这是indexloc提供的服务,不要输入任何密码
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77 changes: 77 additions & 0 deletions .github/ISSUE_TEMPLATE/bug_report.yaml
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name: Bug Report
description: Report incorrect behavior in the tmlt.analytics library
labels: [Bug, Needs Triage]

body:
- type: checkboxes
id: checks
attributes:
label: Basic checks
options:
- label: >
I can confirm that there isn't a seperate issue filed related to this bug.
required: true
- type: textarea
id: example
attributes:
label: Reproducible Example
description: >
Please add an example that reproduces the bug.

[This guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) has guidance
on how to create an example.
placeholder: >
from pyspark.sql import SparkSession
from tmlt.analytics import Session, PureDPBudget, AddOneRow

spark = SparkSession.builder.appName("example").getOrCreate()
df = spark.createDataFrame(
[(1, "Alice"), (2, "Bob")],
["id", "name"]
)

session = Session.Builder() \
.with_private_dataframe("example", df, AddOneRow()) \
.with_privacy_budget(PureDPBudget(1)) \
.build()
...
render: python
validations:
required: true
- type: textarea
id: problem
attributes:
label: Bug Description
description: >
Please describe the bug, specifically the undesirable behavior, shown by your example.
validations:
required: true
- type: textarea
id: expected-behavior
attributes:
label: Expected Behavior
description: >
Please describe what the exepected program outputs of your example code are.
validations:
required: true
- type: input
id: version-info
attributes:
label: Version Info
description: >
Please add what version of tmlt.analytics you have:
validations:
required: true
- type: textarea
id: platform
attributes:
label: Platform
description: >
[Optional] If you think this bug is an installation issue, please describe your system:


Important notes for tmlt.analytics:
- What versions of Java, Python, and Spark do you have installed?
- What processor architecture (ex: x86_64 or arm) are you installing on?
- What operating system and version are you installing on?
- What version of tmlt.core are you using?
64 changes: 64 additions & 0 deletions .github/ISSUE_TEMPLATE/feature_request.yaml
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name: Feature Request
description: Suggest an improvement for tmlt.analytics
labels: [Enhancement, Needs Triage]

body:
- type: checkboxes
id: checks
attributes:
label: Feature Category
description: Please mark what category of feature you're proposing.
options:
- label: >
Adding new functionality to tmlt.analytics
- label: >
Changing existing functionality in tmlt.analytics
- label: >
Removing existing functionality in tmlt.analytics
- type: textarea
id: description
attributes:
label: Use Case Description
description: >
Please describe what the use case for your proposed feature is. What type of problem does this feature solve?
placeholder: >
I have to generate tabular statistics with a sparse keyset. A sparse keyset results in lots of spurious cell outputs.
validations:
required: true
- type: textarea
id: feature
attributes:
label: Feature Request
description: >
Please describe the feature that you are proposing. Include any relevant code examples that describe the feature.
placeholder: >
# Enable KeySet Creation using ApproxDP.

from pyspark.sql import SparkSession
from tmlt.analytics import Session, ApproxDPBudget, AddOneRow, QueryBuilder

spark = SparkSession.builder.appName("example").getOrCreate()
df = spark.createDataFrame(
[(1, "Alice"), (2, "Bob")],
["id", "name"]
)

budget = ApproxDPBudget(1, 10e-8)

session = Session.Builder() \
.with_private_dataframe("example", df, AddOneRow()) \
.with_privacy_budget(budget) \
.build()

keyset_query = QueryBuilder("example").get_groups()
keyset = session.evaluate(keyset_query, budget)

...
validations:
required: true
- type: textarea
id: information
attributes:
label: Additional Information
description: >
Please add any relevant details, code, Github links, other issues, or academic papers.