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<4919840+vincent-octo@users.noreply.github.com> Date: Tue, 9 Jun 2026 15:19:19 +0300 Subject: [PATCH 02/15] setup clean base for Pietro --- src/kanta/config.py | 6 ++++++ src/kanta/engine/__init__.py | 0 src/kanta/engine/__main__.py | 5 +++++ src/kanta/engine/injection.py | 3 +++ 4 files changed, 14 insertions(+) create mode 100644 src/kanta/config.py create mode 100644 src/kanta/engine/__init__.py create mode 100644 src/kanta/engine/__main__.py create mode 100644 src/kanta/engine/injection.py diff --git a/src/kanta/config.py b/src/kanta/config.py new file mode 100644 index 0000000..ba6b75e --- /dev/null +++ b/src/kanta/config.py @@ -0,0 +1,6 @@ +# Shared config across the project. +EXAMPLE_VAR = [ + 1, + 2, + 3 +] diff --git a/src/kanta/engine/__init__.py b/src/kanta/engine/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/src/kanta/engine/__main__.py b/src/kanta/engine/__main__.py new file mode 100644 index 0000000..40ef581 --- /dev/null +++ b/src/kanta/engine/__main__.py @@ -0,0 +1,5 @@ +from kanta import config +from kanta.engine import injection + +if __name__ == '__main__': + injection.fake_run(config.EXAMPLE_VAR) diff --git a/src/kanta/engine/injection.py b/src/kanta/engine/injection.py new file mode 100644 index 0000000..83228ac --- /dev/null +++ b/src/kanta/engine/injection.py @@ -0,0 +1,3 @@ +def fake_run(param): + print("==> Injection stage") + print(f"from config: {param=}") From d0c1c53a2afca1bf0117ab7e8662dbeb8a9c2853 Mon Sep 17 00:00:00 2001 From: Vincent <4919840+vincent-octo@users.noreply.github.com> Date: Wed, 10 Jun 2026 11:24:02 +0300 Subject: [PATCH 03/15] set Pandas options --- src/kanta/engine/__main__.py | 59 +++++++++++++++++++++++++++++++++++- 1 file changed, 58 insertions(+), 1 deletion(-) diff --git a/src/kanta/engine/__main__.py b/src/kanta/engine/__main__.py index 40ef581..7d0f2e4 100644 --- a/src/kanta/engine/__main__.py +++ b/src/kanta/engine/__main__.py @@ -1,5 +1,62 @@ +import warnings + +import pandas as pd + from kanta import config from kanta.engine import injection -if __name__ == '__main__': + +def main(): injection.fake_run(config.EXAMPLE_VAR) + + # Efficient read + pd.read_parquet( + "path-to-file.parquet", + engine="pyarrow", + # Select only the given columns, this speeds up the read quite a lot for Parquet files. + # The resulting DataFrame contains only the selected columns. + columns=["COL_A", "COL_C"], + # Filtering of rows. + # Only basic filters are available (==, =, >, >=, <, <=, !=, in, not in). This speeds up + # the read as well. + # !! WARNING !! + # The behavior of the filtering changes based on the engine! Only when engine is "pyarrow" + # will the resulting rows be only the one matching the filter. Otherwise this will result + # in a superset of requested rows. + filters=[ + ('COL_A', '=', 'something') + ], + # Use nullable data-types backed by pyarrow. + # - Nullable: missing values stay as NA rather than forcing integer columns up to float or + # string columns into the object dtype. + # - pyarrow: better fit for Parquet files, and future-proofing since Pandas is moving into + # that direction. + dtype_backend="pyarrow", + ) + + +def configure_pandas(): + # Treat NaN (a real float value) and NA (a missing value) as distinct. + pd.options.future.distinguish_nan_and_na = True + + # Default to the pyarrow engine for all Parquet reads/writes, so we don't have to pass + # engine="pyarrow" on every call. + pd.options.io.parquet.engine = "pyarrow" + + # Turn chained assignment into a hard error. + # Chained assignment have weird behavior in that they would turn operations into no-op. + # For example this chained assignment *does not change any value* of df: + # `df[df["A"] > 0]["B"] = 1` + # Instead, use `.loc` or `.iloc` to get correct behavior: + # `df.loc[df["A"] > 0, "B"] = 1` + # We change Pandas default from jsut throw a warning (ChainedAssignmentError), to actually + # raising an error. + # Note that unfortunately we can't just set the option + # `mode.chained_assignment` to `"raise"` because it has no effect under + # Copy-on-Write, so we have to resort to promoting the warning to an error. + warnings.filterwarnings("error", category=pd.errors.ChainedAssignmentError) + + +if __name__ == "__main__": + configure_pandas() + main() From 8ddf06aca44301086445ff6e143277068f567e2e Mon Sep 17 00:00:00 2001 From: Vincent <4919840+vincent-octo@users.noreply.github.com> Date: Fri, 12 Jun 2026 14:43:40 +0200 Subject: [PATCH 04/15] implement base: input, column renaming, output --- src/kanta/engine/__main__.py | 35 +++++++++++++++++++++++++++++------ src/kanta/engine/injection.py | 3 --- src/kanta/engine/reader.py | 16 ++++++++++++++++ 3 files changed, 45 insertions(+), 9 deletions(-) delete mode 100644 src/kanta/engine/injection.py create mode 100644 src/kanta/engine/reader.py diff --git a/src/kanta/engine/__main__.py b/src/kanta/engine/__main__.py index 7d0f2e4..0b42185 100644 --- a/src/kanta/engine/__main__.py +++ b/src/kanta/engine/__main__.py @@ -1,13 +1,18 @@ import warnings +from argparse import ArgumentParser +from pathlib import Path + import pandas as pd -from kanta import config -from kanta.engine import injection +from kanta.engine import output, reader def main(): - injection.fake_run(config.EXAMPLE_VAR) + args = cli_init() + + for df_chunk in reader.chunk_iterator(args.intput_file): + (df_chunk.pipe(output.write_files, output_dir=args.output_dir)) # Efficient read pd.read_parquet( @@ -23,9 +28,7 @@ def main(): # The behavior of the filtering changes based on the engine! Only when engine is "pyarrow" # will the resulting rows be only the one matching the filter. Otherwise this will result # in a superset of requested rows. - filters=[ - ('COL_A', '=', 'something') - ], + filters=[("COL_A", "=", "something")], # Use nullable data-types backed by pyarrow. # - Nullable: missing values stay as NA rather than forcing integer columns up to float or # string columns into the object dtype. @@ -35,6 +38,26 @@ def main(): ) +def cli_init(): + parser = ArgumentParser( + description="Kanta Lab preprocessing pipeline: raw data ⇒ clean data." + ) + parser.add_argument( + "--input-file", + type=Path, + help="Path to the Kanta Lab data file coming from the intake stage (Parquet)", + required=True, + ) + parser.add_argument( + "--output-dir", + type=Path, + help="Directory to store the output data files.", + required=True + ) + + return parser.parse_args() + + def configure_pandas(): # Treat NaN (a real float value) and NA (a missing value) as distinct. pd.options.future.distinguish_nan_and_na = True diff --git a/src/kanta/engine/injection.py b/src/kanta/engine/injection.py deleted file mode 100644 index 83228ac..0000000 --- a/src/kanta/engine/injection.py +++ /dev/null @@ -1,3 +0,0 @@ -def fake_run(param): - print("==> Injection stage") - print(f"from config: {param=}") diff --git a/src/kanta/engine/reader.py b/src/kanta/engine/reader.py new file mode 100644 index 0000000..7ba2a0e --- /dev/null +++ b/src/kanta/engine/reader.py @@ -0,0 +1,16 @@ +from pathlib import Path + +import pandas as pd + +from kanta.config import engine_read_columns + + +def chunk_iterator(input_file: Path): + return ( + pd.read_parquet( + input_file, + engine="pyarrow", + columns=engine_read_columns, + dtype_backend="pyarrow" + ) + ) From 7e9c0ab8414de841ffd094d7845e79599cba7833 Mon Sep 17 00:00:00 2001 From: Vincent <4919840+vincent-octo@users.noreply.github.com> Date: Fri, 12 Jun 2026 14:56:29 +0200 Subject: [PATCH 05/15] implement Parquet chunk reader iterator --- src/kanta/config.py | 13 +++++++---- src/kanta/engine/__main__.py | 43 ++++++++++++++---------------------- src/kanta/engine/output.py | 0 src/kanta/engine/reader.py | 23 +++++++++++-------- 4 files changed, 39 insertions(+), 40 deletions(-) create mode 100644 src/kanta/engine/output.py diff --git a/src/kanta/config.py b/src/kanta/config.py index ba6b75e..bf40491 100644 --- a/src/kanta/config.py +++ b/src/kanta/config.py @@ -1,6 +1,11 @@ # Shared config across the project. -EXAMPLE_VAR = [ - 1, - 2, - 3 + +# ============================================================================= +# ENGINE +# ============================================================================= +ENGINE_READ_COLUMNS = [ + "!!!__TODO__!!!" ] + +# Number of rows per chunk when streaming the input Parquet file. +ENGINE_CHUNK_N_LINES = 1_000_000 diff --git a/src/kanta/engine/__main__.py b/src/kanta/engine/__main__.py index 0b42185..e8dd598 100644 --- a/src/kanta/engine/__main__.py +++ b/src/kanta/engine/__main__.py @@ -2,7 +2,6 @@ from argparse import ArgumentParser from pathlib import Path - import pandas as pd from kanta.engine import output, reader @@ -11,31 +10,21 @@ def main(): args = cli_init() - for df_chunk in reader.chunk_iterator(args.intput_file): - (df_chunk.pipe(output.write_files, output_dir=args.output_dir)) - - # Efficient read - pd.read_parquet( - "path-to-file.parquet", - engine="pyarrow", - # Select only the given columns, this speeds up the read quite a lot for Parquet files. - # The resulting DataFrame contains only the selected columns. - columns=["COL_A", "COL_C"], - # Filtering of rows. - # Only basic filters are available (==, =, >, >=, <, <=, !=, in, not in). This speeds up - # the read as well. - # !! WARNING !! - # The behavior of the filtering changes based on the engine! Only when engine is "pyarrow" - # will the resulting rows be only the one matching the filter. Otherwise this will result - # in a superset of requested rows. - filters=[("COL_A", "=", "something")], - # Use nullable data-types backed by pyarrow. - # - Nullable: missing values stay as NA rather than forcing integer columns up to float or - # string columns into the object dtype. - # - pyarrow: better fit for Parquet files, and future-proofing since Pandas is moving into - # that direction. - dtype_backend="pyarrow", - ) + for df_chunk in reader.chunk_iterator(args.input_file): + + def noop_filter(df): + return df + + df_chunk = ( + df_chunk.pipe(noop_filter) + .pipe(noop_filter) + .pipe(noop_filter) + .pipe(noop_filter) + .pipe(noop_filter) + .pipe(noop_filter) + ) + + # TODO concat chunks for outputting def cli_init(): @@ -52,7 +41,7 @@ def cli_init(): "--output-dir", type=Path, help="Directory to store the output data files.", - required=True + required=True, ) return parser.parse_args() diff --git a/src/kanta/engine/output.py b/src/kanta/engine/output.py new file mode 100644 index 0000000..e69de29 diff --git a/src/kanta/engine/reader.py b/src/kanta/engine/reader.py index 7ba2a0e..73cf132 100644 --- a/src/kanta/engine/reader.py +++ b/src/kanta/engine/reader.py @@ -1,16 +1,21 @@ +from collections.abc import Iterator from pathlib import Path import pandas as pd +import pyarrow.parquet as pq -from kanta.config import engine_read_columns +from kanta.config import ENGINE_CHUNK_N_LINES, ENGINE_READ_COLUMNS -def chunk_iterator(input_file: Path): - return ( - pd.read_parquet( - input_file, - engine="pyarrow", - columns=engine_read_columns, - dtype_backend="pyarrow" +def chunk_iterator(input_file: Path) -> Iterator[pd.DataFrame]: + # Use pyarrow to read the Parquet file in chunks. + parquet_file = pq.ParquetFile(input_file) + for batch in parquet_file.iter_batches( + batch_size=ENGINE_CHUNK_N_LINES, + # Select only the given columns, this speeds up the read quite a lot for Parquet files. + columns=ENGINE_READ_COLUMNS, + ): + yield batch.to_pandas( + # Use nullable data-types backed by pyarrow. + types_mapper=pd.ArrowDtype ) - ) From 2fd10f2ba7d1a2479996d943492ea6feb32e34d8 Mon Sep 17 00:00:00 2001 From: Vincent <4919840+vincent-octo@users.noreply.github.com> Date: Mon, 15 Jun 2026 10:18:15 +0200 Subject: [PATCH 06/15] implement concatenating chunks to output --- src/kanta/config.py | 6 +-- src/kanta/engine/__main__.py | 13 ++++++- src/kanta/engine/output.py | 71 ++++++++++++++++++++++++++++++++++++ 3 files changed, 85 insertions(+), 5 deletions(-) diff --git a/src/kanta/config.py b/src/kanta/config.py index bf40491..030a41d 100644 --- a/src/kanta/config.py +++ b/src/kanta/config.py @@ -1,8 +1,8 @@ # Shared config across the project. -# ============================================================================= -# ENGINE -# ============================================================================= +# ╭────────────────────────────────────────────────────────────────────────────╮ +# │ ENGINE │ +# ╰────────────────────────────────────────────────────────────────────────────╯ ENGINE_READ_COLUMNS = [ "!!!__TODO__!!!" ] diff --git a/src/kanta/engine/__main__.py b/src/kanta/engine/__main__.py index e8dd598..c95a00c 100644 --- a/src/kanta/engine/__main__.py +++ b/src/kanta/engine/__main__.py @@ -10,7 +10,13 @@ def main(): args = cli_init() - for df_chunk in reader.chunk_iterator(args.input_file): + output.run_safety_checks(args.output_dir) + + chunks_dir = output.create_chunks_dir(args.output_dir) + + for chunk_index, df_chunk in enumerate( + reader.chunk_iterator(args.input_file) + ): def noop_filter(df): return df @@ -24,7 +30,10 @@ def noop_filter(df): .pipe(noop_filter) ) - # TODO concat chunks for outputting + output.write_chunk(df_chunk, chunks_dir, chunk_index) + + output_file = args.output_dir / f"{args.input_file.stem}.engine-stage.parquet" + output.concatenate_chunks(chunks_dir, output_file) def cli_init(): diff --git a/src/kanta/engine/output.py b/src/kanta/engine/output.py index e69de29..32b7d2d 100644 --- a/src/kanta/engine/output.py +++ b/src/kanta/engine/output.py @@ -0,0 +1,71 @@ +import shutil +import warnings +from pathlib import Path + +import pandas as pd +import pyarrow.parquet as pq + +CHUNKS_DIR_NAME = "_chunks" +CHUNKS_FILE_TEMPLATE = "chunk_{index:06d}.parquet" +CHUNKS_FILE_GLOB = "chunk_*.parquet" + + +def run_safety_checks(output_dir: Path): + """Checks to run before any computation to avoid situation where output cannot be written.""" + if output_dir.exists(): + raise FileExistsError( + f"The output directory already exists at {output_dir}. Aborting." + ) + + disk_usage = shutil.disk_usage(output_dir) + free_in_gib = disk_usage.free >> 30 + min_gib_warning = 50 + if free_in_gib < min_gib_warning: + warnings.warn(f"Only {free_in_gib} GiB of free disk space available.") + + +def create_chunks_dir(output_dir: Path) -> Path: + """Create a temporary directory to hold Parquet files for each chunk.""" + chunks_dir = output_dir / CHUNKS_DIR_NAME + chunks_dir.mkdir(parents=True) + return chunks_dir + + +def write_chunk(dataframe: pd.DataFrame, chunks_dir: Path, chunk_index: int) -> Path: + """Write one processed chunk to its own Parquet chunk file. + + Use `chunk_index` to keep track of order for later in-order concatenation. + """ + chunk_path = chunks_dir / CHUNKS_FILE_TEMPLATE.format(index=chunk_index) + dataframe.to_parquet(chunk_path, engine="pyarrow", compression="zstd", index=False) + return chunk_path + + +def concatenate_chunks(chunks_dir: Path, output_file: Path, cleanup: bool = True): + """Concatenate chunks in order so no sorting is required afterwards. + + The order relies on the filename, which holds the chunk index. + """ + chunks = sorted(chunks_dir.glob(CHUNKS_FILE_GLOB), key=get_chunk_index) + + writer = None + try: + for chunk_path in chunks: + table = pq.read_table(chunk_path) + + # Initialize the ParquetWriter, needs the schema. + if writer is None: + writer = pq.ParquetWriter(output_file, table.schema) + writer.write_table(table) + + finally: + if writer is not None: + writer.close() + + if cleanup: + shutil.rmtree(chunks_dir) + + +def get_chunk_index(chunk_path: Path) -> int: + """Extract the integer chunk index from a chunk file name (e.g. chunk_000007 -> 7).""" + return int(chunk_path.stem.split("_")[-1]) From 83708daf908ef5c55908a31c0a296396387dab62 Mon Sep 17 00:00:00 2001 From: Vincent <4919840+vincent-octo@users.noreply.github.com> Date: Mon, 15 Jun 2026 10:18:15 +0200 Subject: [PATCH 07/15] add --test parameter --- src/kanta/engine/__main__.py | 8 +++++++- src/kanta/engine/reader.py | 9 ++++++++- 2 files changed, 15 insertions(+), 2 deletions(-) diff --git a/src/kanta/engine/__main__.py b/src/kanta/engine/__main__.py index c95a00c..4745fd5 100644 --- a/src/kanta/engine/__main__.py +++ b/src/kanta/engine/__main__.py @@ -15,7 +15,7 @@ def main(): chunks_dir = output.create_chunks_dir(args.output_dir) for chunk_index, df_chunk in enumerate( - reader.chunk_iterator(args.input_file) + reader.chunk_iterator(args.input_file, is_test_run=args.test) ): def noop_filter(df): @@ -46,6 +46,12 @@ def cli_init(): help="Path to the Kanta Lab data file coming from the intake stage (Parquet)", required=True, ) + parser.add_argument( + "--test", + action="store_true", + help="Process only the first chunk. Use for development.", + required=False, + ) parser.add_argument( "--output-dir", type=Path, diff --git a/src/kanta/engine/reader.py b/src/kanta/engine/reader.py index 73cf132..d7ff0c3 100644 --- a/src/kanta/engine/reader.py +++ b/src/kanta/engine/reader.py @@ -7,9 +7,12 @@ from kanta.config import ENGINE_CHUNK_N_LINES, ENGINE_READ_COLUMNS -def chunk_iterator(input_file: Path) -> Iterator[pd.DataFrame]: +def chunk_iterator( + input_file: Path, *, is_test_run: bool = False +) -> Iterator[pd.DataFrame]: # Use pyarrow to read the Parquet file in chunks. parquet_file = pq.ParquetFile(input_file) + for batch in parquet_file.iter_batches( batch_size=ENGINE_CHUNK_N_LINES, # Select only the given columns, this speeds up the read quite a lot for Parquet files. @@ -19,3 +22,7 @@ def chunk_iterator(input_file: Path) -> Iterator[pd.DataFrame]: # Use nullable data-types backed by pyarrow. types_mapper=pd.ArrowDtype ) + + # Yield only the first item when test run is ON + if is_test_run: + break From a98b050e4765d2789bad10412156bb74e8331d54 Mon Sep 17 00:00:00 2001 From: Vincent <4919840+vincent-octo@users.noreply.github.com> Date: Mon, 15 Jun 2026 11:51:02 +0200 Subject: [PATCH 08/15] fix typos --- src/kanta/intake/assemble.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/kanta/intake/assemble.py b/src/kanta/intake/assemble.py index 65ff63e..aac1216 100644 --- a/src/kanta/intake/assemble.py +++ b/src/kanta/intake/assemble.py @@ -62,7 +62,7 @@ COL_PREFIX_FREETEXT = "freetext." -def main(source_list_file: Path, output_file: Path) -> Path: +def main(source_list_file: Path, output_file: Path) -> None: print() print("=== ASSEMBLE STAGE ===") pairs = validate_input_pairs(source_list_file) @@ -72,7 +72,7 @@ def main(source_list_file: Path, output_file: Path) -> Path: print("# Checking merge consistency") is_consistent = check_merge_consistency(output_file) - print("All good." if is_consistent else "!!! Inconsitent merge !!!") + print("All good." if is_consistent else "!!! Inconsistent merge !!!") def validate_input_pairs( @@ -136,7 +136,7 @@ def merge_by_pair(pairs: list[tuple[Path, Path]], parquet_output: str | Path) -> ) -def reorder_columns(frame: pl.LazyFame | pl.DataFrame) -> pl.LazyFrame | pl.DataFrame: +def reorder_columns(frame: pl.LazyFrame | pl.DataFrame) -> pl.LazyFrame | pl.DataFrame: column_order = ( ["_rowid_source"] # Columns for main From 4c6fd06a0fbbf6ce51208914bb29ca67487eb4d7 Mon Sep 17 00:00:00 2001 From: Vincent <4919840+vincent-octo@users.noreply.github.com> Date: Mon, 15 Jun 2026 11:56:25 +0200 Subject: [PATCH 09/15] refactor output writing for use in different places --- src/kanta/engine/__main__.py | 58 ++++++++++++++++------- src/kanta/engine/{output.py => writer.py} | 23 --------- src/kanta/intake/__main__.py | 29 ++++++++---- src/kanta/intake/assemble.py | 16 ++++++- src/kanta/intake/tidyup.py | 23 ++++----- src/kanta/output.py | 38 +++++++++++++++ 6 files changed, 125 insertions(+), 62 deletions(-) rename src/kanta/engine/{output.py => writer.py} (65%) create mode 100644 src/kanta/output.py diff --git a/src/kanta/engine/__main__.py b/src/kanta/engine/__main__.py index 4745fd5..6eb2460 100644 --- a/src/kanta/engine/__main__.py +++ b/src/kanta/engine/__main__.py @@ -4,18 +4,26 @@ import pandas as pd -from kanta.engine import output, reader - - -def main(): - args = cli_init() - - output.run_safety_checks(args.output_dir) +from kanta import output +from kanta.engine import reader, writer + + +def main( + input_file: Path, + output_file: Path, + tmp_dir: Path, + *, + is_test_run=False, +): + # Setup + configure_pandas() - chunks_dir = output.create_chunks_dir(args.output_dir) + chunks_dir = tmp_dir / "chunks" + chunks_dir.mkdir() + # Iterate over each chunk for chunk_index, df_chunk in enumerate( - reader.chunk_iterator(args.input_file, is_test_run=args.test) + reader.chunk_iterator(input_file, is_test_run=is_test_run) ): def noop_filter(df): @@ -30,13 +38,12 @@ def noop_filter(df): .pipe(noop_filter) ) - output.write_chunk(df_chunk, chunks_dir, chunk_index) + writer.write_chunk(df_chunk, chunks_dir, chunk_index) - output_file = args.output_dir / f"{args.input_file.stem}.engine-stage.parquet" - output.concatenate_chunks(chunks_dir, output_file) + writer.concatenate_chunks(chunks_dir, output_file) -def cli_init(): +def init_cli(): parser = ArgumentParser( description="Kanta Lab preprocessing pipeline: raw data ⇒ clean data." ) @@ -53,11 +60,16 @@ def cli_init(): required=False, ) parser.add_argument( - "--output-dir", + "--output-file", type=Path, - help="Directory to store the output data files.", + help="Output file path (Parquet)", required=True, ) + parser.add_argument( + "--keep-intermediate-files", + help="Keep intermediate files, useful for debugging.", + action="store_true", + ) return parser.parse_args() @@ -85,5 +97,17 @@ def configure_pandas(): if __name__ == "__main__": - configure_pandas() - main() + args = init_cli() + + output.check_safe_write(args.output_file) + tmp_dir = output.create_tmp_dir() + + main( + args.input_file, + args.output_file, + tmp_dir, + is_test_run=args.test, + ) + + if not args.keep_intermediate_files: + output.teardown_dir(tmp_dir) diff --git a/src/kanta/engine/output.py b/src/kanta/engine/writer.py similarity index 65% rename from src/kanta/engine/output.py rename to src/kanta/engine/writer.py index 32b7d2d..4165567 100644 --- a/src/kanta/engine/output.py +++ b/src/kanta/engine/writer.py @@ -1,36 +1,13 @@ import shutil -import warnings from pathlib import Path import pandas as pd import pyarrow.parquet as pq -CHUNKS_DIR_NAME = "_chunks" CHUNKS_FILE_TEMPLATE = "chunk_{index:06d}.parquet" CHUNKS_FILE_GLOB = "chunk_*.parquet" -def run_safety_checks(output_dir: Path): - """Checks to run before any computation to avoid situation where output cannot be written.""" - if output_dir.exists(): - raise FileExistsError( - f"The output directory already exists at {output_dir}. Aborting." - ) - - disk_usage = shutil.disk_usage(output_dir) - free_in_gib = disk_usage.free >> 30 - min_gib_warning = 50 - if free_in_gib < min_gib_warning: - warnings.warn(f"Only {free_in_gib} GiB of free disk space available.") - - -def create_chunks_dir(output_dir: Path) -> Path: - """Create a temporary directory to hold Parquet files for each chunk.""" - chunks_dir = output_dir / CHUNKS_DIR_NAME - chunks_dir.mkdir(parents=True) - return chunks_dir - - def write_chunk(dataframe: pd.DataFrame, chunks_dir: Path, chunk_index: int) -> Path: """Write one processed chunk to its own Parquet chunk file. diff --git a/src/kanta/intake/__main__.py b/src/kanta/intake/__main__.py index 6bd162d..c3a1d32 100644 --- a/src/kanta/intake/__main__.py +++ b/src/kanta/intake/__main__.py @@ -3,6 +3,7 @@ from datetime import date from pathlib import Path + from kanta import output from kanta.intake import assemble from kanta.intake import tidyup @@ -34,32 +35,40 @@ default=24, ) parser.add_argument( - "--debug", - help="Increase verbosity and keep intermediate files", - required=False, + "--keep-intermediate-files", + help="Keep intermediate files, useful for debugging.", action="store_true", ) args = parser.parse_args() - # Assemble stage + # Setup output_file_assemble_stage = ( args.output_dir / f"finngen_R14_kanta_laboratory_responses.assemble-stage.{date.today()}.parquet" ) - post_assemble_file = assemble.main( - args.source_list_file, output_file_assemble_stage - ) - - # Tidy-up stage output_file_tidyup_stage = ( args.output_dir / f"finngen_R14_kanta_laboratory_responses_internal_1.0_{date.today()}.parquet" ) + output.check_safe_write(output_file_assemble_stage) + output.check_safe_write(output_file_tidyup_stage) + + tmp_dir = output.create_tmp_dir() + + # Assemble stage + assemble.main( + args.source_list_file, output_file_assemble_stage + ) + + # Tidy-up stage tidyup.main( output_file_assemble_stage, args.phenotype_file, output_file_tidyup_stage, + tmp_dir=tmp_dir, partition_n_buckets=args.partition_n_buckets, - keep_intermediate_files=args.debug, ) + + if not args.keep_intermediate_files: + output.teardown_dir(tmp_dir) diff --git a/src/kanta/intake/assemble.py b/src/kanta/intake/assemble.py index aac1216..5080196 100644 --- a/src/kanta/intake/assemble.py +++ b/src/kanta/intake/assemble.py @@ -15,6 +15,8 @@ import polars as pl +from kanta import output + EXPECTED_COLUMNS_MAIN = [ "FINNGENID", @@ -80,8 +82,18 @@ def validate_input_pairs( ) -> list[tuple[Path, Path]]: pairs = [] with open(source_list_file) as fp: - for line in fp: + for line_number, line in enumerate(fp, start=1): + # Skip blank lines (e.g. a trailing newline at end of file). + if not line.strip(): + continue + values = line.split(separator, maxsplit=2) + if len(values) != 2: + raise ValueError( + f"Malformed source-list line {line_number} in {source_list_file}: " + f"expected a main and a freetext path separated by {separator!r}, " + f"got: {line.strip()!r}" + ) main = validate_tsv_gz(values[0], source_list_file.parent) freetext = validate_tsv_gz(values[1], source_list_file.parent) @@ -258,4 +270,6 @@ def get_columns(input_path: Path) -> list[str]: args = parser.parse_args() + output.check_safe_write(args.output_file) + main(args.source_list_file, args.output_file) diff --git a/src/kanta/intake/tidyup.py b/src/kanta/intake/tidyup.py index 2f7ca0d..935016e 100644 --- a/src/kanta/intake/tidyup.py +++ b/src/kanta/intake/tidyup.py @@ -23,13 +23,13 @@ The GCP VM type appears to matter. N2D is about 2x faster than E2. """ -import tempfile -import shutil from argparse import ArgumentParser from pathlib import Path import polars as pl +from kanta import output + COLUMNS_UNIQUENESS_SORT = [ "FINNGENID", @@ -47,13 +47,10 @@ def main( assembled_file: Path, phenotype_file: Path, output_file: Path, + tmp_dir: Path, *, partition_n_buckets: int, - keep_intermediate_files: bool, ): - # Set up output file and temporary directory for intermediate files - tmp_dir = Path(tempfile.mkdtemp()) - print() print("=== TIDY-UP STAGE ===") print("# Run info") @@ -160,9 +157,6 @@ def main( .sink_parquet(output_file) ) - if not keep_intermediate_files: - shutil.rmtree(tmp_dir) - def init_cli(): parser = ArgumentParser() @@ -202,7 +196,7 @@ def init_cli(): def consolidate_columns(assembled_file: Path, output_file: Path) -> Path: - """Remove unecessary columns form the assembled file and rename the ones we will keep.""" + """Remove unnecessary columns form the assembled file and rename the ones we will keep.""" rename_columns = { "main.FINNGENID": "FINNGENID", "main.EVENT_AGE": "EVENT_AGE", @@ -262,10 +256,17 @@ def sort_dedup(frame: pl.LazyFrame | pl.DataFrame): if __name__ == "__main__": args = init_cli() + + output.check_safe_write(args.output_file) + tmp_dir = output.create_tmp_dir() + main( args.assembled_file, args.phenotype_file, args.output_file, + tmp_dir, partition_n_buckets=args.partition_n_buckets, - keep_intermediate_files=args.keep_intermediate_files, ) + + if not args.keep_intermediate_files: + output.teardown_dir(tmp_dir) diff --git a/src/kanta/output.py b/src/kanta/output.py new file mode 100644 index 0000000..a4432f8 --- /dev/null +++ b/src/kanta/output.py @@ -0,0 +1,38 @@ +import shutil +import tempfile +import warnings +from pathlib import Path + + +def check_safe_write(output_file: Path) -> None: + """Check it's safe to write to output file path.""" + if output_file.exists(): + raise FileExistsError( + f"The output file already exists at {output_file}. Aborting." + ) + + free_space = check_free_space(output_file.parent) + print(f"Free space in dir for output file {output_file.name}: {free_space}") + + +def create_tmp_dir(): + tmp_dir = Path(tempfile.mkdtemp()) + + free_space = check_free_space(tmp_dir) + print(f"Free space: {free_space} in {tmp_dir}") + + return tmp_dir + + +def check_free_space(dir, *, min_space_gb=50) -> str: + disk_usage = shutil.disk_usage(dir) + free_in_gib = disk_usage.free >> 30 + + if free_in_gib < min_space_gb: + warnings.warn(f"Only {free_in_gib} GiB of free disk space available.") + + return f"{free_in_gib} GiB" + + +def teardown_dir(dir): + shutil.rmtree(dir) From dff502d4c6cef55408dfabb949b3d067b1dcc02e Mon Sep 17 00:00:00 2001 From: Vincent <4919840+vincent-octo@users.noreply.github.com> Date: Mon, 15 Jun 2026 17:08:32 +0200 Subject: [PATCH 10/15] add column mapping needed for the engine --- src/kanta/config.py | 30 +++++++++++++++++++++++++++--- src/kanta/engine/__main__.py | 21 +++++++++------------ src/kanta/engine/pipes.py | 9 +++++++++ src/kanta/engine/reader.py | 4 ++-- 4 files changed, 47 insertions(+), 17 deletions(-) create mode 100644 src/kanta/engine/pipes.py diff --git a/src/kanta/config.py b/src/kanta/config.py index 030a41d..a83243a 100644 --- a/src/kanta/config.py +++ b/src/kanta/config.py @@ -3,9 +3,33 @@ # ╭────────────────────────────────────────────────────────────────────────────╮ # │ ENGINE │ # ╰────────────────────────────────────────────────────────────────────────────╯ -ENGINE_READ_COLUMNS = [ - "!!!__TODO__!!!" -] +# Which columns to read +# - (key) from the input file (output of intake stage) +# - (value) to its renamed name during processing +ENGINE_INPUT_COLUMNS_MAPPING = { + # + "FINNGENID": "FINNGENID", + "EVENT_AGE": "EVENT_AGE", + "tutkimuskoodistonjarjestelma": "CODING_SYSTEM", + "paikallinentutkimusnimike_selite": "TEST_NAME_ABBREVIATION", + "tutkimustulosarvo": "MEASUREMENT_VALUE", + "tutkimustulosyksikko": "MEASUREMENT_UNIT", + "tutkimusvastauksentila": "MEASUREMENT_STATUS", + "tuloksenpoikkeavuus": "TEST_OUTCOME", + "viitearvoryhma": "REFERENCE_RANGE_GROUP", + "viitevalialkuarvo": "REFERENCE_RANGE_LOWER_VALUE", + "viitevalialkuyksikko": "REFERENCE_RANGE_LOWER_UNIT", + "viitevaliloppuarvo": "REFERENCE_RANGE_UPPER_VALUE", + "viitevaliloppuyksikko": "REFERENCE_RANGE_UPPER_UNIT", + "tutkimustulosteksti": "MEASUREMENT_FREE_TEXT", + "paikallinentutkimusnimike_koodi": "paikallinentutkimusnimike_koodi", + "laboratoriotutkimusnimike": "laboratoriotutkimusnimike", + "APPROX_EVENT_DAY": "APPROX_EVENT_DAY", + "TIME": "TIME", + "_rowid": "_rowid", + "_rowid_source": "_rowid_source", + "SEX": "SEX", +} # Number of rows per chunk when streaming the input Parquet file. ENGINE_CHUNK_N_LINES = 1_000_000 diff --git a/src/kanta/engine/__main__.py b/src/kanta/engine/__main__.py index 6eb2460..b957009 100644 --- a/src/kanta/engine/__main__.py +++ b/src/kanta/engine/__main__.py @@ -4,8 +4,8 @@ import pandas as pd -from kanta import output -from kanta.engine import reader, writer +from kanta import output, config +from kanta.engine import pipes, reader, writer def main( @@ -25,17 +25,14 @@ def main( for chunk_index, df_chunk in enumerate( reader.chunk_iterator(input_file, is_test_run=is_test_run) ): - - def noop_filter(df): - return df - df_chunk = ( - df_chunk.pipe(noop_filter) - .pipe(noop_filter) - .pipe(noop_filter) - .pipe(noop_filter) - .pipe(noop_filter) - .pipe(noop_filter) + df_chunk.pipe(pipes.rename_cols, col_mapping=config.ENGINE_INPUT_COLUMNS_MAPPING) + .pipe(pipes.noop_filter) + .pipe(pipes.noop_filter) + .pipe(pipes.noop_filter) + .pipe(pipes.noop_filter) + .pipe(pipes.noop_filter) + .pipe(pipes.noop_filter) ) writer.write_chunk(df_chunk, chunks_dir, chunk_index) diff --git a/src/kanta/engine/pipes.py b/src/kanta/engine/pipes.py new file mode 100644 index 0000000..f96e4e2 --- /dev/null +++ b/src/kanta/engine/pipes.py @@ -0,0 +1,9 @@ +import pandas as pd + + +def noop_filter(df): + return df + + +def rename_cols(df : pd.DataFrame, *, col_mapping: dict) -> pd.DataFrame: + return df.rename(columns=col_mapping) diff --git a/src/kanta/engine/reader.py b/src/kanta/engine/reader.py index d7ff0c3..b6c4867 100644 --- a/src/kanta/engine/reader.py +++ b/src/kanta/engine/reader.py @@ -4,7 +4,7 @@ import pandas as pd import pyarrow.parquet as pq -from kanta.config import ENGINE_CHUNK_N_LINES, ENGINE_READ_COLUMNS +from kanta.config import ENGINE_CHUNK_N_LINES, ENGINE_INPUT_COLUMNS_MAPPING def chunk_iterator( @@ -16,7 +16,7 @@ def chunk_iterator( for batch in parquet_file.iter_batches( batch_size=ENGINE_CHUNK_N_LINES, # Select only the given columns, this speeds up the read quite a lot for Parquet files. - columns=ENGINE_READ_COLUMNS, + columns=ENGINE_INPUT_COLUMNS_MAPPING.keys(), ): yield batch.to_pandas( # Use nullable data-types backed by pyarrow. From 493286afbbf6a85a8a9be92f7e7ccbe582735cd3 Mon Sep 17 00:00:00 2001 From: Vincent <4919840+vincent-octo@users.noreply.github.com> Date: Mon, 15 Jun 2026 17:17:18 +0200 Subject: [PATCH 11/15] combine engine reader and writer to chunking module --- src/kanta/engine/__main__.py | 8 +++--- src/kanta/engine/{writer.py => chunking.py} | 24 ++++++++++++++++++ src/kanta/engine/reader.py | 28 --------------------- src/kanta/intake/__main__.py | 4 +-- 4 files changed, 29 insertions(+), 35 deletions(-) rename src/kanta/engine/{writer.py => chunking.py} (65%) delete mode 100644 src/kanta/engine/reader.py diff --git a/src/kanta/engine/__main__.py b/src/kanta/engine/__main__.py index b957009..781a7bb 100644 --- a/src/kanta/engine/__main__.py +++ b/src/kanta/engine/__main__.py @@ -5,7 +5,7 @@ import pandas as pd from kanta import output, config -from kanta.engine import pipes, reader, writer +from kanta.engine import pipes, chunking def main( @@ -23,7 +23,7 @@ def main( # Iterate over each chunk for chunk_index, df_chunk in enumerate( - reader.chunk_iterator(input_file, is_test_run=is_test_run) + chunking.chunk_iterator(input_file, is_test_run=is_test_run) ): df_chunk = ( df_chunk.pipe(pipes.rename_cols, col_mapping=config.ENGINE_INPUT_COLUMNS_MAPPING) @@ -35,9 +35,9 @@ def main( .pipe(pipes.noop_filter) ) - writer.write_chunk(df_chunk, chunks_dir, chunk_index) + chunking.write_chunk(df_chunk, chunks_dir, chunk_index) - writer.concatenate_chunks(chunks_dir, output_file) + chunking.concatenate_chunks(chunks_dir, output_file) def init_cli(): diff --git a/src/kanta/engine/writer.py b/src/kanta/engine/chunking.py similarity index 65% rename from src/kanta/engine/writer.py rename to src/kanta/engine/chunking.py index 4165567..7ecc03e 100644 --- a/src/kanta/engine/writer.py +++ b/src/kanta/engine/chunking.py @@ -1,13 +1,37 @@ import shutil +from collections.abc import Iterator from pathlib import Path import pandas as pd import pyarrow.parquet as pq +from kanta.config import ENGINE_CHUNK_N_LINES, ENGINE_INPUT_COLUMNS_MAPPING + CHUNKS_FILE_TEMPLATE = "chunk_{index:06d}.parquet" CHUNKS_FILE_GLOB = "chunk_*.parquet" +def chunk_iterator( + input_file: Path, *, is_test_run: bool = False +) -> Iterator[pd.DataFrame]: + # Use pyarrow to read the Parquet file in chunks. + parquet_file = pq.ParquetFile(input_file) + + for batch in parquet_file.iter_batches( + batch_size=ENGINE_CHUNK_N_LINES, + # Select only the given columns, this speeds up the read quite a lot for Parquet files. + columns=ENGINE_INPUT_COLUMNS_MAPPING.keys(), + ): + yield batch.to_pandas( + # Use nullable data-types backed by pyarrow. + types_mapper=pd.ArrowDtype + ) + + # Yield only the first item when test run is ON + if is_test_run: + break + + def write_chunk(dataframe: pd.DataFrame, chunks_dir: Path, chunk_index: int) -> Path: """Write one processed chunk to its own Parquet chunk file. diff --git a/src/kanta/engine/reader.py b/src/kanta/engine/reader.py deleted file mode 100644 index b6c4867..0000000 --- a/src/kanta/engine/reader.py +++ /dev/null @@ -1,28 +0,0 @@ -from collections.abc import Iterator -from pathlib import Path - -import pandas as pd -import pyarrow.parquet as pq - -from kanta.config import ENGINE_CHUNK_N_LINES, ENGINE_INPUT_COLUMNS_MAPPING - - -def chunk_iterator( - input_file: Path, *, is_test_run: bool = False -) -> Iterator[pd.DataFrame]: - # Use pyarrow to read the Parquet file in chunks. - parquet_file = pq.ParquetFile(input_file) - - for batch in parquet_file.iter_batches( - batch_size=ENGINE_CHUNK_N_LINES, - # Select only the given columns, this speeds up the read quite a lot for Parquet files. - columns=ENGINE_INPUT_COLUMNS_MAPPING.keys(), - ): - yield batch.to_pandas( - # Use nullable data-types backed by pyarrow. - types_mapper=pd.ArrowDtype - ) - - # Yield only the first item when test run is ON - if is_test_run: - break diff --git a/src/kanta/intake/__main__.py b/src/kanta/intake/__main__.py index c3a1d32..c1e23e3 100644 --- a/src/kanta/intake/__main__.py +++ b/src/kanta/intake/__main__.py @@ -57,9 +57,7 @@ tmp_dir = output.create_tmp_dir() # Assemble stage - assemble.main( - args.source_list_file, output_file_assemble_stage - ) + assemble.main(args.source_list_file, output_file_assemble_stage) # Tidy-up stage tidyup.main( From a19857e858089d721aa51868953c5f5e25d8bba7 Mon Sep 17 00:00:00 2001 From: Vincent <4919840+vincent-octo@users.noreply.github.com> Date: Mon, 15 Jun 2026 17:29:14 +0200 Subject: [PATCH 12/15] use same logic as before for chunk size --- src/kanta/config.py | 5 ++++- src/kanta/engine/__main__.py | 4 +++- src/kanta/engine/pipes.py | 2 +- 3 files changed, 8 insertions(+), 3 deletions(-) diff --git a/src/kanta/config.py b/src/kanta/config.py index a83243a..dcc8014 100644 --- a/src/kanta/config.py +++ b/src/kanta/config.py @@ -1,5 +1,8 @@ # Shared config across the project. +import os + + # ╭────────────────────────────────────────────────────────────────────────────╮ # │ ENGINE │ # ╰────────────────────────────────────────────────────────────────────────────╯ @@ -32,4 +35,4 @@ } # Number of rows per chunk when streaming the input Parquet file. -ENGINE_CHUNK_N_LINES = 1_000_000 +ENGINE_CHUNK_N_LINES = (os.process_cpu_count() or 2) * 10_000 diff --git a/src/kanta/engine/__main__.py b/src/kanta/engine/__main__.py index 781a7bb..3cb4e3b 100644 --- a/src/kanta/engine/__main__.py +++ b/src/kanta/engine/__main__.py @@ -26,7 +26,9 @@ def main( chunking.chunk_iterator(input_file, is_test_run=is_test_run) ): df_chunk = ( - df_chunk.pipe(pipes.rename_cols, col_mapping=config.ENGINE_INPUT_COLUMNS_MAPPING) + df_chunk.pipe( + pipes.rename_cols, col_mapping=config.ENGINE_INPUT_COLUMNS_MAPPING + ) .pipe(pipes.noop_filter) .pipe(pipes.noop_filter) .pipe(pipes.noop_filter) diff --git a/src/kanta/engine/pipes.py b/src/kanta/engine/pipes.py index f96e4e2..a958594 100644 --- a/src/kanta/engine/pipes.py +++ b/src/kanta/engine/pipes.py @@ -5,5 +5,5 @@ def noop_filter(df): return df -def rename_cols(df : pd.DataFrame, *, col_mapping: dict) -> pd.DataFrame: +def rename_cols(df: pd.DataFrame, *, col_mapping: dict) -> pd.DataFrame: return df.rename(columns=col_mapping) From 2113f6ba7d27ac01b64169115fa5d86e6a4f8669 Mon Sep 17 00:00:00 2001 From: Vincent <4919840+vincent-octo@users.noreply.github.com> Date: Tue, 16 Jun 2026 13:13:56 +0200 Subject: [PATCH 13/15] simplify calls to config --- src/kanta/config.py | 55 +++++++++++++++++++++++++----------- src/kanta/engine/__main__.py | 6 ++-- src/kanta/engine/chunking.py | 17 +++++------ src/kanta/engine/pipes.py | 6 ++-- 4 files changed, 53 insertions(+), 31 deletions(-) diff --git a/src/kanta/config.py b/src/kanta/config.py index dcc8014..9648050 100644 --- a/src/kanta/config.py +++ b/src/kanta/config.py @@ -2,17 +2,12 @@ import os - # ╭────────────────────────────────────────────────────────────────────────────╮ -# │ ENGINE │ +# │ COMMON │ # ╰────────────────────────────────────────────────────────────────────────────╯ -# Which columns to read -# - (key) from the input file (output of intake stage) -# - (value) to its renamed name during processing -ENGINE_INPUT_COLUMNS_MAPPING = { - # - "FINNGENID": "FINNGENID", - "EVENT_AGE": "EVENT_AGE", +# Renaming of column names (e.g. translation from Finnish) to more descriptive names used in this +# codebase. +RENAME_COLUMNS = { "tutkimuskoodistonjarjestelma": "CODING_SYSTEM", "paikallinentutkimusnimike_selite": "TEST_NAME_ABBREVIATION", "tutkimustulosarvo": "MEASUREMENT_VALUE", @@ -25,14 +20,40 @@ "viitevaliloppuarvo": "REFERENCE_RANGE_UPPER_VALUE", "viitevaliloppuyksikko": "REFERENCE_RANGE_UPPER_UNIT", "tutkimustulosteksti": "MEASUREMENT_FREE_TEXT", - "paikallinentutkimusnimike_koodi": "paikallinentutkimusnimike_koodi", - "laboratoriotutkimusnimike": "laboratoriotutkimusnimike", - "APPROX_EVENT_DAY": "APPROX_EVENT_DAY", - "TIME": "TIME", - "_rowid": "_rowid", - "_rowid_source": "_rowid_source", - "SEX": "SEX", } + +# ╭────────────────────────────────────────────────────────────────────────────╮ +# │ ENGINE │ +# ╰────────────────────────────────────────────────────────────────────────────╯ +# Which columns to read from the input file. This is used very early in the pipeline to limit the +# amount of data read, so the column renaming has not been done yet, hence using the original +# column names. +ENGINE_READ_COLUMNS = [ + "FINNGENID", + "EVENT_AGE", + "tutkimuskoodistonjarjestelma", + "paikallinentutkimusnimike_selite", + "tutkimustulosarvo", + "tutkimustulosyksikko", + "tutkimusvastauksentila", + "tuloksenpoikkeavuus", + "viitearvoryhma", + "viitevalialkuarvo", + "viitevalialkuyksikko", + "viitevaliloppuarvo", + "viitevaliloppuyksikko", + "tutkimustulosteksti", + "paikallinentutkimusnimike_koodi", + "laboratoriotutkimusnimike", + "APPROX_EVENT_DAY", + "TIME", + "_rowid", + "_rowid_source", + "SEX", +] + # Number of rows per chunk when streaming the input Parquet file. -ENGINE_CHUNK_N_LINES = (os.process_cpu_count() or 2) * 10_000 +ENGINE_N_LINES_PER_CHUNK = (os.process_cpu_count() or 2) * 10_000 +ENGINE_CHUNKS_FILE_TEMPLATE = "chunk_{index:06d}.parquet" +ENGINE_CHUNKS_FILE_GLOB = "chunk_*.parquet" diff --git a/src/kanta/engine/__main__.py b/src/kanta/engine/__main__.py index 3cb4e3b..b00de59 100644 --- a/src/kanta/engine/__main__.py +++ b/src/kanta/engine/__main__.py @@ -4,7 +4,7 @@ import pandas as pd -from kanta import output, config +from kanta import output from kanta.engine import pipes, chunking @@ -26,9 +26,7 @@ def main( chunking.chunk_iterator(input_file, is_test_run=is_test_run) ): df_chunk = ( - df_chunk.pipe( - pipes.rename_cols, col_mapping=config.ENGINE_INPUT_COLUMNS_MAPPING - ) + df_chunk.pipe(pipes.rename_cols) .pipe(pipes.noop_filter) .pipe(pipes.noop_filter) .pipe(pipes.noop_filter) diff --git a/src/kanta/engine/chunking.py b/src/kanta/engine/chunking.py index 7ecc03e..2257aee 100644 --- a/src/kanta/engine/chunking.py +++ b/src/kanta/engine/chunking.py @@ -5,10 +5,7 @@ import pandas as pd import pyarrow.parquet as pq -from kanta.config import ENGINE_CHUNK_N_LINES, ENGINE_INPUT_COLUMNS_MAPPING - -CHUNKS_FILE_TEMPLATE = "chunk_{index:06d}.parquet" -CHUNKS_FILE_GLOB = "chunk_*.parquet" +from kanta import config def chunk_iterator( @@ -18,9 +15,9 @@ def chunk_iterator( parquet_file = pq.ParquetFile(input_file) for batch in parquet_file.iter_batches( - batch_size=ENGINE_CHUNK_N_LINES, + batch_size=config.ENGINE_N_LINES_PER_CHUNK, # Select only the given columns, this speeds up the read quite a lot for Parquet files. - columns=ENGINE_INPUT_COLUMNS_MAPPING.keys(), + columns=config.ENGINE_READ_COLUMNS, ): yield batch.to_pandas( # Use nullable data-types backed by pyarrow. @@ -37,7 +34,9 @@ def write_chunk(dataframe: pd.DataFrame, chunks_dir: Path, chunk_index: int) -> Use `chunk_index` to keep track of order for later in-order concatenation. """ - chunk_path = chunks_dir / CHUNKS_FILE_TEMPLATE.format(index=chunk_index) + chunk_path = chunks_dir / config.ENGINE_CHUNKS_FILE_TEMPLATE.format( + index=chunk_index + ) dataframe.to_parquet(chunk_path, engine="pyarrow", compression="zstd", index=False) return chunk_path @@ -47,7 +46,9 @@ def concatenate_chunks(chunks_dir: Path, output_file: Path, cleanup: bool = True The order relies on the filename, which holds the chunk index. """ - chunks = sorted(chunks_dir.glob(CHUNKS_FILE_GLOB), key=get_chunk_index) + chunks = sorted( + chunks_dir.glob(config.ENGINE_CHUNKS_FILE_GLOB), key=get_chunk_index + ) writer = None try: diff --git a/src/kanta/engine/pipes.py b/src/kanta/engine/pipes.py index a958594..9ac448e 100644 --- a/src/kanta/engine/pipes.py +++ b/src/kanta/engine/pipes.py @@ -1,9 +1,11 @@ import pandas as pd +from kanta import config + def noop_filter(df): return df -def rename_cols(df: pd.DataFrame, *, col_mapping: dict) -> pd.DataFrame: - return df.rename(columns=col_mapping) +def rename_cols(df: pd.DataFrame) -> pd.DataFrame: + return df.rename(columns=config.RENAME_COLUMNS) From 25186f51fe28ea586c025e2a4039c52922bf9e78 Mon Sep 17 00:00:00 2001 From: Vincent <4919840+vincent-octo@users.noreply.github.com> Date: Tue, 16 Jun 2026 16:04:58 +0200 Subject: [PATCH 14/15] add parallelization to engine via multiprocessing --- src/kanta/config.py | 7 ++- src/kanta/engine/__main__.py | 99 ++++++++++++++++++++-------------- src/kanta/engine/chunking.py | 14 +++-- src/kanta/engine/pipes.py | 12 +++++ src/kanta/engine/processing.py | 41 ++++++++++++++ 5 files changed, 128 insertions(+), 45 deletions(-) create mode 100644 src/kanta/engine/processing.py diff --git a/src/kanta/config.py b/src/kanta/config.py index 9648050..3abc520 100644 --- a/src/kanta/config.py +++ b/src/kanta/config.py @@ -1,6 +1,5 @@ # Shared config across the project. -import os # ╭────────────────────────────────────────────────────────────────────────────╮ # │ COMMON │ @@ -54,6 +53,10 @@ ] # Number of rows per chunk when streaming the input Parquet file. -ENGINE_N_LINES_PER_CHUNK = (os.process_cpu_count() or 2) * 10_000 +# The value is independent of the number of CPUs: the memory used by the engine +# is already proportional to the number of workers, so scaling the number of +# rows per chunk by the number of workers would make the memory use scale by +# (N workers × N workers). +ENGINE_N_LINES_PER_CHUNK = 200_000 ENGINE_CHUNKS_FILE_TEMPLATE = "chunk_{index:06d}.parquet" ENGINE_CHUNKS_FILE_GLOB = "chunk_*.parquet" diff --git a/src/kanta/engine/__main__.py b/src/kanta/engine/__main__.py index b00de59..fb4f80e 100644 --- a/src/kanta/engine/__main__.py +++ b/src/kanta/engine/__main__.py @@ -1,11 +1,11 @@ -import warnings +import multiprocessing as mp +import os from argparse import ArgumentParser +from functools import partial from pathlib import Path -import pandas as pd - from kanta import output -from kanta.engine import pipes, chunking +from kanta.engine import chunking, processing def main( @@ -14,32 +14,52 @@ def main( tmp_dir: Path, *, is_test_run=False, + n_workers=1, ): # Setup - configure_pandas() + processing.configure_pandas() chunks_dir = tmp_dir / "chunks" chunks_dir.mkdir() # Iterate over each chunk - for chunk_index, df_chunk in enumerate( - chunking.chunk_iterator(input_file, is_test_run=is_test_run) - ): - df_chunk = ( - df_chunk.pipe(pipes.rename_cols) - .pipe(pipes.noop_filter) - .pipe(pipes.noop_filter) - .pipe(pipes.noop_filter) - .pipe(pipes.noop_filter) - .pipe(pipes.noop_filter) - .pipe(pipes.noop_filter) - ) + iter_indexed_chunks = chunking.chunk_iterator(input_file, is_test_run=is_test_run) - chunking.write_chunk(df_chunk, chunks_dir, chunk_index) + process_func = partial(processing.process_chunk, chunks_dir=chunks_dir) + + if n_workers > 1: + process_in_parallel( + process_func, iter_indexed_chunks, n_workers=n_workers + ) + else: + for indexed_chunk in iter_indexed_chunks: + process_func(indexed_chunk) chunking.concatenate_chunks(chunks_dir, output_file) +def process_in_parallel(func, indexed_chunks, *, n_workers: int): + """Process the chunks in parallel using `n_workers` spawned processes.""" + # Explicitly use the "spawn" method to create workers for consistent behavior across OSes + # and Python versions. + ctx = mp.get_context("spawn") + + # Setting the `initializer` here is required since we used the "spawn" method above to + # start workers: they start with no configuration, so we must provide it. + # + # NOTE(Vincent 2026-06-17): + # It looks like `multiprocessing.Pool` has a non-trivial silent failure mode: if a + # worker process get OOM-killed (i.e. because available memory is low) then the killed + # worker will fail silently and the Pool will hang forever. + # IMHO we should leave as it is for now and make sure to monitor memory usage. The future + # rewrite to Polars will remove the use of `multiprocessing` and this problem. + # See: https://bugs.python.org/issue22393 + with ctx.Pool(n_workers, initializer=processing.configure_pandas) as pool: + for _result in pool.imap_unordered(func, indexed_chunks): + # Consume the iterator, discard the result since it's written to disk. + pass + + def init_cli(): parser = ArgumentParser( description="Kanta Lab preprocessing pipeline: raw data ⇒ clean data." @@ -53,7 +73,10 @@ def init_cli(): parser.add_argument( "--test", action="store_true", - help="Process only the first chunk. Use for development.", + help=( + "Process only the first chunk (useful for debugging). " + "This overwrites --n-workers to 1." + ), required=False, ) parser.add_argument( @@ -62,35 +85,32 @@ def init_cli(): help="Output file path (Parquet)", required=True, ) + parser.add_argument( + "--n-workers", + type=int, + default=os.process_cpu_count() or 1, + help=( + "Number of worker processes used to process chunks in parallel. " + "Defaults to the number of available CPUs. Use 1 to run serially " + "(useful for debugging)." + ), + required=False, + ) parser.add_argument( "--keep-intermediate-files", help="Keep intermediate files, useful for debugging.", action="store_true", ) - return parser.parse_args() - + args = parser.parse_args() -def configure_pandas(): - # Treat NaN (a real float value) and NA (a missing value) as distinct. - pd.options.future.distinguish_nan_and_na = True + if args.n_workers < 1: + raise ValueError("--n-workers must be 1 or more") - # Default to the pyarrow engine for all Parquet reads/writes, so we don't have to pass - # engine="pyarrow" on every call. - pd.options.io.parquet.engine = "pyarrow" + if args.test: + args.n_workers = 1 - # Turn chained assignment into a hard error. - # Chained assignment have weird behavior in that they would turn operations into no-op. - # For example this chained assignment *does not change any value* of df: - # `df[df["A"] > 0]["B"] = 1` - # Instead, use `.loc` or `.iloc` to get correct behavior: - # `df.loc[df["A"] > 0, "B"] = 1` - # We change Pandas default from jsut throw a warning (ChainedAssignmentError), to actually - # raising an error. - # Note that unfortunately we can't just set the option - # `mode.chained_assignment` to `"raise"` because it has no effect under - # Copy-on-Write, so we have to resort to promoting the warning to an error. - warnings.filterwarnings("error", category=pd.errors.ChainedAssignmentError) + return args if __name__ == "__main__": @@ -104,6 +124,7 @@ def configure_pandas(): args.output_file, tmp_dir, is_test_run=args.test, + n_workers=args.n_workers, ) if not args.keep_intermediate_files: diff --git a/src/kanta/engine/chunking.py b/src/kanta/engine/chunking.py index 2257aee..ab71c43 100644 --- a/src/kanta/engine/chunking.py +++ b/src/kanta/engine/chunking.py @@ -10,20 +10,26 @@ def chunk_iterator( input_file: Path, *, is_test_run: bool = False -) -> Iterator[pd.DataFrame]: +) -> Iterator[tuple[int, pd.DataFrame]]: # Use pyarrow to read the Parquet file in chunks. parquet_file = pq.ParquetFile(input_file) + chunk_index = 0 for batch in parquet_file.iter_batches( batch_size=config.ENGINE_N_LINES_PER_CHUNK, # Select only the given columns, this speeds up the read quite a lot for Parquet files. columns=config.ENGINE_READ_COLUMNS, ): - yield batch.to_pandas( - # Use nullable data-types backed by pyarrow. - types_mapper=pd.ArrowDtype + yield ( + chunk_index, + batch.to_pandas( + # Use nullable data-types backed by pyarrow. + types_mapper=pd.ArrowDtype + ), ) + chunk_index += 1 + # Yield only the first item when test run is ON if is_test_run: break diff --git a/src/kanta/engine/pipes.py b/src/kanta/engine/pipes.py index 9ac448e..a28cc9b 100644 --- a/src/kanta/engine/pipes.py +++ b/src/kanta/engine/pipes.py @@ -9,3 +9,15 @@ def noop_filter(df): def rename_cols(df: pd.DataFrame) -> pd.DataFrame: return df.rename(columns=config.RENAME_COLUMNS) + + +def run_all(df: pd.DataFrame) -> pd.DataFrame: + return ( + df.pipe(rename_cols) + .pipe(noop_filter) + .pipe(noop_filter) + .pipe(noop_filter) + .pipe(noop_filter) + .pipe(noop_filter) + .pipe(noop_filter) + ) diff --git a/src/kanta/engine/processing.py b/src/kanta/engine/processing.py new file mode 100644 index 0000000..03650eb --- /dev/null +++ b/src/kanta/engine/processing.py @@ -0,0 +1,41 @@ +import warnings +from pathlib import Path + +import pandas as pd + +from kanta.engine import chunking, pipes + + +def configure_pandas(): + """Set preferred Pandas behavior via options. + + IMPORTANT: This function must be called when initializing workers for multiprocessing, since + creating them with the 'spawn' method doesn't carry over the Pandas configuration. + """ + # Treat NaN (a real float value) and NA (a missing value) as distinct. + pd.options.future.distinguish_nan_and_na = True + + # Default to the pyarrow engine for all Parquet reads/writes, so we don't have to pass + # engine="pyarrow" on every call. + pd.options.io.parquet.engine = "pyarrow" + + # Turn chained assignment into a hard error. + # Chained assignments have weird behavior in that they would turn operations into no-ops. + # For example this chained assignment *does not change any value* of df: + # `df[df["A"] > 0]["B"] = 1` + # Instead, use `.loc` or `.iloc` to get correct behavior: + # `df.loc[df["A"] > 0, "B"] = 1` + # We change Pandas default from just throwing a warning (ChainedAssignmentError), to actually + # raising an error. + # Note that unfortunately we can't just set the option + # `mode.chained_assignment` to `"raise"` because it has no effect under + # Copy-on-Write, so we have to resort to promoting the warning to an error. + warnings.filterwarnings("error", category=pd.errors.ChainedAssignmentError) + + +def process_chunk(indexed_chunk: tuple[int, pd.DataFrame], chunks_dir: Path) -> Path: + chunk_index, df_chunk = indexed_chunk + + df_chunk = pipes.run_all(df_chunk) + + return chunking.write_chunk(df_chunk, chunks_dir, chunk_index) From d61593b93ca610f708c3a1e557a57f72fd187651 Mon Sep 17 00:00:00 2001 From: Vincent <4919840+vincent-octo@users.noreply.github.com> Date: Wed, 17 Jun 2026 16:11:38 +0200 Subject: [PATCH 15/15] change kanta.config to have only cross-module vars If the role of a variable is a cross-module contract, then it belongs to kanta.config. Otherwise it belongs to their own module (e.g. engine knobs belong into kanta.engine). --- src/kanta/config.py | 51 +++-------------------------------- src/kanta/engine/__main__.py | 4 +-- src/kanta/engine/chunking.py | 52 +++++++++++++++++++++++++++++------- src/kanta/engine/pipes.py | 2 +- 4 files changed, 49 insertions(+), 60 deletions(-) diff --git a/src/kanta/config.py b/src/kanta/config.py index 3abc520..db66d60 100644 --- a/src/kanta/config.py +++ b/src/kanta/config.py @@ -1,12 +1,9 @@ # Shared config across the project. - -# ╭────────────────────────────────────────────────────────────────────────────╮ -# │ COMMON │ -# ╰────────────────────────────────────────────────────────────────────────────╯ -# Renaming of column names (e.g. translation from Finnish) to more descriptive names used in this -# codebase. -RENAME_COLUMNS = { +# Aliases mapping column name from input (dict keys) to a name used in the code (dict values). +# The purpose is to expose easier column names that can be referenced in the data processing code. +# For more column names, check: https://github.com/FINNGEN/Kanta_lab_QC#column-description +COLUMN_ALIASES = { "tutkimuskoodistonjarjestelma": "CODING_SYSTEM", "paikallinentutkimusnimike_selite": "TEST_NAME_ABBREVIATION", "tutkimustulosarvo": "MEASUREMENT_VALUE", @@ -20,43 +17,3 @@ "viitevaliloppuyksikko": "REFERENCE_RANGE_UPPER_UNIT", "tutkimustulosteksti": "MEASUREMENT_FREE_TEXT", } - - -# ╭────────────────────────────────────────────────────────────────────────────╮ -# │ ENGINE │ -# ╰────────────────────────────────────────────────────────────────────────────╯ -# Which columns to read from the input file. This is used very early in the pipeline to limit the -# amount of data read, so the column renaming has not been done yet, hence using the original -# column names. -ENGINE_READ_COLUMNS = [ - "FINNGENID", - "EVENT_AGE", - "tutkimuskoodistonjarjestelma", - "paikallinentutkimusnimike_selite", - "tutkimustulosarvo", - "tutkimustulosyksikko", - "tutkimusvastauksentila", - "tuloksenpoikkeavuus", - "viitearvoryhma", - "viitevalialkuarvo", - "viitevalialkuyksikko", - "viitevaliloppuarvo", - "viitevaliloppuyksikko", - "tutkimustulosteksti", - "paikallinentutkimusnimike_koodi", - "laboratoriotutkimusnimike", - "APPROX_EVENT_DAY", - "TIME", - "_rowid", - "_rowid_source", - "SEX", -] - -# Number of rows per chunk when streaming the input Parquet file. -# The value is independent of the number of CPUs: the memory used by the engine -# is already proportional to the number of workers, so scaling the number of -# rows per chunk by the number of workers would make the memory use scale by -# (N workers × N workers). -ENGINE_N_LINES_PER_CHUNK = 200_000 -ENGINE_CHUNKS_FILE_TEMPLATE = "chunk_{index:06d}.parquet" -ENGINE_CHUNKS_FILE_GLOB = "chunk_*.parquet" diff --git a/src/kanta/engine/__main__.py b/src/kanta/engine/__main__.py index fb4f80e..330e53c 100644 --- a/src/kanta/engine/__main__.py +++ b/src/kanta/engine/__main__.py @@ -28,9 +28,7 @@ def main( process_func = partial(processing.process_chunk, chunks_dir=chunks_dir) if n_workers > 1: - process_in_parallel( - process_func, iter_indexed_chunks, n_workers=n_workers - ) + process_in_parallel(process_func, iter_indexed_chunks, n_workers=n_workers) else: for indexed_chunk in iter_indexed_chunks: process_func(indexed_chunk) diff --git a/src/kanta/engine/chunking.py b/src/kanta/engine/chunking.py index ab71c43..2d85d78 100644 --- a/src/kanta/engine/chunking.py +++ b/src/kanta/engine/chunking.py @@ -5,7 +5,45 @@ import pandas as pd import pyarrow.parquet as pq -from kanta import config + +# Which columns to read from the input file. This is used very early in the pipeline to limit the +# amount of data read, so the column renaming has not been done yet, hence using the original +# column names. +# TODO(Vincent 2026-06-17) This should use the canonical column aliases from the config. A good +# time to do that would be when the data processing is in place so that all the column reference +# the canonical column aliases. +READ_COLUMNS = [ + "FINNGENID", + "EVENT_AGE", + "tutkimuskoodistonjarjestelma", + "paikallinentutkimusnimike_selite", + "tutkimustulosarvo", + "tutkimustulosyksikko", + "tutkimusvastauksentila", + "tuloksenpoikkeavuus", + "viitearvoryhma", + "viitevalialkuarvo", + "viitevalialkuyksikko", + "viitevaliloppuarvo", + "viitevaliloppuyksikko", + "tutkimustulosteksti", + "paikallinentutkimusnimike_koodi", + "laboratoriotutkimusnimike", + "APPROX_EVENT_DAY", + "TIME", + "_rowid", + "_rowid_source", + "SEX", +] + +# Number of rows per chunk when streaming the input Parquet file. +# The value is independent of the number of CPUs: the memory used by the engine +# is already proportional to the number of workers, so scaling the number of +# rows per chunk by the number of workers would make the memory use scale by +# (N workers × N workers). +N_LINES_PER_CHUNK = 200_000 +CHUNKS_FILE_TEMPLATE = "chunk_{index:06d}.parquet" +CHUNKS_FILE_GLOB = "chunk_*.parquet" def chunk_iterator( @@ -16,9 +54,9 @@ def chunk_iterator( chunk_index = 0 for batch in parquet_file.iter_batches( - batch_size=config.ENGINE_N_LINES_PER_CHUNK, + batch_size=N_LINES_PER_CHUNK, # Select only the given columns, this speeds up the read quite a lot for Parquet files. - columns=config.ENGINE_READ_COLUMNS, + columns=READ_COLUMNS, ): yield ( chunk_index, @@ -40,9 +78,7 @@ def write_chunk(dataframe: pd.DataFrame, chunks_dir: Path, chunk_index: int) -> Use `chunk_index` to keep track of order for later in-order concatenation. """ - chunk_path = chunks_dir / config.ENGINE_CHUNKS_FILE_TEMPLATE.format( - index=chunk_index - ) + chunk_path = chunks_dir / CHUNKS_FILE_TEMPLATE.format(index=chunk_index) dataframe.to_parquet(chunk_path, engine="pyarrow", compression="zstd", index=False) return chunk_path @@ -52,9 +88,7 @@ def concatenate_chunks(chunks_dir: Path, output_file: Path, cleanup: bool = True The order relies on the filename, which holds the chunk index. """ - chunks = sorted( - chunks_dir.glob(config.ENGINE_CHUNKS_FILE_GLOB), key=get_chunk_index - ) + chunks = sorted(chunks_dir.glob(CHUNKS_FILE_GLOB), key=get_chunk_index) writer = None try: diff --git a/src/kanta/engine/pipes.py b/src/kanta/engine/pipes.py index a28cc9b..3b626f3 100644 --- a/src/kanta/engine/pipes.py +++ b/src/kanta/engine/pipes.py @@ -8,7 +8,7 @@ def noop_filter(df): def rename_cols(df: pd.DataFrame) -> pd.DataFrame: - return df.rename(columns=config.RENAME_COLUMNS) + return df.rename(columns=config.COLUMN_ALIASES) def run_all(df: pd.DataFrame) -> pd.DataFrame: