These are great libraries for small full-stack teams who do not want to get lost in the complexity of front-end stuff like react, webpack, etc.
1,309 karma · joined January 3, 2010
These are great libraries for small full-stack teams who do not want to get lost in the complexity of front-end stuff like react, webpack, etc.
Regarding the getting started, probably just a a section on the steps to install cookie cutter, then the sample shell commands to bring it up with docker.
And I agree with heroku offering a good value to get started. However, do you think your audience is at that level? Furthermore what happens to my app if/when I graduate to my own server at digital ocean or kube cluster?
Which brings me to another question: who do you think this is for? Beginners or maybe more advanced devs who are needing to prototype ideas or have a greenfield project in front of them?
Myself, I am a capable dev with existing infrastructure at hand (laptop and docker swarm clusters on azure, for example).
Maybe rather than seeing a CI pipeline to heroku you could offer alternatives to push work from local docker to a kube cluster or swarm? I do that with all my projects through bitbucket pipelines CI.
However, as I've become more comfortable in the Django and python ecosystem, I have been cutting closer and closer to the stock install.
I think the cookie-cutter stuff is great for when you have a highly-opinionated way to do things (specific test frameworks, databases, patterns, etc).
Some feedback:
Authentication:
I looked at your way of authentication, and I kindly ask you take a look at djoser [1]. They have a nice authentication system for DRF with a password reset flow.
Or also maybe an integration with Auth0?
Storage:
If you replace boto3 with Apache's libcloud [2], then you make this project a little more platform agnostic. I say this as someone who works across multiple platforms. I see that django-storages even plays nicely with it also [3].
And to be honest I'm not so thrilled with Heroku as the deployment target. Maybe just beef up the README with instructions on getting started just on my laptop with pip, cookie-cutter, and docker-compose?
All in all, nice job. I'll add my star to your project and consider it next time the use case arises.
[1] - https://github.com/sunscrapers/djoser
[2] - https://libcloud.apache.org/
[3] - https://django-storages.readthedocs.io/en/latest/backends/ap...
Edit - not picking on you, but given the quality and ecosystem of libraries and ancillary tools for scrapy, I don't even consider alternatives at this point. Good on anyone who does it to learn but for actual workloads I won't consider anything else.
What what cultural cues do you get from the product / service offerings?
Google stalk the employees in the company. What can you learn about them? For example, I imagine that Uber is no longer attracting the best and brightest in light of their recent scandals.
Putting in the time to really dig into the human sides of potential employers is important.
Reach out to former employees of said companies. See if you can get an opinion on things. I'm often surprised at how candid people will be, even over Skype.
Then, at the end of it all, you should listen to your gut feeling.
ACI current pricing as of Dec 2017
1 create request x 1GB memory x 1 month (2592000 seconds) x $0.0000125 (GB/sec) = $32
1 create request x 1 CPU Core x 1 month (2592000 seconds) x $0.0000125 (GB/sec) = $32
Total ~ $64 / month.
I think you might be better off running an Ubuntu VM with Docker for your services and then add Azure Databases for MySQL for persistence. That is how I deploy inside azure.
[1] - https://scrapy.org
I'm pleasently surprised that bitbucket-pipelines has actually worked this well. So well that we have turned off our Jenkins server.
Nice work, atlassian!
And here: https://news.ycombinator.com/item?id=15834656
I think most here appreciate the hustle, but hammering HN with posts is not a path the community appreciates.
- MongoDB
- Cassandra
- Graph API
- Azure tables
- DocumentDB
I've used the MongoDB version, and it works ok for the basic CRUD stuff. I cant comment on aggregations, etc.Not sure from a quick peek if DynamoDB does the same...
1. Automation I automate provision environments, deployments, tests, and the command line. Pretty much whatever I can in a reasonable amount of time.
2. Templating I have a few project templates that already have the above automations scoped out. My ci/cd script, a makefile with common tasks, dockerfile skeleton, sensible playbooks. This lives in a skeleton git repo and cookiecutter.
3. Asking for help I'm active on stackoverflow ,various slack communities and mailing lists. This is critical in moving my work along at a healthy clip. There is a lot to be said for figuring it out on your own, but I'm more concerned with delivering value than being academic or pedantic about my implementation.
These are the skills and behaviors I try to hire for and the ones I try to have for myself.
Http://www.3cosystem.com
2. Endpoint for collecting anonymous usage stats in our apps.
One thing I'm not so clear with , however, is linux support for sql server clients. More specifically Django?
begging implies some kind of charity. Patreon is enabling one exchange of value for another. Very different IMO.
https://docs.microsoft.com/en-us/azure/cosmos-db/mongodb-int...
I'm not shilling just a happy azure user.
My only peeve is the confusing admin tools -- it is still Exchange on the backend, so there are a ton of features and settings that are simply in the way.
So why not just buy a carbon offset, take the flight, and make $10k?
If you host privately then bitbucket offers their CI called pipeline. [1]
Gitlab has their own CI. [2]
Then there is always travis-ci. [3]
Jenkins [4] is great, but I thought it was a little much for my pet projects.
In the end I decided to make one of my side projects a mini-CI/CD, appropriately called minici [5]. Since then I have rolled most of the side projects over to this.
All of these play well with docker (to a degree). Mini-ci (my baby) was built with docker in mind.
Things to watch out for: Each of the CI systems have a flavor of runner file or DSL to run in their CI. This is sometime a YAML file or in Jenkins case a groovy script. In my mini-ci project I opted for a standard Makefile with a specific target name to kick things off.
None of them have a steep learning curve, but I find that the complexity creeps in when you want a full SDLC pipeline with multiple stages, reporting, and alerting. Lots of moving parts.
I'm glad that I put time into learning modern CI/CD systems. It has made me more comfortable to put down a side projects for months at a time and only ship tiny changes without worry of remembering how to do deployments or run tests.
[1] - https://bitbucket.org/product/features/pipelines
[2] - https://about.gitlab.com/features/gitlab-ci-cd/
[3] - https://travis-ci.org
[4] - https://jenkins.io
You know, don't want to think you actually think that. Perhaps you meant, "fight the negative outcomes sometimes found in capitalist societies."
Best to assume when, not if one of your less than tech savvy users are compromised and begin sending malicious traffic from their machines.
(I'm joking -- right up until the point where I am not)
I'm not even sure how one would verify that a subpoena is valid.
I suppose the same goes for verifying badge numbers for police, fire marshalls, city inspectors, etc.