New/to cdf #513

stephTchembeu · 2025-10-28T09:40:47Z

No description provided.

UnravelSports · 2025-10-28T10:21:28Z

kloppy/infra/serializers/tracking/cdf/serializer.py

+                dataset.metadata.date + frame.timestamp
+            )
+            # Period
+            frame_data["period"] = periods.get(frame.period.id, "unknownn")


Change "unknownn" to "MISSING_MANDATORY_PERIOD_ID"

UnravelSports · 2025-10-28T10:23:16Z

kloppy/infra/serializers/tracking/cdf/serializer.py

+            Orientation,
+            BallState,
+        )
+


We should add a check to warn the user if they are progressing with only_alive=True in their kloppy dataset, because CDF expects all frames.

if all([True for x in tracking_dataset if x.ball_state == BallState.ALIVE]): warnings.warn( "All frames in 'tracking_dataset' are 'ALIVE', the Commond Data Format expects 'DEAD' frames as well. Set `only_alive=False` in your kloppy `.load_tracking()` call to include 'DEAD' frames.", UserWarning, )

UnravelSports · 2025-10-28T10:24:15Z

kloppy/infra/serializers/tracking/cdf/serializer.py

+
+            # Teams and players
+            home_players = []
+            for player, coordinates in frame.players_coordinates.items():


This duplicated code (for home and away players) to loop over players needs to be a function.

UnravelSports · 2025-10-28T10:24:50Z

kloppy/infra/serializers/tracking/cdf/serializer.py

+                            }
+                        )
+                    except KeyError:
+                        continue


What KeyError are we handling here? Should be handled without exception

UnravelSports · 2025-10-28T10:26:05Z

kloppy/infra/serializers/tracking/cdf/serializer.py

+
+            # teams within the tracking data.
+
+            home_players_id = []


What is this loop for?

UnravelSports · 2025-10-28T10:36:46Z

kloppy/infra/serializers/tracking/cdf/serializer.py

+                    "formation": (
+                        home_team.formations.at_start()
+                        if home_team.formations.items
+                        else self.get_starting_formation(


This is a small mistake in the common-data-format-validator, only "id" and "players" are mandatory here. So, we can remove "jersey_color" and "formation" as keys on the frame by frame level. If "home_team.name" is not None, we can add it too, but it's also not required.

UnravelSports · 2025-10-28T10:36:55Z

kloppy/infra/serializers/tracking/cdf/serializer.py

+                        away_team.formations.at_start()
+                        if away_team.formations.items
+                        else self.get_starting_formation(
+                            [


UnravelSports · 2025-10-28T10:37:37Z

kloppy/infra/serializers/tracking/cdf/serializer.py

+            starters_ids.append(player.player_id)
+
+        for player in home_team.players:
+            try:


Why are we catching KeyErrors here?

UnravelSports · 2025-10-28T10:38:03Z

kloppy/infra/serializers/tracking/cdf/serializer.py

+
+        meta_away_players = []
+        for player in away_team.players:
+            try:


same, again, these two operations for home and away are the same, we can make a function out of this

UnravelSports · 2025-10-28T10:39:58Z

kloppy/infra/serializers/tracking/cdf/serializer.py

+            # Add to tracking list
+            outputs.tracking_data.append(frame_file)
+
+        ###################### build now the metadata.


Create two separate functions in the serializer.py, one for generating meta data and one for tracking data to clean it up.

UnravelSports · 2025-10-28T12:36:02Z

@koenvo how do we want to make this functionality ultimately available to the end user? It should be captured in some type of common_data_format.store(dataset, file_path) type operation, right?

koenvo · 2025-10-28T13:13:21Z

@koenvo how do we want to make this functionality ultimately available to the end user? It should be captured in some type of common_data_format.store(dataset, file_path) type operation, right?

Yes, or we can start with a helper like:

dataset.to_cdf(file_path)

...


def to_cdf(self, file_path):
    # load and save?
    from common_data_format import save
    save(self, file_path)

UnravelSports · 2025-10-28T15:01:08Z

@koenvo how do we want to make this functionality ultimately available to the end user? It should be captured in some type of common_data_format.store(dataset, file_path) type operation, right?

Yes, or we can start with a helper like:
dataset.to_cdf(file_path)

...


def to_cdf(self, file_path):
    # load and save?
    from common_data_format import save
    save(self, file_path)

Oh, yeah I thought you were against doing the to_cdf option, I definitely prefer this as well.

koenvo · 2025-10-28T15:21:37Z

@koenvo how do we want to make this functionality ultimately available to the end user? It should be captured in some type of common_data_format.store(dataset, file_path) type operation, right?

Yes, or we can start with a helper like:
dataset.to_cdf(file_path)

...


def to_cdf(self, file_path):
    # load and save?
    from common_data_format import save
    save(self, file_path)
Oh, yeah I thought you were against doing the to_cdf option, I definitely prefer this as well.

I believe the initial idea was to put the actual implementation into the to_cdf method, and that isn't the best idea.

This adds comprehensive write support to the open_as_file() function with efficient memory management and streaming capabilities. Key features: - BufferedStream: SpooledTemporaryFile wrapper with chunked I/O (5MB memory threshold) - Write modes: 'wb' (write), 'ab' (append) - binary only - Adapter pattern: write_from_stream() method (opt-in for adapters) - Compression support: .gz, .bz2, .xz files handled automatically - Local files and S3 URIs supported via FSSpecAdapter - Protocols for type safety: SupportsRead, SupportsWrite Implementation details: - read_from()/write_to() methods use shutil.copyfileobj for chunked copying - Context manager pattern buffers writes and flushes on exit - No breaking changes to existing read functionality

Cleaned up CDF Serializer

stephTchembeu added 2 commits October 28, 2025 09:42

squash feta/to_cdf

e252c91

squash

1e2d6e6

UnravelSports reviewed Oct 28, 2025

View reviewed changes

UnravelSports [JB] and others added 4 commits October 30, 2025 14:44

cleaned up CDF Serializer

8eaafbb

WIP: add write support

fbf20c6

Follow output pattern for SportsCode

3e1073a

UnravelSports added this to the 3.19.0 milestone Nov 18, 2025

UnravelSports [JB] and others added 15 commits December 11, 2025 10:36

merge pr-515

e249156

working writer

f419105

cdf improve write

7993ec8

io

9e00f8e

improved (now complete) skillcorner position mapping

6b904b2

remove setup.py

87883a2

add import error

c731a76

improved tests, 2 providers

3100eb5

skillcorner additional test files

b72f03e

improved meta data

c4055e7

remove error, add warning

5ffa0d0

fix test

766e2f0

Merge pull request #5 from UnravelSports/pr-513

769ab73

Cleaned up CDF Serializer

Merge branch 'master' into new/to_cdf

9ba3f97

failing tests

75da5d6

UnravelSports mentioned this pull request Dec 17, 2025

[CDF] to_cdf #519

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New/to cdf #513

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New/to cdf #513

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stephTchembeu commented Oct 28, 2025

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UnravelSports commented Oct 28, 2025

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koenvo commented Oct 28, 2025

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UnravelSports commented Oct 28, 2025

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koenvo commented Oct 28, 2025

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