[
https://issues.apache.org/jira/browse/PIO-192?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Takako Shimamoto updated PIO-192:
---------------------------------
Description:
h3. Summary
Enhance the pypio, which is the Python API for PIO.
h3. Goals
The limitations of the current Python support always force developers to have
access to sbt. This enhancement will get rid of the build phase.
h3. Description
A Python engine template requires 3 files:
* Python code to specify for the --main-py-file option
* template.json
{code:json}
{"pio": {"version": { "min": "0.14.0-SNAPSHOT" }}}
{code}
* engine.json
{code:json}
{
"id": "default",
"description": "Default settings",
"engineFactory": "org.apache.predictionio.e2.engine.PythonEngine",
"algorithms": [
{
"name": "default",
"params": {
"name": "BHPApp"
}
}
],
"serving": {
"params": {
"columns": ["prediction"]
}
}
}
{code}
h4. pypio module
Developers can use the pypio module with jupyter notebook and Python code.
First, import the necessary modules.
{code:python}
from pypio import pypio
{code}
Once the module in imported, the first step is to initialize the pypio module.
{code:python}
pypio.init()
{code}
Next, find data from the event store.
{code:python}
event_df = pypio.find('BHPApp')
{code}
And then, save the model.
{code:python}
# model is a PipelineModel, which is produced after a Pipeline’s fit() method
runs
model = ...
pypio.save(model)
{code}
was:
h3. Summary
Enhance the pypio, which is the Python API for PIO.
h3. Goals
The limitations of the current Python support always force developers to have
access to sbt. This enhancement will get rid of the build phase.
h3. Description
A Python engine template requires 3 files:
* Python code to specify for the --main-py-file option
* template.json
{code:json}
{"pio": {"version": { "min": "0.14.0-SNAPSHOT" }}}
{code}
* engine.json
{code:json}
{
"id": "default",
"description": "Default settings",
"engineFactory": "org.apache.predictionio.e2.engine.PythonEngine",
"algorithms": [
{
"name": "default",
"params": {
"name": "BHPApp"
}
}
]
}
{code}
h4. pypio module
Developers can use the pypio module with jupyter notebook and Python code.
First, import the necessary modules.
{code:python}
from pypio import pypio
{code}
Once the module in imported, the first step is to initialize the pypio module.
{code:python}
pypio.init()
{code}
Next, find data from the event store.
{code:python}
event_df = pypio.find('BHPApp')
{code}
And then, save the model.
{code:python}
# model is a PipelineModel, which is produced after a Pipeline’s fit() method
runs
model = ...
pypio.save(model)
{code}
> Enhance PySpark support
> -----------------------
>
> Key: PIO-192
> URL: https://issues.apache.org/jira/browse/PIO-192
> Project: PredictionIO
> Issue Type: Improvement
> Components: Core
> Affects Versions: 0.13.0
> Reporter: Takako Shimamoto
> Assignee: Takako Shimamoto
> Priority: Major
>
> h3. Summary
> Enhance the pypio, which is the Python API for PIO.
> h3. Goals
> The limitations of the current Python support always force developers to have
> access to sbt. This enhancement will get rid of the build phase.
> h3. Description
> A Python engine template requires 3 files:
> * Python code to specify for the --main-py-file option
> * template.json
> {code:json}
> {"pio": {"version": { "min": "0.14.0-SNAPSHOT" }}}
> {code}
> * engine.json
> {code:json}
> {
> "id": "default",
> "description": "Default settings",
> "engineFactory": "org.apache.predictionio.e2.engine.PythonEngine",
> "algorithms": [
> {
> "name": "default",
> "params": {
> "name": "BHPApp"
> }
> }
> ],
> "serving": {
> "params": {
> "columns": ["prediction"]
> }
> }
> }
> {code}
> h4. pypio module
> Developers can use the pypio module with jupyter notebook and Python code.
> First, import the necessary modules.
> {code:python}
> from pypio import pypio
> {code}
> Once the module in imported, the first step is to initialize the pypio module.
> {code:python}
> pypio.init()
> {code}
> Next, find data from the event store.
> {code:python}
> event_df = pypio.find('BHPApp')
> {code}
> And then, save the model.
> {code:python}
> # model is a PipelineModel, which is produced after a Pipeline’s fit() method
> runs
> model = ...
> pypio.save(model)
> {code}
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