Releases: mitdbg/palimpzest
Releases · mitdbg/palimpzest
Release list
0.5.4
update docs with new research papers (#115)
0.5.3: Create chat.rst (#96)
* Create chat.rst * Update pyproject.toml Hotfix for chat * Update conf.py Hotfix for chat.rst
0.5.2: Update datasources.py (#93)
* Update datasources.py Removing Hardcoded limit to pdf text. We kept it for a demo but now is undocumented behavior * bump version --------- Co-authored-by: Matthew Russo <mdrusso@mit.edu>
0.5.1: Add Static Redirect to Chat Demo (#90)
* adding static redirect to chat demo * bump version * make pandas version more flexible
0.5.0: Dev to main. (#88)
* update README
* 1. support add_columns in Dataset; 2. support run().to_df(); 3. add demo in df-newinterface.py (#78)
* Support add_columns in Dataset. Support demo in df-newinterface.py
Currently we have to do
records, _ = qr3.run()
outputDf = DataRecord.to_df(records)
I'll try to make qr3.run().to_df() work in another PR.
* ruff check --fix
* Support run().to_df()
Update run() to DataRecordCollection, so that it will be easier for use to support more features for run() output.
We support to_df() in this change.
I'll send out following commits to update other demos.
* run check --fix
* fix typo in DataRecordCollection
* Update records.py
* fix tiny bug in mab processor.
The code will run into issue if we don't return any stats for this function in
```
max_quality_record_set = self.pick_highest_quality_output(all_source_record_sets)
if (
not prev_logical_op_is_filter
or (
prev_logical_op_is_filter
and max_quality_record_set.record_op_stats[0].passed_operator
)
```
* update record.to_df interface
update to record.to_df(records: list[DataRecord], project_cols: list[str] | None = None) which is consistent with other function in this class.
* Update demo for the new execute() output format
* better way to get plan from output.run()
* fix getting plan from DataRecordCollection.
people used to get plan from execute() of streaming processor, which is not a good practice.
I update plan_str to plan_stats, and they need to get physical plan from processor.
Consider use better ways to provide executed physical plan to DataRecordCollection, possibly from stats.
* Update df-newinterface.py
* update code based on comments from Matt.
1. add cardinality param in add_columns
2. remove extra testdata files
3. add __iter__ in DataRecordCollection to help iter over streaming output.
* see if copilot just saved me 20 minutes
* fix package name
* use sed to get version from pyproject.toml
* bump project version; keep docs behind to test ci pipeline
* bumping docs version to match code version
* use new __iter__ method in demos where possible
* add type hint for output of __iter__; use __iter__ in unit tests
* Update download-testdata.sh (#89)
Added enron-tiny.csv
---------
Co-authored-by: Matthew Russo <mdrusso@mit.edu>
Co-authored-by: Gerardo Vitagliano <vitaglianog@gmail.com>
0.4.0: Docs (#77)
* update gitignore and add sphinx to pyproject * add initial empty docs * update README * add docs build to gitignore * Load image over http from s3 * adding workflow to publish docs * fixing yaml * remove workflow.yaml * fix webpage content; temp deploy on docs branch * install pz before building docs * fix publish_dir * test package push * test push package logic * test push package * test push package after oidc * update publishing workflow * fix bug * fix cname changing * add missing step name * fix job name * finally get damn links to not show up * starting point for documentation; tweaked README and quickstart * fixed metaclass causing type issues * try to extract package version * try to extract package version * try to extract package version again * try to extract package version again * bump version to help debug pipeline * bump and add * yolo * version bump * preparing version 0.4.0 --------- Co-authored-by: Matthew Russo <mdrusso@mit.edu>