I have attempted some improvements at the 'Downloading Leo' section.
Nice improvement. It answers the 'why git' question up front, in the introduction.
Hi,
I like how documentation is getting more compact and direct. I wonder if installation instructions could go from the most newbie friendly to the not so newbie ones (maybe after releasing 5.5). So installation should start from the most common used installation method of the intended platform and then go to more powerful ones. For example, running a binary self-contained executable on Windows, a dmg on Mac or apt-rpm on Linux. Of course that creates the problem of packaging, that we have discussed previously Leo's manpower (which is mostly Edward) could be not enough to take the laborious and tedious packaging work.
In the Grafoscopio case, I rely on the Pharo platform to manage
packaging and provide prerequisites, which makes installation and
updating easy, but I was wondering how Python related projects do
this nowadays. One path is Conda and, particularly, Miniconda
which manages depedencies and is already packaged for several
platforms [1], but seems that a full installation can be overkill
for Leo and its prerrequisites [2]. In the Jupyter case the map
they provide [3] gives the user and overview of what they want to
do, based on the answer the user gives to a question, and they use
the external installer method (in their case Anaconda) to the
final installation, making it pretty easy [4] ('cause the heavy
work is done by conda and not the user/developer). Conda can be
also used to upgrade the software, including updating/building
from git[5]
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I like how documentation is getting more compact and direct.
I wonder if installation instructions could go from the most newbie friendly to the not so newbie ones (maybe after releasing 5.5). So installation should start from the most common used installation method of the intended platform and then go to more powerful ones.
... I was wondering how Python related projects do this nowadays. One path is Conda and, particularly, Miniconda which manages dependencies and is already packaged for several platforms [1], but seems that a full installation can be overkill for Leo and its prerequisites[2].
In the Jupyter case the map they provide [3] gives the user and overview of what they want to do, based on the answer the user gives to a question, and they use the external installer method (in their case Anaconda) to the final installation, making it pretty easy [4] ('cause the heavy work is done by conda and not the user/developer). Conda can be also used to upgrade the software, including updating/building from git[5]
Hi,
On Mon, Mar 20, 2017 at 7:00 PM, Offray Vladimir Luna Cárdenas <off...@riseup.net> wrote:
I like how documentation is getting more compact and direct.
I agree. This is a big step forward, for everyone, but especially for first timers.I wonder if installation instructions could go from the most newbie friendly to the not so newbie ones (maybe after releasing 5.5). So installation should start from the most common used installation method of the intended platform and then go to more powerful ones.
Heh. The eternal tension. Perhaps you could have a conversation with Lewis Neal.
... I was wondering how Python related projects do this nowadays. One path is Conda and, particularly, Miniconda which manages dependencies and is already packaged for several platforms [1], but seems that a full installation can be overkill for Leo and its prerequisites[2].Overkill, maybe, but I think it is useful overkill. Installing the full Anaconda package (or packages, if you install for both Python 2 and 3) saves a lot of time in the long run. I'm not looking for anything better. Besides, these days even small machines typically have huge memories.
In the Jupyter case the map they provide [3] gives the user and overview of what they want to do, based on the answer the user gives to a question, and they use the external installer method (in their case Anaconda) to the final installation, making it pretty easy [4] ('cause the heavy work is done by conda and not the user/developer). Conda can be also used to upgrade the software, including updating/building from git[5]
I think this is just fine or Leo too.
Whoops! hit enter at the wrong time. I meant that I started my mail thinking in native installers, but as I progressed the (mini)conda method seemed better.
From the Conda.io https://conda.io/docs/install/quick.html site:NOTE: If you choose to install the full Anaconda package, it requires 3 GB of available disk space.Using Miniconda py3.6 64bit the Binary File is only 57.8 MB.
Edward - do you have any statistics on how Leo's user base installs Leo? Sure the numbers might be meaningless as most git downloads are updates, but the knowledge may help guide the direction of the install documents.