SQLite schema, Python classes and data management tools for working with time series from engineering test beds
Project description
Time Series Storage Tools
This software can be used to store time series from manufacturing test beds. The design was derived with data analysis in mind, enabling FAIR principles and reproducibility.
The conceptualization is published in [link will follow shortly]. If you use this software in any of your works please cite [DOI will follow shortly].
Setup storagetools
To use storagetools in your projects, you need the following:
storagetoolsinstalled- a
config.ini(works without but is not useful, see Getting Started)
A minimal config.ini may look like:
[environment]
analysis_name = my_first_analysis
[property_columns]
# additional case-specific properties (metadata information) as dict of lists.
# Use SQLite datatype as key for the dict (e.g., "TEXT", "FLOAT", etc.)
experiment = {"INT": ["run", "material"], "FLOAT": ["feedrate"]}
sensor = {"TEXT": ["manufacturer", "model", "identifier", "description"]}
channel = {"TEXT": ["measurand", "unit"]}
A more complete config.ini may look like:
[environment]
analysis_name = ucb_mill
available_cores = 12
# upper size limit for the key-value store, for most cases just leave as is
max_kvsize = 1099511627776
[storagetools.locations]
# name of the working directory
workdir_root = work
# name of the data directory within the work directory
storage_dir = data
# name of the plots directory within the work directory
plot_dir = plots
# name of the SQLite database file
database_filename = database.db
[property_columns]
# additional case-specific properties (metadata information) as dict of lists.
# Use SQLite datatype as key for the dict (e.g., "TEXT", "FLOAT", etc.)
experiment = {"INT": ["run", "material"], "FLOAT": ["feedrate"]}
sensor = {"TEXT": ["manufacturer", "model", "identifier", "description"]}
channel = {"TEXT": ["measurand", "unit"]}
If you want to modify logging, you can add:
[loggers]
keys=root
[handlers]
keys=screen, file
[formatters]
keys=default
[logger_root]
level=DEBUG
handlers=screen,file
[handler_screen]
class=StreamHandler
level=INFO
formatter=default
args=(sys.stdout,)
[handler_file]
class=FileHandler
level=DEBUG
formatter=default
args=('debug.log', 'a')
[formatter_default]
format=%(asctime)s %(levelname)s %(filename)s:%(lineno)d (%(funcName)s): %(message)s
Getting Started
For a demonstration of how to use storagetools refer to the jupyter-notebooks in doc/tutorials.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file ts_storagetools-0.2.2.tar.gz.
File metadata
- Download URL: ts_storagetools-0.2.2.tar.gz
- Upload date:
- Size: 16.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
4ae7f8e00da9b80d4e74141c6d7bb864d2b4cc45b8e35ba2967a5d1a06dc90cb
|
|
| MD5 |
6f9dc658cf372816709838a989499282
|
|
| BLAKE2b-256 |
33525d69347eca6c2ad90f3290299903d4975eeb1cf10e717403ea4e7958ed6f
|
File details
Details for the file ts_storagetools-0.2.2-py3-none-any.whl.
File metadata
- Download URL: ts_storagetools-0.2.2-py3-none-any.whl
- Upload date:
- Size: 18.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
52ee66d01aa20b8e19b5bcf88c6f63fb9d6d636e0c8e2cdc3ecfb2b412737c6e
|
|
| MD5 |
4b4906773a63965d4378adcc9ff7087a
|
|
| BLAKE2b-256 |
09426a8cca80636e08e50753d60e315f5771ce1721aa002bcafe521f15148a77
|