1557289876
Python is a powerful and flexible programming language used by millions of developers around the world to build their applications. It comes as no surprise that Python developers commonly leverage MongoDB hosting, the most popular NoSQL database, for their deployments due to its flexible nature and lack of schema requirements.
So, what's the best way to use MongoDB with Python? PyMongo is a Python distribution containing tools for working with MongoDB, and the recommended Python MongoDB driver. It is a fairly mature driver that supports most of the common operations with the database, and you can check out this tutorial for an introduction to the PyMongo driver.
When deploying in production, it's highly recommended to setup in a MongoDB replica set configuration so your data is geographically distributed for high availability. It is also recommended that SSL connections be enabled to encrypt the client-database traffic. We often undertake testing of failover characteristics of various MongoDB drivers to qualify them for production use cases, or when our customers ask us for advice. In this post, we show you how to connect to an SSL-enabled MongoDB replica set configured with self-signed certificates using PyMongo, and how to test MongoDB failover behavior in your code.
The first step is to ensure that the right versions of PyMongo and its dependencies are installed. This guide helps you in sorting out the dependencies, and the driver compatibility matrix can be found here.
The mongo_client.MongoClient parameters that are of interest to us are ssland ss_ca_cert. In order to connect to an SSL-enabled MongoDB endpoint that uses a self-signed certificate, ssl must be set to True and ss_ca_cert must point to the CA certificate file.
If you are a ScaleGrid customer, you can download the CA certificate file for your MongoDB clusters from the ScaleGrid console as shown here:
So, a connection snippet would look like:
>>> import pymongo >>> MONGO_URI = 'mongodb://rwuser:@SG-example-0.servers.mongodirector.com:27017,SG-example-1.servers.mongodirector.com:27017,SG-example-2.servers.mongodirector.com:27017/admin?replicaSet=RS-example&ssl=true' >>> client = pymongo.MongoClient(MONGO_URI, ssl = True, ssl_ca_certs = '') >>> print("Databases - " + str(client.list_database_names())) Databases - ['admin', 'local', 'test'] >>> client.close() >>>
If you are using your own self-signed certificates where hostname verification might fail, you will also have to set the ssl_match_hostnameparameter to False. Like the driver documentation says, this is not recommended as it makes the connection susceptible to man-in-the-middle attacks.
With MongoDB deployments, failovers aren't considered major events as they were with traditional database management systems. Although most MongoDB drivers try to abstract this event, developers should understand and design their applications for such behavior, as applications should expect transient network errors and retry before percolating errors up.
You can test the resilience of your applications by inducing failovers while your workload runs. The easiest way to induce failover is to run the rs.stepDown() command:
RS-example-0:PRIMARY> rs.stepDown() 2019-04-18T19:44:42.257+0530 E QUERY [thread1] Error: error doing query: failed: network error while attempting to run command 'replSetStepDown' on host 'SG-example-1.servers.mongodirector.com:27017' : DB.prototype.runCommand@src/mongo/shell/db.js:168:1 DB.prototype.adminCommand@src/mongo/shell/db.js:185:1 rs.stepDown@src/mongo/shell/utils.js:1305:12 @(shell):1:1 2019-04-18T19:44:42.261+0530 I NETWORK [thread1] trying reconnect to SG-example-1.servers.mongodirector.com:27017 (X.X.X.X) failed 2019-04-18T19:44:43.267+0530 I NETWORK [thread1] reconnect SG-example-1.servers.mongodirector.com:27017 (X.X.X.X) ok RS-example-0:SECONDARY>
One of the ways I like to test the behavior of drivers is by writing a simple 'perpetual' writer app. This would be simple code that keeps writing to the database unless interrupted by the user, and would print all exceptions it encounters to help us understand the driver and database behavior. I also keep track of the data it writes to ensure that there's no unreported data loss in the test. Here's the relevant part of test code we will use to test our MongoDB failover behavior:
import logging import traceback ... import pymongo ... logger = logging.getLogger("test")MONGO_URI = ‘mongodb://rwuser:@SG-example-0.servers.mongodirector.com:48273,SG-example-1.servers.mongodirector.com:27017,SG-example-2.servers.mongodirector.com:27017/admin?replicaSet=RS-example-0&ssl=true’
try:
logger.info(“Attempting to connect…”)
client = pymongo.MongoClient(MONGO_URI, ssl = True, ssl_ca_certs = ‘path-to-cacert.pem’)
db = client[‘test’]
collection = db[‘test’]
i = 0
while True:
try:
text = ‘’.join(random.choices(string.ascii_uppercase + string.digits, k = 3))
doc = { “idx”: i, “date” : datetime.utcnow(), “text” : text}
i += 1
id = collection.insert_one(doc).inserted_id
logger.info("Record inserted - id: " + str(id))
sleep(3)
except pymongo.errors.ConnectionFailure as e:
logger.error("ConnectionFailure seen: " + str(e))
traceback.print_exc(file = sys.stdout)
logger.info(“Retrying…”)logger.info("Done...")
except Exception as e:
logger.error("Exception seen: " + str(e))
traceback.print_exc(file = sys.stdout)
finally:
client.close()
The sort of entries that this writes look like:
RS-example-0:PRIMARY> db.test.find()
{ “_id” : ObjectId(“5cb6d6269ece140f18d05438”), “idx” : 0, “date” : ISODate(“2019-04-17T07:30:46.533Z”), “text” : “400” }
{ “_id” : ObjectId(“5cb6d6299ece140f18d05439”), “idx” : 1, “date” : ISODate(“2019-04-17T07:30:49.755Z”), “text” : “X63” }
{ “_id” : ObjectId(“5cb6d62c9ece140f18d0543a”), “idx” : 2, “date” : ISODate(“2019-04-17T07:30:52.976Z”), “text” : “5BX” }
{ “_id” : ObjectId(“5cb6d6329ece140f18d0543c”), “idx” : 4, “date” : ISODate(“2019-04-17T07:30:58.001Z”), “text” : “TGQ” }
{ “_id” : ObjectId(“5cb6d63f9ece140f18d0543d”), “idx” : 5, “date” : ISODate(“2019-04-17T07:31:11.417Z”), “text” : “ZWA” }
{ “_id” : ObjectId(“5cb6d6429ece140f18d0543e”), “idx” : 6, “date” : ISODate(“2019-04-17T07:31:14.654Z”), “text” : “WSR” }
…
Notice that we catch the ConnectionFailure exception to deal with all network-related issues we may encounter due to failovers - we print the exception and continue to attempt to write to the database. The driver documentation recommends that:
If an operation fails because of a network error, ConnectionFailure is raised and the client reconnects in the background. Application code should handle this exception (recognizing that the operation failed) and then continue to execute.
Let’s run this and do a database failover while it executes. Here’s what happens:
04/17/2019 12:49:17 PM INFO Attempting to connect…
04/17/2019 12:49:20 PM INFO Record inserted - id: 5cb6d3789ece145a2408cbc7
04/17/2019 12:49:23 PM INFO Record inserted - id: 5cb6d37b9ece145a2408cbc8
04/17/2019 12:49:27 PM INFO Record inserted - id: 5cb6d37e9ece145a2408cbc9
04/17/2019 12:49:30 PM ERROR PyMongoError seen: connection closed
Traceback (most recent call last):
id = collection.insert_one(doc).inserted_id
File “C:\Users\Random\AppData\Local\Programs\Python\Python36-32\lib\site-packages\pymongo\collection.py”, line 693, in insert_one
session=session),
…
File “C:\Users\Random\AppData\Local\Programs\Python\Python36-32\lib\site-packages\pymongo\network.py”, line 173, in receive_message
_receive_data_on_socket(sock, 16))
File “C:\Users\Random\AppData\Local\Programs\Python\Python36-32\lib\site-packages\pymongo\network.py”, line 238, in _receive_data_on_socket
raise AutoReconnect(“connection closed”)
pymongo.errors.AutoReconnect: connection closed
04/17/2019 12:49:30 PM INFO Retrying…
04/17/2019 12:49:42 PM INFO Record inserted - id: 5cb6d3829ece145a2408cbcb
04/17/2019 12:49:45 PM INFO Record inserted - id: 5cb6d3919ece145a2408cbcc
04/17/2019 12:49:49 PM INFO Record inserted - id: 5cb6d3949ece145a2408cbcd
04/17/2019 12:49:52 PM INFO Record inserted - id: 5cb6d3989ece145a2408cbce
Notice that the driver takes about 12 seconds to understand the new topology, connect to the new primary, and continue writing. The exception raised is errors.AutoReconnect which is a subclass of ConnectionFailure.
You could do a few more runs to see what other exceptions are seen. For example, here’s another exception trace I encountered:
id = collection.insert_one(doc).inserted_id
File “C:\Users\Random\AppData\Local\Programs\Python\Python36-32\lib\site-packages\pymongo\collection.py”, line 693, in insert_one
session=session),
…
File “C:\Users\Randome\AppData\Local\Programs\Python\Python36-32\lib\site-packages\pymongo\network.py”, line 150, in command
parse_write_concern_error=parse_write_concern_error)
File “C:\Users\Random\AppData\Local\Programs\Python\Python36-32\lib\site-packages\pymongo\helpers.py”, line 132, in _check_command_response
raise NotMasterError(errmsg, response)
pymongo.errors.NotMasterError: not master
This exception is also a sub class of ConnectionFailure.
Another area to test MongoDB failover behavior would be seeing how other parameter variations affect the results. One parameter that is relevant is ‘retryWrites’:
retryWrites: (boolean) Whether supported write operations executed within this MongoClient will be retried once after a network error on MongoDB 3.6+. Defaults to False.
Let’s see how this parameter works with a failover. The only change made to the code is:
client = pymongo.MongoClient(MONGO_URI, ssl = True, ssl_ca_certs = ‘path-to-cacert.pem’, retryWrites = True)
Let’s run it now, and then do a database system failover:
04/18/2019 08:49:30 PM INFO Attempting to connect…
04/18/2019 08:49:35 PM INFO Record inserted - id: 5cb895869ece146554010c77
04/18/2019 08:49:38 PM INFO Record inserted - id: 5cb8958a9ece146554010c78
04/18/2019 08:49:41 PM INFO Record inserted - id: 5cb8958d9ece146554010c79
04/18/2019 08:49:44 PM INFO Record inserted - id: 5cb895909ece146554010c7a
04/18/2019 08:49:48 PM INFO Record inserted - id: 5cb895939ece146554010c7b <<< Failover around this time
04/18/2019 08:50:04 PM INFO Record inserted - id: 5cb895979ece146554010c7c
04/18/2019 08:50:07 PM INFO Record inserted - id: 5cb895a79ece146554010c7d
04/18/2019 08:50:10 PM INFO Record inserted - id: 5cb895aa9ece146554010c7e
04/18/2019 08:50:14 PM INFO Record inserted - id: 5cb895ad9ece146554010c7f
…
Notice how the insert after the failover takes about 12 seconds, but goes through successfully as the retryWrites parameter ensures the failed write is retried. Remember that setting this parameter doesn’t absolve you from handling the ConnectionFailure exception - you need to worry about reads and other operations whose behavior is not affected by this parameter. It also doesn’t completely solve the issue, even for supported operations - sometimes failovers can take longer to complete and retryWrites alone will not be enough.
rs.stepDown() induces a rather quick failover, as the replica set primary is intructed to become a secondary, and the secondaries hold an election to determine the new primary. In production deployments, network load, partition, and other such issues delay the detection of unavailability of the primary server, thus, prolonging your failover time. You would also often run into PyMongo errors like errors.ServerSelectionTimeoutError, errors.NetworkTimeout, etc. during network issues and failovers.
If this occurs very often, you must look to tweak the timeout parameters. The related MongoClient timeout parameters are serverSelectionTimeoutMS, connectTimeoutMS, and socketTimeoutMS. Of these, selecting a larger value for serverSelectionTimeoutMS most often helps in dealing with errors during failovers:
serverSelectionTimeoutMS: (integer) Controls how long (in milliseconds) the driver will wait to find an available, appropriate server to carry out a database operation; while it is waiting, multiple server monitoring operations may be carried out, each controlled by connectTimeoutMS. Defaults to 30000 (30 seconds).
Ready to use MongoDB in your Python application? Check out our Getting Started with Python and MongoDB article to see how you can get up and running in just 5 easy steps. ScaleGrid is the only MongoDB DBaaS providerthat it gives you full SSH access to your instances so you can run your Python server on the same machine as your MongoDB server. Automate your MongoDB cloud deployments on AWS, Azure, or DigitalOcean with dedicated servers, high availability, and disaster recovery so you can focus on developing your Python application.
Originally published by ScaleGrid at dev.to
----------------------------------------------------------------------------------------------------------
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The electric scooter revolution has caught on super-fast taking many cities across the globe by storm. eScooters, a renovated version of old-school scooters now turned into electric vehicles are an environmentally friendly solution to current on-demand commute problems. They work on engines, like cars, enabling short traveling distances without hassle. The result is that these groundbreaking electric machines can now provide faster transport for less — cheaper than Uber and faster than Metro.
Since they are durable, fast, easy to operate and maintain, and are more convenient to park compared to four-wheelers, the eScooters trend has and continues to spike interest as a promising growth area. Several companies and universities are increasingly setting up shop to provide eScooter services realizing a would-be profitable business model and a ready customer base that is university students or residents in need of faster and cheap travel going about their business in school, town, and other surrounding areas.
In many countries including the U.S., Canada, Mexico, U.K., Germany, France, China, Japan, India, Brazil and Mexico and more, a growing number of eScooter users both locals and tourists can now be seen effortlessly passing lines of drivers stuck in the endless and unmoving traffic.
A recent report by McKinsey revealed that the E-Scooter industry will be worth― $200 billion to $300 billion in the United States, $100 billion to $150 billion in Europe, and $30 billion to $50 billion in China in 2030. The e-Scooter revenue model will also spike and is projected to rise by more than 20% amounting to approximately $5 billion.
And, with a necessity to move people away from high carbon prints, traffic and congestion issues brought about by car-centric transport systems in cities, more and more city planners are developing more bike/scooter lanes and adopting zero-emission plans. This is the force behind the booming electric scooter market and the numbers will only go higher and higher.
Companies that have taken advantage of the growing eScooter trend develop an appthat allows them to provide efficient eScooter services. Such an app enables them to be able to locate bike pick-up and drop points through fully integrated google maps.
It’s clear that e scooters will increasingly become more common and the e-scooter business model will continue to grab the attention of manufacturers, investors, entrepreneurs. All this should go ahead with a quest to know what are some of the best electric bikes in the market especially for anyone who would want to get started in the electric bikes/scooters rental business.
We have done a comprehensive list of the best electric bikes! Each bike has been reviewed in depth and includes a full list of specs and a photo.
https://www.kickstarter.com/projects/enkicycles/billy-were-redefining-joyrides
To start us off is the Billy eBike, a powerful go-anywhere urban electric bike that’s specially designed to offer an exciting ride like no other whether you want to ride to the grocery store, cafe, work or school. The Billy eBike comes in 4 color options – Billy Blue, Polished aluminium, Artic white, and Stealth black.
Price: $2490
Available countries
Available in the USA, Europe, Asia, South Africa and Australia.This item ships from the USA. Buyers are therefore responsible for any taxes and/or customs duties incurred once it arrives in your country.
Features
Specifications
Why Should You Buy This?
**Who Should Ride Billy? **
Both new and experienced riders
**Where to Buy? **Local distributors or ships from the USA.
Featuring a sleek and lightweight aluminum frame design, the 200-Series ebike takes your riding experience to greater heights. Available in both black and white this ebike comes with a connected app, which allows you to plan activities, map distances and routes while also allowing connections with fellow riders.
Price: $2099.00
Available countries
The Genze 200 series e-Bike is available at GenZe retail locations across the U.S or online via GenZe.com website. Customers from outside the US can ship the product while incurring the relevant charges.
Features
Specifications
https://ebikestore.com/shop/norco-vlt-s2/
The Norco VLT S2 is a front suspension e-Bike with solid components alongside the reliable Bosch Performance Line Power systems that offer precise pedal assistance during any riding situation.
Price: $2,699.00
Available countries
This item is available via the various Norco bikes international distributors.
Features
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http://www.bodoevs.com/bodoev/products_show.asp?product_id=13
Manufactured by Bodo Vehicle Group Limited, the Bodo EV is specially designed for strong power and extraordinary long service to facilitate super amazing rides. The Bodo Vehicle Company is a striking top in electric vehicles brand field in China and across the globe. Their Bodo EV will no doubt provide your riders with high-level riding satisfaction owing to its high-quality design, strength, breaking stability and speed.
Price: $799
Available countries
This item ships from China with buyers bearing the shipping costs and other variables prior to delivery.
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1595494844
Are you leading an organization that has a large campus, e.g., a large university? You are probably thinking of introducing an electric scooter/bicycle fleet on the campus, and why wouldn’t you?
Introducing micro-mobility in your campus with the help of such a fleet would help the people on the campus significantly. People would save money since they don’t need to use a car for a short distance. Your campus will see a drastic reduction in congestion, moreover, its carbon footprint will reduce.
Micro-mobility is relatively new though and you would need help. You would need to select an appropriate fleet of vehicles. The people on your campus would need to find electric scooters or electric bikes for commuting, and you need to provide a solution for this.
To be more specific, you need a short-term electric bike rental app. With such an app, you will be able to easily offer micro-mobility to the people on the campus. We at Devathon have built Autorent exactly for this.
What does Autorent do and how can it help you? How does it enable you to introduce micro-mobility on your campus? We explain these in this article, however, we will touch upon a few basics first.
You are probably thinking about micro-mobility relatively recently, aren’t you? A few relevant insights about it could help you to better appreciate its importance.
Micro-mobility is a new trend in transportation, and it uses vehicles that are considerably smaller than cars. Electric scooters (e-scooters) and electric bikes (e-bikes) are the most popular forms of micro-mobility, however, there are also e-unicycles and e-skateboards.
You might have already seen e-scooters, which are kick scooters that come with a motor. Thanks to its motor, an e-scooter can achieve a speed of up to 20 km/h. On the other hand, e-bikes are popular in China and Japan, and they come with a motor, and you can reach a speed of 40 km/h.
You obviously can’t use these vehicles for very long commutes, however, what if you need to travel a short distance? Even if you have a reasonable public transport facility in the city, it might not cover the route you need to take. Take the example of a large university campus. Such a campus is often at a considerable distance from the central business district of the city where it’s located. While public transport facilities may serve the central business district, they wouldn’t serve this large campus. Currently, many people drive their cars even for short distances.
As you know, that brings its own set of challenges. Vehicular traffic adds significantly to pollution, moreover, finding a parking spot can be hard in crowded urban districts.
Well, you can reduce your carbon footprint if you use an electric car. However, electric cars are still new, and many countries are still building the necessary infrastructure for them. Your large campus might not have the necessary infrastructure for them either. Presently, electric cars don’t represent a viable option in most geographies.
As a result, you need to buy and maintain a car even if your commute is short. In addition to dealing with parking problems, you need to spend significantly on your car.
All of these factors have combined to make people sit up and think seriously about cars. Many people are now seriously considering whether a car is really the best option even if they have to commute only a short distance.
This is where micro-mobility enters the picture. When you commute a short distance regularly, e-scooters or e-bikes are viable options. You limit your carbon footprints and you cut costs!
Businesses have seen this shift in thinking, and e-scooter companies like Lime and Bird have entered this field in a big way. They let you rent e-scooters by the minute. On the other hand, start-ups like Jump and Lyft have entered the e-bike market.
Think of your campus now! The people there might need to travel short distances within the campus, and e-scooters can really help them.
What advantages can you get from micro-mobility? Let’s take a deeper look into this question.
Micro-mobility can offer several advantages to the people on your campus, e.g.:
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Learn the most popular NoSQL / document database: MongoDB. In this quickstart tutorial, you’ll be up and running with MongoDB and Python.
⭐️Course Contents⭐️
⌨️ (0:00:00) Welcome
⌨️ (0:04:33) Intro to MongoDB
⌨️ (0:07:49) How do document DBs work?
⌨️ (0:10:34) Who uses MongoDB
⌨️ (0:13:02) Data modeling
⌨️ (0:16:30) Modeling guidelines
⌨️ (0:22:11) Integration database
⌨️ (0:24:23) Getting demo code
⌨️ (0:30:07) How ODMs work?
⌨️ (0:32:55) Introduction to mongoengine
⌨️ (0:34:01) Demo: Registering connections with MongoEngine
⌨️ (0:37:20) Concept: Registering connections
⌨️ (0:39:14) Demo: Defining mongoengine entities (classes)
⌨️ (0:45:22) Concept: mongoengine entities
⌨️ (0:49:03) Demo: Create a new account
⌨️ (0:56:55) Demo: Robo 3T for viewing and managing data
⌨️ (0:58:18) Demo: Login
⌨️ (1:00:07) Demo: Register a cage
⌨️ (1:10:28) Demo: Add a bookable time as a host
⌨️ (1:16:13) Demo: Managing your snakes as a guest
⌨️ (1:19:18) Demo: Book a cage as a guest
⌨️ (1:33:41) Demo: View your bookings as guest
⌨️ (1:41:29) Demo: View bookings as host
⌨️ (1:46:18) Concept: Inserting documents
⌨️ (1:47:28) Concept: Queries
⌨️ (1:48:09) Concept: Querying subdocuments with mongoengine
⌨️ (1:49:37) Concept: Query using operators
⌨️ (1:50:24) Concept: Updating via whole documents
⌨️ (1:51:46) Concept: Updating via in-place operators
⌨️ (1:54:01) Conclusion
📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=E-1xI85Zog8&list=PLWKjhJtqVAbnqBxcdjVGgT3uVR10bzTEB&index=10
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With more of us using smartphones, the popularity of mobile applications has exploded. In the digital era, the number of people looking for products and services online is growing rapidly. Smartphone owners look for mobile applications that give them quick access to companies’ products and services. As a result, mobile apps provide customers with a lot of benefits in just one device.
Likewise, companies use mobile apps to increase customer loyalty and improve their services. Mobile Developers are in high demand as companies use apps not only to create brand awareness but also to gather information. For that reason, mobile apps are used as tools to collect valuable data from customers to help companies improve their offer.
There are many types of mobile applications, each with its own advantages. For example, native apps perform better, while web apps don’t need to be customized for the platform or operating system (OS). Likewise, hybrid apps provide users with comfortable user experience. However, you may be wondering how long it takes to develop an app.
To give you an idea of how long the app development process takes, here’s a short guide.
_Average time spent: two to five weeks _
This is the initial stage and a crucial step in setting the project in the right direction. In this stage, you brainstorm ideas and select the best one. Apart from that, you’ll need to do some research to see if your idea is viable. Remember that coming up with an idea is easy; the hard part is to make it a reality.
All your ideas may seem viable, but you still have to run some tests to keep it as real as possible. For that reason, when Web Developers are building a web app, they analyze the available ideas to see which one is the best match for the targeted audience.
Targeting the right audience is crucial when you are developing an app. It saves time when shaping the app in the right direction as you have a clear set of objectives. Likewise, analyzing how the app affects the market is essential. During the research process, App Developers must gather information about potential competitors and threats. This helps the app owners develop strategies to tackle difficulties that come up after the launch.
The research process can take several weeks, but it determines how successful your app can be. For that reason, you must take your time to know all the weaknesses and strengths of the competitors, possible app strategies, and targeted audience.
The outcomes of this stage are app prototypes and the minimum feasible product.
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