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A Python toolkit for managing, retrieving, and processing data.
You can install the toolkit with:
$ pip3 install pydtk
If you want to install the toolkit with extra feature (e.g. support for PointCloud and ROS), you can install it with extra dependencies as follows:
$ pip3 install pydtk[pointcloud,ros]
Some PyDTK models require additional packages.
Please refer the following table and install them manually with command pip install ...
.
PyDTK model | Required packages |
---|---|
rosbag.* | ros_numpy (https://github.com/eric-wieser/ros_numpy.git) |
pointcloud.PCDModel | pypcd (https://github.com/klintan/pypcd.git) |
By using Pydtk, you can load a variety of types of data with a unified interface as shown below.
from pydtk.db import DBHandler
# Initialize handler (This will read all the metadata from DB on initialization)
handler = DBHandler(
db_class='meta',
db_host='./examples/example_db',
base_dir_path='./test'
)
# Select by timestamp
handler.read(pql='start_timestamp > 1420000000 and end_timestamp < 1500000000')
print(handler.data)
# Select by record-id
handler.read(pql='record_id == regex("test.*")')
print(handler.data)
from pydtk.io import BaseFileReader, NoModelMatchedError
reader = BaseFileReader()
try:
for sample in handler:
print('loading content "{0}" from file "{1}"'.format(sample['contents'], sample['path']))
try:
timestamps, data, columns = reader.read(sample)
assert print(data)
except NoModelMatchedError as e:
print(str(e))
continue
except EOFError:
pass
For more information about this toolkit, please refer the document.
To improve this toolkit, firstly clone this repository and then run the following command to prepare the environment.
$ git clone git@github.com:dataware-tools/pydtk.git --recurse-submodules
$ poetry install
Make sure that poetry is installed before executing the command.
If you want to install the toolkit with extra feature (e.g. support for ROS),
please specify it with -E
option.
Example (installation with pointcloud
and ros
extras):
$ poetry install -E pointcloud -E ros
FAQs
A Python toolkit for managing, retrieving and processing data.
We found that pydtk demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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