dapla-ipython-kernels
Python module for use within Jupyter notebooks. It contains kernel extensions for integrating with Apache Spark, Google Cloud Storage and custom dapla services.
Getting Started
Install the module from pip:
# pip
pip install dapla-ipython-kernels
Now the module is ready to use with a single import:
import dapla as dp
This module is targeted to python kernels in Jupyter, but it may work in any IPython environment. It also depends on a number of custom services, e.g. the custom auth service
To test, simply create any Pandas dataframe. This can be stored in Google Cloud Storage at a specific path:
import pandas as pd
import dapla as dp
data = {
'apples': [3, 2, 0, 1],
'oranges': [0, 3, 7, 2]
}
# Create pandas DataFrame
purchases = pd.DataFrame(data, index=['June', 'Robert', 'Lily', 'David'])
# Write pandas DataFrame to parquet
dp.write_pandas(purchases, '/testfolder/python/purchases', valuation='INTERNAL', state= 'INPUT')
Conversely, parquet files can be read from a path directly into a pandas DataFrame.
import dapla as dp
# Read path into pandas dataframe
purchases = dp.read_pandas('/testfolder/python/purchases')
Other functions
Since the python module integrates with Google Cloud Storage and custom dapla services, some other functions exist as well:
import dapla as dp
# List path by prefix
dp.show('/testfolder/python')
| Path | Timestamp |
|---|---|
| /testfolder/python/purchases | 1593120298095 |
| /testfolder/python/other | 1593157667793 |
import dapla as dp
# Show file details
dp.details('/testfolder/python/purchases')
| Size | Name |
|---|---|
| 2908 | 42331105444c9ca0ce049ef6de7160.parquet |
See also the example notebook written for Jupyter.
Deploy to SSB jupyter
Release version pypi
Make sure you have a clean master branch.
run make bump-version-patch - this will update version and commit to git.
run git push --tags origin master - important to have --tags to make it auto deploy to pypi
If everything was ok we should see a new release her: https://pypi.org/project/ssb-ipython-kernels/
Update jupyter image on staging
- Bump ssb-ipython-kernels in dapla-gcp-jupyter Dockerfile
- Example of previous update
- Example of previous update
- Check new tag from build on azure piplines
- update platform dev jupyter-kubespawner-config with tag
For now, we have to delete the running jupyer hub instance to make it use this new config
Metadata
Release files for ssb-ipython-kernels 0.3.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| ssb-ipython-kernels-0.3.3.tar.gz | 25.3 kB | Without provenance | Details for ssb-ipython-kernels-0.3.3.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| ssb_ipython_kernels-0.3.3-py3-none-any.whl | Python 3 | none | any | Details for ssb_ipython_kernels-0.3.3-py3-none-any.whl |
Total release size: 54.7 kB
Release files / ssb-ipython-kernels-0.3.3.tar.gz
| Download URL | ssb-ipython-kernels-0.3.3.tar.gz |
|---|---|
| Size | 25.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
5fde0db08be21e8082cd70eaeeb9a832db54e9ef77467f2874bb12ee5f97be25
|
|
BLAKE2b-256 checksum How to use checksums |
c1500dbd3944013356007b66c31ca1102cd26dbe060e7fd02b7699fa4bd1146d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.6.0 importlib_metadata/4.8.2 pkginfo/1.8.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.12
|
Release files / ssb_ipython_kernels-0.3.3-py3-none-any.whl
| Download URL | ssb_ipython_kernels-0.3.3-py3-none-any.whl |
|---|---|
| Size | 29.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
15e84d565a0eeaaddef09cd28f54fe4fac92f3aba791aecf41b2991aa1153c83
|
|
BLAKE2b-256 checksum How to use checksums |
13f7c67b79f7877844be3ec9b637cef1b2f64dbf1466c6fecbd12be9d76bab9b
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.6.0 importlib_metadata/4.8.2 pkginfo/1.8.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.12
|
Security for ssb-ipython-kernels 0.3.3
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.