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![Database Instance #!/bin/python from pymongo import MongoClient mc = MongoClient() ! db = mc['zurich_pug'] ! #or ! db = mc.zurich_pug database instance](https://image.slidesharecdn.com/mongodbpython-150309065254-conversion-gate01/75/MongoDB-and-Python-20-2048.jpg)
![Collection Instance #!/bin/python from pymongo import MongoClient mc = MongoClient() ! coll = mc[‘zurich_pug']['testcollection'] ! #or ! coll = mc.zurich_pug.testcollection collection instance](https://image.slidesharecdn.com/mongodbpython-150309065254-conversion-gate01/75/MongoDB-and-Python-21-2048.jpg)
![Insert #!/bin/python from pymongo import MongoClient mc = MongoClient() ! coll = mc['zurich_pug']['testcollection'] ! ! coll.insert( {'field_one': 'some value'})](https://image.slidesharecdn.com/mongodbpython-150309065254-conversion-gate01/75/MongoDB-and-Python-25-2048.jpg)
![Find #!/bin/python from pymongo import MongoClient mc = MongoClient() ! coll = mc['zurich_pug']['testcollection'] ! ! cur = coll.find( {'field_one': 'some value'}) ! for d in cur: print d](https://image.slidesharecdn.com/mongodbpython-150309065254-conversion-gate01/75/MongoDB-and-Python-26-2048.jpg)
![Update #!/bin/python from pymongo import MongoClient mc = MongoClient() ! coll = mc['zurich_pug']['testcollection'] ! ! result = coll.update( {'field_one': 'some value'}, {"$set": {'field_one': 'new_value'}} ) ! print(result) !](https://image.slidesharecdn.com/mongodbpython-150309065254-conversion-gate01/75/MongoDB-and-Python-27-2048.jpg)
![Remove #!/bin/python from pymongo import MongoClient mc = MongoClient() ! coll = mc['zurich_pug']['testcollection'] ! ! result = coll.remove( {'field_one': 'some value'}) ! print(result) !](https://image.slidesharecdn.com/mongodbpython-150309065254-conversion-gate01/75/MongoDB-and-Python-28-2048.jpg)
![Aggregation Framework #!/bin/python from pymongo import MongoClient mc = MongoClient() ! coll = mc['zurich_pug']['testcollection'] ! ! cur = coll.aggregate( [ {"$match": {'field_one': {"$exists": True }}} , {"$project": { "new_label": "$field_one" }} ] ) ! for d in cur: print(d)](https://image.slidesharecdn.com/mongodbpython-150309065254-conversion-gate01/75/MongoDB-and-Python-31-2048.jpg)
![GridFS #!/bin/python from pymongo import MongoClient import gridfs ! ! mc = MongoClient() database = mc.grid_example ! ! gfs = gridfs.GridFS( database) ! read_file = open( '/tmp/somefile', 'r') ! gfs.put(read_file, author='Norberto', tags=['awesome', 'zurich', 'pug']) call grids lib w/ database](https://image.slidesharecdn.com/mongodbpython-150309065254-conversion-gate01/75/MongoDB-and-Python-34-2048.jpg)
![GridFS #!/bin/python from pymongo import MongoClient import gridfs ! ! mc = MongoClient() database = mc.grid_example ! ! gfs = gridfs.GridFS( database) ! read_file = open( '/tmp/somefile', 'r') ! gfs.put(read_file, author='Norberto', tags=['awesome', 'zurich', 'pug']) open file for reading](https://image.slidesharecdn.com/mongodbpython-150309065254-conversion-gate01/75/MongoDB-and-Python-35-2048.jpg)
![GridFS #!/bin/python from pymongo import MongoClient import gridfs ! ! mc = MongoClient() database = mc.grid_example ! ! gfs = gridfs.GridFS( database) ! read_file = open( '/tmp/somefile', 'r') ! gfs.put(read_file, author='Norberto', tags=['awesome', 'zurich', 'pug']) call put to store file and metadata](https://image.slidesharecdn.com/mongodbpython-150309065254-conversion-gate01/75/MongoDB-and-Python-36-2048.jpg)
![Compound Field Index from pymongo import ASCENDING, DESCENDING, MongoClient mc = MongoClient() ! coll = mc.zurich_pug.testcollection ! coll.ensure_index( [('field_ascending', ASCENDING), ('field_descending', DESCENDING)] ) indexed fields indexing order](https://image.slidesharecdn.com/mongodbpython-150309065254-conversion-gate01/75/MongoDB-and-Python-43-2048.jpg)
![Multikey Field Index mc = MongoClient() ! coll = mc.zurich_pug.testcollection ! ! coll.insert( {'array_field': [1, 2, 54, 89]}) ! coll.ensure_index( 'array_field') indexed field](https://image.slidesharecdn.com/mongodbpython-150309065254-conversion-gate01/75/MongoDB-and-Python-44-2048.jpg)
![Geospatial Field Index from pymongo import GEOSPHERE import geojson ! ! p = geojson.Point( [-73.9858603477478, 40.75929362758241]) ! coll.insert( {'point', p) ! coll.ensure_index( [( 'point', GEOSPHERE )]) index type](https://image.slidesharecdn.com/mongodbpython-150309065254-conversion-gate01/75/MongoDB-and-Python-45-2048.jpg)
Uploaded byNorberto Leite
MongoDB and Python
The document is a presentation by Norberto Leite, a technical evangelist for MongoDB, detailing its features and the use of PyMongo, the official Python driver for MongoDB. It covers key functionalities such as CRUD operations, aggregation frameworks, and storage solutions like GridFS. The document also touches on indexing mechanisms and encourages testing MongoDB 3.0 ahead of its release.
MongoDB and Python
- 2. MongoDB + Python NorbertoLeite Technical Evangelist norberto@mongodb.com
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- 4. Ola, I'm Norberto NorbertoLeite Technical Evangelist ! Madrid, Spain @nleite norberto@mongodb.com http://www.mongodb.com/norberto
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- 6. MongoDB GENERAL PURPOSE DOCUMENTDATABASE OPEN-SOURCE
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- 8. MongoDB Features JSON DocumentModel with Dynamic Schemas Auto-Sharding for Horizontal Scalability Text Search Aggregation Framework and MapReduce Full, Flexible Index Support and Rich Queries Built-In Replication for High Availability Advanced Security Large Media Storage with GridFS
- 9. MongoDB Inc. 400+ employees2,000+ customers Over $311 million in funding13 offices around the world
- 10. THE LARGEST ECOSYSTEM 9,000,000+ MongoDBDownloads 250,000+ Online Education Registrants 35,000+ MongoDB User Group Members 35,000+ MongoDB Management Service (MMS) Users 750+ Technology and Services Partners 2,000+ Customers Across All Industries
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- 12. pymongo • MongoDB Pythonofficial driver • Rockstart developer team • Jesse Jiryu Davis, Bernie Hackett • One of oldest and better maintained drivers • Python and MongoDB are a natural fit • BSON is very similar to dictionaries • (everyone likes dictionaries) • http://api.mongodb.org/python/current/ • https://github.com/mongodb/mongo-python-driver
- 13. pymongo 2.8 • Supportfor upcoming MongoDB 3.0 • New get collections and get indexes commands for Wired Tiger • Backward compatible w/ 2.6 ! • Future releases of pymongo (3.0) • Server discovery spec • Monitoring spec • Faster client startup when connecting to Replica Set • Faster failover • More robust replica set connections • API clean up
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- 15. Connecting #!/bin/python from pymongo importMongoClient ! mc = MongoClient() client instance
- 16. Connecting #!/bin/python from pymongo importMongoClient ! uri = 'mongodb://127.0.0.1' mc = MongoClient(uri)
- 17. Connecting #!/bin/python from pymongo importMongoClient ! uri = 'mongodb://127.0.0.1' mc = MongoClient(host=uri, max_pool_size=10)
- 18. Connecting to ReplicaSet #!/bin/python from pymongo import MongoClient ! uri = ‘mongodb://127.0.0.1?replicaSet=MYREPLICA' mc = MongoClient(uri)
- 19. Connecting to ReplicaSet #!/bin/python from pymongo import MongoClient ! uri = ‘mongodb://127.0.0.1' mc = MongoClient(host=uri, replicaSet='MYREPLICA')
- 20. Database Instance #!/bin/python from pymongoimport MongoClient mc = MongoClient() ! db = mc['zurich_pug'] ! #or ! db = mc.zurich_pug database instance
- 21. Collection Instance #!/bin/python from pymongoimport MongoClient mc = MongoClient() ! coll = mc[‘zurich_pug']['testcollection'] ! #or ! coll = mc.zurich_pug.testcollection collection instance
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- 23. Operations • Insert • Remove •Update • Query • Aggregate • Create Indexes • …
- 24. CRUD • Insert • Remove •Update • Query • Aggregate • Create Indexes • …
- 25. Insert #!/bin/python from pymongo importMongoClient mc = MongoClient() ! coll = mc['zurich_pug']['testcollection'] ! ! coll.insert( {'field_one': 'some value'})
- 26. Find #!/bin/python from pymongo importMongoClient mc = MongoClient() ! coll = mc['zurich_pug']['testcollection'] ! ! cur = coll.find( {'field_one': 'some value'}) ! for d in cur: print d
- 27. Update #!/bin/python from pymongo importMongoClient mc = MongoClient() ! coll = mc['zurich_pug']['testcollection'] ! ! result = coll.update( {'field_one': 'some value'}, {"$set": {'field_one': 'new_value'}} ) ! print(result) !
- 28. Remove #!/bin/python from pymongo importMongoClient mc = MongoClient() ! coll = mc['zurich_pug']['testcollection'] ! ! result = coll.remove( {'field_one': 'some value'}) ! print(result) !
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- 30. Aggregation Framework • Analyticalworkload solution • Pipeline processing • Several Stages • $match • $group • $project • $unwind • $sort • $limit • $skip • $out ! • http://docs.mongodb.org/manual/aggregation/
- 31. Aggregation Framework #!/bin/python from pymongoimport MongoClient mc = MongoClient() ! coll = mc['zurich_pug']['testcollection'] ! ! cur = coll.aggregate( [ {"$match": {'field_one': {"$exists": True }}} , {"$project": { "new_label": "$field_one" }} ] ) ! for d in cur: print(d)
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- 33. GridFS • MongoDB hasa 16MB document size limit • So how can we store data bigger than 16MB? • Media files (images, pdf’s, long binary files …) • GridFS • Convention more than a feature • All drivers implement this convention • pymongo is no different • Very flexible approach • Handy out-of-the-box solution
- 34. GridFS #!/bin/python from pymongo import MongoClient import gridfs ! ! mc = MongoClient() database = mc.grid_example ! ! gfs = gridfs.GridFS( database) ! read_file = open( '/tmp/somefile', 'r') ! gfs.put(read_file, author='Norberto', tags=['awesome', 'zurich', 'pug']) call grids lib w/ database
- 35. GridFS #!/bin/python from pymongo import MongoClient import gridfs ! ! mc = MongoClient() database = mc.grid_example ! ! gfs = gridfs.GridFS( database) ! read_file = open( '/tmp/somefile', 'r') ! gfs.put(read_file, author='Norberto', tags=['awesome', 'zurich', 'pug']) open file for reading
- 36. GridFS #!/bin/python from pymongo import MongoClient import gridfs ! ! mc = MongoClient() database = mc.grid_example ! ! gfs = gridfs.GridFS( database) ! read_file = open( '/tmp/somefile', 'r') ! gfs.put(read_file, author='Norberto', tags=['awesome', 'zurich', 'pug']) call put to store file and metadata
- 37. GridFS mongo nair(mongod-‐3.1.0-‐pre-‐) grid_sample> show dbs grid_sample 0.246GB local 0.000GB nair(mongod-‐3.1.0-‐pre-‐) grid_sample> show collections fs.chunks 258.995MB / 252.070MB fs.files 0.000MB / 0.016MB database created
- 38. GridFS mongo nair(mongod-‐3.1.0-‐pre-‐) grid_sample> show dbs grid_sample 0.246GB local 0.000GB nair(mongod-‐3.1.0-‐pre-‐) grid_sample> show collections fs.chunks 258.995MB / 252.070MB fs.files 0.000MB / 0.016MB 2 collections
- 39. GridFS mongo nair(mongod-‐3.1.0-‐pre-‐) grid_sample> show dbs grid_sample 0.246GB local 0.000GB nair(mongod-‐3.1.0-‐pre-‐) grid_sample> show collections fs.chunks 258.995MB / 252.070MB fs.files 0.000MB / 0.016MB chunks collection holds binary data files holds metada data
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- 41. Indexes • Single Field •Compound • Multikey • Geospatial • 2d • 2dSphere - GeoJSON • Full Text • Hash Based • TTL indexes • Unique • Sparse
- 42. Single Field Index frompymongo import ASCENDING, MongoClient mc = MongoClient() ! coll = mc.zurich_pug.testcollection ! coll.ensure_index( 'some_single_field', ASCENDING ) indexed field indexing order
- 43. Compound Field Index frompymongo import ASCENDING, DESCENDING, MongoClient mc = MongoClient() ! coll = mc.zurich_pug.testcollection ! coll.ensure_index( [('field_ascending', ASCENDING), ('field_descending', DESCENDING)] ) indexed fields indexing order
- 44. Multikey Field Index mc= MongoClient() ! coll = mc.zurich_pug.testcollection ! ! coll.insert( {'array_field': [1, 2, 54, 89]}) ! coll.ensure_index( 'array_field') indexed field
- 45. Geospatial Field Index frompymongo import GEOSPHERE import geojson ! ! p = geojson.Point( [-73.9858603477478, 40.75929362758241]) ! coll.insert( {'point', p) ! coll.ensure_index( [( 'point', GEOSPHERE )]) index type
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- 47. Friends • mongoengine • http://mongoengine.org/ •Motor • http://motor.readthedocs.org/en/stable/ • async driver • Tornado • Greenlets • ming • http://sourceforge.net/projects/merciless/
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- 49. Recap • MongoDB isAwesome • Specially to work with Python • pymongo • super well supported • fully in sync with MongoDB server
- 50. MongoDB 3.0 iscoming
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