QuantConnect / QuantConnect/Lean

Missing History Method Overloads

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depth feature
Dominant language
C#
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Avg merge
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Merged PRs (30d)
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Description

Expected Behavior
  • QCAlgorithm.History method has integer and TimeSpan overloads that include a DataNormalizationMode parameter. These methods will be used to request scaled raw data (DataNormalizationMode.ScaledRaw).
  • QCAlgorithm.History method has an overload that returns IEnumerable<Slice> for Python algorithms. These method allow us to request Slice data without the conversion to pandas.Dataframe.
Actual Behavior
  • To request DataNormalizationMode.ScaledRaw data, we need to use the DateTime/DateTime overload that requires the start time of the history request.
  • We cannot get Slice data in Python algorithms, since the available overloads convert the data to pandas Dataframe.
Potential Solution

N/A

Checklist
  • I have completely filled out this template
  • I have confirmed that this issue exists on the current master branch
  • I have confirmed that this is not a duplicate issue by searching issues
  • I have provided detailed steps to reproduce the issue

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start at the QCAlgorithm.History overloads and inspect how DataNormalizationMode and Python algorithm calls are exposed. Done means integer and TimeSpan overloads accept the requested normalization mode, and Python algorithms can request IEnumerable without conversion to a pandas DataFrame.

Written by the indexing model from the issue text.

Assessment

Tech stack
csharp, python
Domain
api
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
42/100

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