From ee93437ee62c4b780908413d77062a2d762923a1 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Tom=20Kr=C3=BCger?= Date: Wed, 9 Dec 2020 19:16:24 +0100 Subject: [PATCH] worked on readme --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index d9f325c..8396aaa 100644 --- a/README.md +++ b/README.md @@ -6,7 +6,7 @@ The pyalma package provides a framework to plan, run, pause and continue file ba ## Example -Everything starts with grouping the files of interests (a) [batch(es)](./docs/batch.md). Lets say we have a batch file `example.batch`. This could look as follows. +Everything starts with grouping the files of interests to (a) [batch(es)](./docs/batch.md). Lets say we have a batch file `example.batch`. This could look as follows. ###### `example.batch` @@ -60,13 +60,13 @@ Now that we have specified everything, we can start executing our experiment. >>> dispatcher.start() ``` -The line `dispatcher.start()` starts the concurrent non blocking execution of our experiment. This means the dispatcher stays responsive and we can pause/stop the execution at every given time. +The line `dispatcher.start()` starts the concurrent non blocking execution of our experiment. This means the dispatcher stays responsive and we can pause/stop the execution at any given time. ``` >>> dispatcher.stop() ``` -During the execution the `dispatcher` continuously keeps track of which files he still needs to call `run(...)` on, how many iterations he has left and saves the current state of the execution in a file. Loading an experiment (`alma.experiment.load(...)`) the framework first looks for such a save file if one exists the execution pill pick up at the point we've called `dispatcher.stop()`. To pick up the experiment we can perform: +During the execution the `dispatcher` continuously keeps track of which files he still needs to call `run(...)` on and how many iterations he has left. He does so by saving the current state of the execution in a file. Loading an experiment (`alma.experiment.load(...)`) the framework first looks for such a save file and if one exists, the execution will pick up at the point we've called `dispatcher.stop()`. To pick up the experiment we can perform: ``` >>> dispatcher = alma.experiment.load("example.experiment")