Published:
JB2008 is an emperical atmospheric neutral density model (long name Jacchia-Bowman 2008). It is the most recent itteration of the Jacchia-Bowman family at atmospheric models and incorporates both Solar and Geomagnetic activity into the modelling of atmospheric neutral denisty, temperature, and exospheric temperature.
Published:
dev-hub started as a way to keep my code in shape: a task board of small upkeep jobs, and features for bigger pieces of work. But most of my repos exist because of research, and the reason for any piece of code exists is usually because it’s linked to a research project, not on a board.
Published:
In my first dev-hub post, every piece of work was a task: one self-contained change on its own branch, with its own pull request that I merge as soon as it’s done. That covers most upkeep. That’s generally my workflow, but not everyone’s, and some work shouldn’t reach main one piece at a time: a new module isn’t always useful until it’s complete and some works needs validating before it replaces the old path.
Published:
In my last post I described dev-hub, a private GitHub repo that acts as mission control for Claude across my repos. Most of the time I run dev-hub tasks from Claude Code, either on my machine or on the web, where Claude can push branches and open pull requests itself.
Published:
I have a handful of research and side-project repos that all need the same kind of upkeep: tests that were never written, dated packaging, automated checks (continuous integration, or CI) that don’t exist, outdated READMEs. None of it is hard, but it never makes it to the top of the list; a lot of development stops once things work, as in plenty of research codebases.
Published:
Having problems accessing Anaconda from VS Code (Python: Select Interpreter)?
Published:
Often when working in science/research we are rapidly developing and modifying code (and maybe not following the very best practices for coding). In these instances we may not be writing, developing, or installing Python modules which can be accessed by the Python interpreter. Rather we may have a directory with set of scripts, functions, or classes. In Python in order to access these without installing a module we need to add the file path of our directory to the Python path. This can be easily acomplished using the sys module.
Published:
Environments in Anaconda and Python allow you to create a named and isolated copy of Python. Within these environments you can work with specefic versions of Python and packages without affecting your base installation. These enviroments make it easy to:
Published:
Experiencing weird scaling issues with Spyder?
Published:
Have you found your Anaconda enviroments stalling when trying to install new packages via conda?
Published:
dev-hub started as a way to keep my code in shape: a task board of small upkeep jobs, and features for bigger pieces of work. But most of my repos exist because of research, and the reason for any piece of code exists is usually because it’s linked to a research project, not on a board.
Published:
In my first dev-hub post, every piece of work was a task: one self-contained change on its own branch, with its own pull request that I merge as soon as it’s done. That covers most upkeep. That’s generally my workflow, but not everyone’s, and some work shouldn’t reach main one piece at a time: a new module isn’t always useful until it’s complete and some works needs validating before it replaces the old path.
Published:
In my last post I described dev-hub, a private GitHub repo that acts as mission control for Claude across my repos. Most of the time I run dev-hub tasks from Claude Code, either on my machine or on the web, where Claude can push branches and open pull requests itself.
Published:
I have a handful of research and side-project repos that all need the same kind of upkeep: tests that were never written, dated packaging, automated checks (continuous integration, or CI) that don’t exist, outdated READMEs. None of it is hard, but it never makes it to the top of the list; a lot of development stops once things work, as in plenty of research codebases.
Published:
In my first dev-hub post, every piece of work was a task: one self-contained change on its own branch, with its own pull request that I merge as soon as it’s done. That covers most upkeep. That’s generally my workflow, but not everyone’s, and some work shouldn’t reach main one piece at a time: a new module isn’t always useful until it’s complete and some works needs validating before it replaces the old path.
Published:
I have a handful of research and side-project repos that all need the same kind of upkeep: tests that were never written, dated packaging, automated checks (continuous integration, or CI) that don’t exist, outdated READMEs. None of it is hard, but it never makes it to the top of the list; a lot of development stops once things work, as in plenty of research codebases.
Published:
Experiencing weird scaling issues with Spyder?
Published:
Ever been actively editing a module while also using it? IPython (and JUPYTER) have some automagic to help with this.
Published:
Have you found your Anaconda enviroments stalling when trying to install new packages via conda?
Published:
In my first dev-hub post, every piece of work was a task: one self-contained change on its own branch, with its own pull request that I merge as soon as it’s done. That covers most upkeep. That’s generally my workflow, but not everyone’s, and some work shouldn’t reach main one piece at a time: a new module isn’t always useful until it’s complete and some works needs validating before it replaces the old path.
Published:
In my last post I described dev-hub, a private GitHub repo that acts as mission control for Claude across my repos. Most of the time I run dev-hub tasks from Claude Code, either on my machine or on the web, where Claude can push branches and open pull requests itself.
Published:
I have a handful of research and side-project repos that all need the same kind of upkeep: tests that were never written, dated packaging, automated checks (continuous integration, or CI) that don’t exist, outdated READMEs. None of it is hard, but it never makes it to the top of the list; a lot of development stops once things work, as in plenty of research codebases.
Published:
Have you found your Anaconda enviroments stalling when trying to install new packages via conda?
Published:
Persisting ML/AI models (or model serialization) allows users to save models that they’ve trained so that they can be reloaded and reused. Model persistence is important as it can save time and allows models to be shared with other users without the need to retrain the model (which can be computationally expensive and time consuming) or share the training data set (which can be large).
Published:
Many of Pandas read functions have the ability to read files from the internet. This can be helpful you’re writing tutorials or examples and want them to work even if users don’t have the data. Or if you want to quickly look at data without downloading it.
Published:
Many of Pandas read functions have the ability to read files from the internet. This can be helpful you’re writing tutorials or examples and want them to work even if users don’t have the data. Or if you want to quickly look at data without downloading it.
Published:
JB2008 is an emperical atmospheric neutral density model (long name Jacchia-Bowman 2008). It is the most recent itteration of the Jacchia-Bowman family at atmospheric models and incorporates both Solar and Geomagnetic activity into the modelling of atmospheric neutral denisty, temperature, and exospheric temperature.
Published:
Often when working in science/research we are rapidly developing and modifying code (and maybe not following the very best practices for coding). In these instances we may not be writing, developing, or installing Python modules which can be accessed by the Python interpreter. Rather we may have a directory with set of scripts, functions, or classes. In Python in order to access these without installing a module we need to add the file path of our directory to the Python path. This can be easily acomplished using the sys module.
Published:
JB2008 is an emperical atmospheric neutral density model (long name Jacchia-Bowman 2008). It is the most recent itteration of the Jacchia-Bowman family at atmospheric models and incorporates both Solar and Geomagnetic activity into the modelling of atmospheric neutral denisty, temperature, and exospheric temperature.
Published:
Persisting ML/AI models (or model serialization) allows users to save models that they’ve trained so that they can be reloaded and reused. Model persistence is important as it can save time and allows models to be shared with other users without the need to retrain the model (which can be computationally expensive and time consuming) or share the training data set (which can be large).
Published:
Many of Pandas read functions have the ability to read files from the internet. This can be helpful you’re writing tutorials or examples and want them to work even if users don’t have the data. Or if you want to quickly look at data without downloading it.
Published:
Having problems accessing Anaconda from VS Code (Python: Select Interpreter)?
Published:
Often when working in science/research we are rapidly developing and modifying code (and maybe not following the very best practices for coding). In these instances we may not be writing, developing, or installing Python modules which can be accessed by the Python interpreter. Rather we may have a directory with set of scripts, functions, or classes. In Python in order to access these without installing a module we need to add the file path of our directory to the Python path. This can be easily acomplished using the sys module.
Published:
Environments in Anaconda and Python allow you to create a named and isolated copy of Python. Within these environments you can work with specefic versions of Python and packages without affecting your base installation. These enviroments make it easy to:
Published:
Experiencing weird scaling issues with Spyder?
Published:
Ever been actively editing a module while also using it? IPython (and JUPYTER) have some automagic to help with this.
Published:
Have you found your Anaconda enviroments stalling when trying to install new packages via conda?
Published:
Many of Pandas read functions have the ability to read files from the internet. This can be helpful you’re writing tutorials or examples and want them to work even if users don’t have the data. Or if you want to quickly look at data without downloading it.
Published:
dev-hub started as a way to keep my code in shape: a task board of small upkeep jobs, and features for bigger pieces of work. But most of my repos exist because of research, and the reason for any piece of code exists is usually because it’s linked to a research project, not on a board.
Published:
Have you found your Anaconda enviroments stalling when trying to install new packages via conda?
Published:
Persisting ML/AI models (or model serialization) allows users to save models that they’ve trained so that they can be reloaded and reused. Model persistence is important as it can save time and allows models to be shared with other users without the need to retrain the model (which can be computationally expensive and time consuming) or share the training data set (which can be large).
Published:
Experiencing weird scaling issues with Spyder?
Published:
JB2008 is an emperical atmospheric neutral density model (long name Jacchia-Bowman 2008). It is the most recent itteration of the Jacchia-Bowman family at atmospheric models and incorporates both Solar and Geomagnetic activity into the modelling of atmospheric neutral denisty, temperature, and exospheric temperature.
Published:
JB2008 is an emperical atmospheric neutral density model (long name Jacchia-Bowman 2008). It is the most recent itteration of the Jacchia-Bowman family at atmospheric models and incorporates both Solar and Geomagnetic activity into the modelling of atmospheric neutral denisty, temperature, and exospheric temperature.
Published:
Having problems accessing Anaconda from VS Code (Python: Select Interpreter)?
Published:
Having problems accessing Anaconda from VS Code (Python: Select Interpreter)?
Published:
dev-hub started as a way to keep my code in shape: a task board of small upkeep jobs, and features for bigger pieces of work. But most of my repos exist because of research, and the reason for any piece of code exists is usually because it’s linked to a research project, not on a board.
Published:
In my first dev-hub post, every piece of work was a task: one self-contained change on its own branch, with its own pull request that I merge as soon as it’s done. That covers most upkeep. That’s generally my workflow, but not everyone’s, and some work shouldn’t reach main one piece at a time: a new module isn’t always useful until it’s complete and some works needs validating before it replaces the old path.
Published:
In my last post I described dev-hub, a private GitHub repo that acts as mission control for Claude across my repos. Most of the time I run dev-hub tasks from Claude Code, either on my machine or on the web, where Claude can push branches and open pull requests itself.
Published:
I have a handful of research and side-project repos that all need the same kind of upkeep: tests that were never written, dated packaging, automated checks (continuous integration, or CI) that don’t exist, outdated READMEs. None of it is hard, but it never makes it to the top of the list; a lot of development stops once things work, as in plenty of research codebases.