Enthought Canopy Geoscience (or Canopy Geo) variant of the product was a data analysis, exploration and visualization package optimized for geologists & geophysicists, and researchers in petroleum science. The product is discontinued.
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FogBugz
Score7 out of 10
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A software project management system used to plan, track and release great software with this lightweight and customizable system that integrates into any project management workflow. FogBugz is designed for software development teams and includes all the project management tools developers need straight out of the box. Users can: Track projects from start to finish - With tasks and subtasks for each case with required details and track them to ensure…
Enthought Canopy is best suites for scripting data analytical concepts. It has a wide range of data analytical libraries and also is good for data visualization. I would not recommend using Enthought Canopy only as an IDE, there may be better options available. If you're looking for a good data simulation & visualization package, Canopy it is.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
FogBugz has been a very useful tool to our organization, and much preferred over other options we reviewed, mainly JIRA. There are still some improvements needed, but with the fairly recent acquisition by DevFactory, we have a great deal of hope for what is in store given DevFactory's focus and transparency. It seems like both DevFactory and FogBugz customers are eager for substantial improvements on the front-end, but there is/was a great deal of backend housecleaning that definitely needed to take place first.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Providing scientific libraries, both open source and Enthought's own libraries which are excellent.
Training. They provide several courses in python for general use and for data analysis.
Debugging tools. Several IDEs provides tools for debugging, but I think they are insufficient or too general. Canopy has a special debugging tool, specially design for python.
Tasks, Subtasks, and notes. All three of these areas were critical for our team. Tasks in Fogbugz were a bit easier to see than in more bug based software like Trello or JIRA
The entire screen is used to view a task or case. Clicking on a task or case will open up and take up the entire screen, aside from the sidebar nav columns. I like to see details and I think Fogbugz does this very well, using up as much digital real estate as possible.
Flowcharting in Fogbugz with Creately is nice - instead of getting an exterior flowchart software like Lucidchart, Creately works right in Fogbugz.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
The simplicity of a single admin type user is not great because anyone who can create a job or client in the system, can also add and delete users. Content and User administrative rights should be separated.
There are ways to change the terminology/lexicon within the tool, but we are not able to get it to work even after reaching out to tech support. So we are forced to use the system terminology that doesn't match up to our company making training a bit difficult.
There is a subscribe function that you can opt into, there should be a way to add subscribers as you create a new task.
Before Canopy with its python we were working with Matlab. We decided for Canopy against Matlab for two reasons: First, we believe that python together with NumPy or SciPy can achieve the objectives with less code and therefore less training, and second the prizes are much lower than matlab which is most robust, expensive and less intuitive. It's clear we are making the comparison with python and it has nothing to with canopy. But with Canopy you feel you have all those tools close together without the problem of configuration, besides a lot of personalized libraries that complements a typical python environment.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Saves time by quickly allowing Developers to make the necessary notes without getting bogged down in bloated UIs
Has allowed us to look back easily and see the exact code changes made for the exact Case to aid in decisions for current changes, increasing the certainty of the decided path, without regression
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
