@jdrumgoole\"})\nObjectId('5c3f4f2fc3b498d6674b08f0')\n>>> client.find_one( {\"name\" : \"Joe Drumgoole\"})\n1 {'_id': ObjectId('5c3f4b04c3b498d4a1c6ce22'),\n2 'name': 'Joe Drumgoole',\n3 'twitter_handle': '@jdrumgoole'}\n>>> client.line_numbers = False # Turn off line numbers\n>>> client.find_one( {\"name\" : \"Joe Drumgoole\"})\n{'_id': ObjectId('5c3f4b04c3b498d4a1c6ce22'),\n 'name': 'Joe Drumgoole',\n 'twitter_handle': '@jdrumgoole'}\n>>>\n```\n## Connecting to a specific MongoDB URI\n\nYou can connect to a different database by using the `MongoDB` class. Here is an\nexample connection to a [MongoDB Atlas](https://www.mongodb.com/cloud/atlas) hosted datbase. \n\n```python\n>>> from mongodbshell import MongoDB\n>>> atlas=MongoDB(uri=\"mongodb+srv://readonly:readonly@demodata-rgl39.mongodb.net/test?retryWrites=true\", database=\"demo\", collection=\"zipcodes\")\n>>> atlas.find_one()\n1 {'_id': '01069',\n2 'city': 'PALMER',\n3 'loc': [-72.328785, 42.176233],\n4 'pop': 9778,\n5 'state': 'MA'}\n\n```\n\n## Looking at large volumes of output\n\nIf you run a query in the python shell it will return a cursor and to look at\nthe objects in the cursor you need to either write a loop to consume the cursor\nor explicitly call `next()` on each cursor item.\n\n```python\n>>> c=pymongo.MongoClient(\"mongodb+srv://readonly:readonly@demodata-rgl39.mongodb.net/test?retryWrites=true\")\n>>> db=c[\"demo\"]\n>>> collection=db[\"zipcodes\"]\n>>> collection.find()\n\n>>> cursor=collection.find()\n>>> next(cursor)\n{'_id': '01069', 'city': 'PALMER', 'loc': [-72.328785, 42.176233], 'pop': 9778, 'state': 'MA'}\n>>> next(cursor)\n{'_id': '01002', 'city': 'CUSHMAN', 'loc': [-72.51565, 42.377017], 'pop': 36963, 'state': 'MA'}\n>>>\n```\n\nThis is tedious and becomes even more so when the objects are large enough to\nscroll off the screen. This is not a problem with the `mongodbshell` as the\n`MongoDB` object will automatically handle pretty printing and paginating outing. \n\n```python\n>>> atlas.find()\n1 {'_id': '01069', 'city': 'PALMER', 'loc': [-72.328785, 42.176233], 'pop': 9778, 'state': 'MA'}\n2 {'_id': '01002', 'city': 'CUSHMAN', 'loc': [-72.51565, 42.377017], 'pop': 36963, 'state': 'MA'}\n3 {'_id': '01012', 'city': 'CHESTERFIELD', 'loc': [-72.833309, 42.38167], 'pop': 177, 'state': 'MA'}\n4 {'_id': '01073', 'city': 'SOUTHAMPTON', 'loc': [-72.719381, 42.224697], 'pop': 4478, 'state': 'MA'}\n5 {'_id': '01096', 'city': 'WILLIAMSBURG', 'loc': [-72.777989, 42.408522], 'pop': 2295, 'state': 'MA'}\n6 {'_id': '01262', 'city': 'STOCKBRIDGE', 'loc': [-73.322263, 42.30104], 'pop': 2200, 'state': 'MA'}\n7 {'_id': '01240', 'city': 'LENOX', 'loc': [-73.271322, 42.364241], 'pop': 5001, 'state': 'MA'}\n8 {'_id': '01370', 'city': 'SHELBURNE FALLS', 'loc': [-72.739059, 42.602203], 'pop': 4525, 'state': 'MA'}\n9 {'_id': '01340', 'city': 'COLRAIN', 'loc': [-72.726508, 42.67905], 'pop': 2050, 'state': 'MA'}\n10 {'_id': '01462', 'city': 'LUNENBURG', 'loc': [-71.726642, 42.58843], 'pop': 9117, 'state': 'MA'}\n11 {'_id': '01473', 'city': 'WESTMINSTER', 'loc': [-71.909599, 42.548319], 'pop': 6191, 'state': 'MA'}\n12 {'_id': '01510', 'city': 'CLINTON', 'loc': [-71.682847, 42.418147], 'pop': 13269, 'state': 'MA'}\n13 {'_id': '01569', 'city': 'UXBRIDGE', 'loc': [-71.632869, 42.074426], 'pop': 10364, 'state': 'MA'}\n14 {'_id': '01775', 'city': 'STOW', 'loc': [-71.515019, 42.430785], 'pop': 5328, 'state': 'MA'}\nHit Return to continue (q or quit to exit)\n```\nPagination will dynamically adjust to screen height.\n\n## Outputting to a file\n\nThe `MongoDB` class can send output to a file by setting the `output_file` property\non the `MongoDB` class. \n\n```python\n>>> atlas.output_file=\"zipcodes.txt\"\n>>> atlas.find()\nOutput is also going to 'zipcodes.txt'\n1 {'_id': '01069', 'city': 'PALMER', 'loc': [-72.328785, 42.176233], 'pop': 9778, 'state': 'MA'}\n2 {'_id': '01002', 'city': 'CUSHMAN', 'loc': [-72.51565, 42.377017], 'pop': 36963, 'state': 'MA'}\n3 {'_id': '01012', 'city': 'CHESTERFIELD', 'loc': [-72.833309, 42.38167], 'pop': 177, 'state': 'MA'}\n4 {'_id': '01073', 'city': 'SOUTHAMPTON', 'loc': [-72.719381, 42.224697], 'pop': 4478, 'state': 'MA'}\n5 {'_id': '01096', 'city': 'WILLIAMSBURG', 'loc': [-72.777989, 42.408522], 'pop': 2295, 'state': 'MA'}\n6 {'_id': '01262', 'city': 'STOCKBRIDGE', 'loc': [-73.322263, 42.30104], 'pop': 2200, 'state': 'MA'}\n7 {'_id': '01240', 'city': 'LENOX', 'loc': [-73.271322, 42.364241], 'pop': 5001, 'state': 'MA'}\n8 {'_id': '01370', 'city': 'SHELBURNE FALLS', 'loc': [-72.739059, 42.602203], 'pop': 4525, 'state': 'MA'}\n9 {'_id': '01340', 'city': 'COLRAIN', 'loc': [-72.726508, 42.67905], 'pop': 2050, 'state': 'MA'}\n10 {'_id': '01462', 'city': 'LUNENBURG', 'loc': [-71.726642, 42.58843], 'pop': 9117, 'state': 'MA'}\n11 {'_id': '01473', 'city': 'WESTMINSTER', 'loc': [-71.909599, 42.548319], 'pop': 6191, 'state': 'MA'}\n12 {'_id': '01510', 'city': 'CLINTON', 'loc': [-71.682847, 42.418147], 'pop': 13269, 'state': 'MA'}\n13 {'_id': '01569', 'city': 'UXBRIDGE', 'loc': [-71.632869, 42.074426], 'pop': 10364, 'state': 'MA'}\n14 {'_id': '01775', 'city': 'STOW', 'loc': [-71.515019, 42.430785], 'pop': 5328, 'state': 'MA'}\n>>> print(open('zipcodes.txt').read())\n{'_id': '01069', 'city': 'PALMER', 'loc': [-72.328785, 42.176233], 'pop': 9778, 'state': 'MA'}\n{'_id': '01002', 'city': 'CUSHMAN', 'loc': [-72.51565, 42.377017], 'pop': 36963, 'state': 'MA'}\n{'_id': '01012', 'city': 'CHESTERFIELD', 'loc': [-72.833309, 42.38167], 'pop': 177, 'state': 'MA'}\n{'_id': '01073', 'city': 'SOUTHAMPTON', 'loc': [-72.719381, 42.224697], 'pop': 4478, 'state': 'MA'}\n{'_id': '01096', 'city': 'WILLIAMSBURG', 'loc': [-72.777989, 42.408522], 'pop': 2295, 'state': 'MA'}\n{'_id': '01262', 'city': 'STOCKBRIDGE', 'loc': [-73.322263, 42.30104], 'pop': 2200, 'state': 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objects. \n\n`MongoDB.line_numbers` : Bool. 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