ROLLOUT 3 · ecmwf/earthkit-data
ecmwf__earthkit-data-111
Solved
270 stotal time
13tool calls
15model calls
3,455tokens generated
108,236prompt tokens read
No error recorded
⚠ The request log has 14 model calls but the trace has 16 agent calls, so tokens are listed separately instead of beside each turn.
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System instructions 4,822 characters
You are a principal Python software engineer resolving a repository issue in `/workspace`. Your sole objective is to produce a minimal, root-cause source patch that passes every hidden fail-to-pass and pass-to-pass regression test on the first grading run. ## Critical Environment & Grader Rules 1. **Air-Gapped Sandbox & Available CLI Tools**: No network access. Never run `pip`, `uv`, `conda`, or `git fetch`. Note: `rg` (`ripgrep`) is NOT installed in the container — always use `grep -rn --include="*.py"` for fast exact searches so you never waste a tool call on `command not found`. 2. **Protected Grading Paths**: Before running official verification, the grading harness **strips and reverts all changes** to `tests/`, `test/`, `testing/`, `test_*.py`, `*_test.py`, `conftest.py`, `pyproject.toml`, `setup.cfg`, `pytest.ini`, and `tox.ini`. Every part of your fix MUST reside in non-test production source files. 3. **Untracked File Trap (`git add -N .`)**: `submit_patch` stages ALL untracked files inside `/workspace`! Never leave reproduction or scratch files inside `/workspace` — run reproductions inline via `python3 - <<'PY'` or inside `/tmp/repro.py` in a single `run_command`. 4. **Stdout Truncation Rule**: `run_command` truncates stdout after the first 5,000 characters from the TOP. Always run pytest quietly with short tracebacks: `pytest path/to/test_file.py -k pattern -q --tb=short --no-header` If a test file is large, redirect output to `/tmp/pytest.log` and inspect `tail -n 80 /tmp/pytest.log` so failure tracebacks at the bottom are never cut off. 5. **Strict Pacing Discipline**: `get_status` and `submit_patch` are free and do NOT count toward `max_tool_calls`. Target **16-22 counted tool calls total**, and **begin your first `edit_file` change no later than tool call 15**. Reserve at least 4 calls for verification, `git status --short && git diff`, and submission. ## Execution Protocol ### Phase 1 — Pinpoint Code & Tests Immediately (1-2 tool calls) - The user message already contains `Workspace Layout` — do NOT waste a turn running `ls` on top-level directories. - Run a single compound `run_command` with `grep -rn --include="*.py"` to locate: (a) the exact symbols, error strings, or functions from the problem description, (b) **all parallel or sibling implementations** (for example sync + async variants, `Client` + `AsyncClient`, serializer + deserializer, multiple backends/dialects, base + subclass methods, `__init__.py` / `__all__` exports), and (c) the closest existing unit test files under `tests/`. ### Phase 2 — Deep Read & Spec Anchor (2-5 tool calls) - Use `read_file` with generous `start_line` and `end_line` windows (180-300 lines per call so you read whole modules in fewer calls) on the target function/class, callers, type annotations, and neighboring tests. - Before editing, verify every explicit and implicit requirement from the issue: exact parameter names, defaults, boundary/domain edge cases, exception types/messages, `None` vs empty collection vs falsy (`0`, `False`, `""`) semantics, mutability/copying, and return types. ### Phase 3 — Reproduce Bug in One Call (1 tool call) - Run ONE concise command (`python3 - <<'PY' ... PY` or targeted `pytest ... -q --tb=short --no-header`) via `run_command` to observe the exact pre-fix failure. Do NOT spend multiple tool calls writing separate reproduction scripts. ### Phase 4 — Surgical Implementation Across All Parallel Paths (1-4 tool calls) - Begin editing by tool call 15! Use `edit_file` with 4-6 lines of exact surrounding context copied from `read_file`. - Update ALL parallel codepaths (sync/async, multiple classes/dialects, type hints) consistently so partial fixes do not fail sibling tests. - **2-Strike Edit Rule**: If `edit_file` fails twice on the same block due to whitespace or escaping, do not retry `edit_file` a third time — apply an atomic Python transformation via `run_command` and immediately verify `python3 -m py_compile path/to/file.py`. ### Phase 5 — Edge-Case Verification, Diff Hygiene & Clean Exit (2-4 tool calls) - Run a single compound `run_command` testing both your reproduction + boundary edge cases (`None`, empty input, leading/trailing delimiters, subdomain/prefix boundaries, subclass/async parity) AND the relevant existing `pytest` module(s) with `-q --tb=short --no-header`. - Run `git status --short && git diff` via `run_command`. Confirm: - ZERO untracked (`??`) files in `/workspace` (`rm -f` any untracked workspace files immediately), - ZERO modifications to `tests/` or protected config files (`git checkout -- tests/` if touched), - Minimal, clean diff with valid imports and indentation. - Call `submit_patch` once verification passes, then respond with a brief 2-sentence plain-text summary and make NO further tool calls.
Task prompt 2,913 characters
You are evaluating a software engineering task for repository ecmwf/earthkit-data.
Problem Statement:
to_pandas fails for bufr when no filters argument specified
### What happened?
Running this code:
```
ds = earthkit.data.from_source("file", "synop.bufr")
r = ds.to_pandas(columns=["latitude", "longitude"])
```
results in the following error:
```
File "git/pdbufr/pdbufr/bufr_structure.py", line 616, in stream_bufr
filters = dict(filters)
TypeError: 'NoneType' object is not iterable
```
To make it work `filters` must be specified. E.g.:
`r = ds.to_pandas(columns=["latitude", "longitude"], filters={})`
### What are the steps to reproduce the bug?
See above
### Version
0.1.3, develop
### Platform (OS and architecture)
all
### Relevant log output
_No response_
### Accompanying data
_No response_
### Organisation
_No response_
## Task Budget (Session terminates when any budget is exhausted)
- Time allowance: 7.5 minutes
- Tool calls allowance: 30 calls
- Max loop iterations: 40 turns
## Execution Environment Rules
- Single command timeout: 90 seconds (commands exceeding this fail without ending the session)
- Command output limit: 5000 characters
- File view limit: 150 lines per read_file call
- File character limit: 10000 characters per read_file call
- Environment is offline (no network/PyPI access). All repository and test dependencies are ALREADY pre-installed. Do NOT attempt to run pip install or download packages.
## Instructions:
0. All source code is under `/workspace`. Do NOT search outside `/workspace` (e.g. `/usr/`, `/wheels/`, system site-packages). If imports fail, the issue is in the source code under `/workspace`, not in missing system packages.
1. Analyze the problem statement and any provided hints carefully to identify all requested script paths, CLI subcommands, or Python modules.
2. Inspect existing codebase conventions and test files before making edits.
3. Verify your implementation using targeted tests or inline assertions before submitting.
4. Call submit_patch only after your implementation is complete and verified.
5. As your final action, you must return a text-only response reporting your completion to terminate the session.
## Workspace Layout
The repository is located at `/workspace`. Here is the directory tree (up to 3 levels):
```
./LICENSE
./Makefile
./README.md
./docs
./earthkit
./earthkit/data
./earthkit/data/__init__.py
./earthkit/data/arguments
./earthkit/data/core
./earthkit/data/data
./earthkit/data/decorators.py
./earthkit/data/indexing
./earthkit/data/input_manager.py
./earthkit/data/mergers
./earthkit/data/mirrors
./earthkit/data/readers
./earthkit/data/sources
./earthkit/data/sphinxext
./earthkit/data/testing.py
./earthkit/data/translators
./earthkit/data/utils
./earthkit/data/vocabularies
./earthkit/data/wrappers
./environment.yml
./pyproject.toml
./pytest.ini
./setup.cfg
./tests
```
Turn 1at 30 s327 tokens out2,836 prompt tokens
The user is reporting a `TypeError: 'NoneType' object is not iterable` when calling `to_pandas()` on a dataset loaded from a BUFR file without specifying the `filters` argument.
The error originates from `git/pdbufr/pdbufr/bufr_structure.py` (wait, the path looks like it's from a different repo or a linked dependency), but it's called via `earthkit.data.from_source("file", "synop.bufr").to_pandas(...)`.
Actually, the error trace says `File "git/pdbufr/pdbufr/bufr_structure.py", line 616`. I need to check if `pdbufr` is part of this repository or an external dependency. Based on the workspace layout, I don't see `pdbufr` in the root. It might be a dependency installed in the environment. However, the task is to fix the bug in `earthkit-data`.
Wait, if the error is in `pdbufr`, but the user says "to_pandas fails for bufr when no filters argument specified", maybe `earthkit-data` is passing `None` as `filters` to `pdbufr` when it should be passing an empty dictionary.
Let's look for `to_pandas` in `earthkit/data`.
TOOL CALL · run_command
{
"command": "grep -rn \"to_pandas\" earthkit/data | grep \".py\""
}Result of run_command 2,293 characters
{
"status": "ok",
"stdout": "earthkit/data/core/statistics.py:71: def to_pandas(self):\nearthkit/data/core/__init__.py:47: def to_pandas(self, **kwargs):\nearthkit/data/mergers/pandas.py:21: return pd.concat([s.to_pandas(**kwargs) for s in sources], **options)\nearthkit/data/mergers/__init__.py:17:FORWARDS = (\"to_xarray\", \"to_pandas\", \"to_tfdataset\")\nearthkit/data/mergers/__init__.py:74: def to_pandas(self, **kwargs):\nearthkit/data/mergers/__init__.py:113: def to_pandas(self, *args, **kwargs):\nearthkit/data/mergers/__init__.py:114: return self.obj.to_pandas(self.paths_or_sources, **kwargs)\nearthkit/data/mergers/__init__.py:129: to_pandas = _call_func\nearthkit/data/sources/multi.py:100: def to_pandas(self, **kwargs):\nearthkit/data/sources/multi.py:101: return make_merger(self.merger, self.sources).to_pandas(**kwargs)\nearthkit/data/sources/cds.py:130: def to_pandas(self, **kwargs):\nearthkit/data/sources/cds.py:146: return super().to_pandas(\nearthkit/data/sources/memory.py:41: def to_pandas(self, **kwargs):\nearthkit/data/sources/memory.py:42: return self._reader.to_pandas(**kwargs)\nearthkit/data/sources/ecmwf_api.py:99: def to_pandas(self, **kwargs):\nearthkit/data/sources/ecmwf_api.py:117: return super().to_pandas(\nearthkit/data/sources/file.py:105: def to_pandas(self, **kwargs):\nearthkit/data/sources/file.py:106: LOG.debug(\"Calling reader.to_pandas %s\", self)\nearthkit/data/sources/file.py:107: return self._reader.to_pandas(**kwargs)\nearthkit/data/wrappers/xarray.py:71: def to_pandas(self, *args, **kwargs):\nearthkit/data/readers/bufr.py:40: def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):\nearthkit/data/readers/grib/pandas.py:16: def to_pandas(self, latitude=None, longitude=None, **kwargs):\nearthkit/data/readers/netcdf.py:191: def to_pandas(self):\nearthkit/data/readers/netcdf.py:192: return self._da.to_pandas()\nearthkit/data/readers/netcdf.py:377: def to_pandas(self):\nearthkit/data/readers/netcdf.py:378: return self.to_xarray().to_pandas()\nearthkit/data/readers/odb.py:18: def to_pandas(self, **kwargs):\nearthkit/data/readers/csv.py:135: def to_pandas(self, **kwargs):\n",
"stderr": "",
"exit_code": 0
}Turn 2at 49 s167 tokens out4,028 prompt tokens
`earthkit/data/readers/bufr.py` has a `to_pandas` method: `earthkit/data/readers/bufr.py:40: def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):` This looks like the place where the issue resides. If `filters` is `None` by default and passed to `pdbufr`, and `pdbufr` expects an iterable (like a dict), then this is the cause. Let's examine `earthkit/data/readers/bufr.py`.
TOOL CALL · read_file
{
"end_line": 100,
"filepath": "earthkit/data/readers/bufr.py",
"start_line": 1
}Result of read_file 3,239 characters
{
"status": "ok",
"filepath": "earthkit/data/readers/bufr.py",
"content": "# (C) Copyright 2020 ECMWF.\n#\n# This software is licensed under the terms of the Apache Licence Version 2.0\n# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.\n# In applying this licence, ECMWF does not waive the privileges and immunities\n# granted to it by virtue of its status as an intergovernmental organisation\n# nor does it submit to any jurisdiction.\n#\n\n# See:\n# https://github.com/ecmwf/pdbufr\nfrom . import Reader\n\nCOLUMNS = (\"latitude\", \"longitude\", \"data_datetime\")\n\nBUFR_LS_KEYS = {\n \"edition\": \"edition\",\n \"type\": \"dataCategory\",\n \"subtype\": \"dataSubCategory\",\n \"c\": \"bufrHeaderCentre\",\n \"mv\": \"masterTablesVersionNumber\",\n \"lv\": \"localTablesVersionNumber\",\n \"subsets\": \"numberOfSubsets\",\n \"compr\": \"compressedData\",\n \"typicalDate\": \"typicalDate\",\n \"typicalTime\": \"typicalTime\",\n \"ident\": \"ident\",\n \"lat\": \"localLatitude\",\n \"lon\": \"localLongitude\",\n}\n\n\nclass BUFRReader(Reader):\n \"\"\"Represents a BUFR file\"\"\"\n\n def __init__(self, source, path):\n super().__init__(source, path)\n self._num = None\n\n def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):\n \"\"\"Extracts BUFR data into an pandas DataFranme using :xref:`pdbufr`.\n\n Parameters\n ----------\n columns: str, sequence[str]\n List of ecCodes BUFR keys to extract for each BUFR message/subset.\n See: :xref:`read_bufr` for details.\n filters: dict\n Defines the conditions when to extract the specified ``columns``. See:\n :xref:`read_bufr` for details.\n **kwargs: dict, optional\n Other keyword arguments:\n\n Returns\n -------\n Pandas DataFrame\n\n Examples\n --------\n :ref:`/examples/bufr.ipynb`\n\n \"\"\"\n import pdbufr\n\n return pdbufr.read_bufr(self.path, columns=columns, filters=filters)\n\n def __len__(self):\n if self._num is None:\n import eccodes\n\n with open(self.path, \"rb\") as f:\n self._num = eccodes.codes_count_in_file(f)\n return self._num\n\n def ls(self, *args, **kwargs):\n from pdbufr.high_level_bufr.bufr import BufrFile\n\n from earthkit.data.utils.summary import ls\n\n b = BufrFile(self.path)\n\n def _proc(keys, n):\n count_start = 0\n if n is None:\n count_end = len(self)\n elif n > 0:\n count_end = n\n else:\n num = len(self)\n count_start = max(0, num + n)\n count_end = num\n\n for count, msg in enumerate(b):\n with msg:\n if count_start <= count < count_end:\n yield ({k: msg[k1] for k, k1 in keys.items()})\n elif count >= count_end:\n break\n\n return ls(_proc, BUFR_LS_KEYS, *args, **kwargs)",
"start_line": 1,
"end_line": 100,
"total_lines": 105,
"is_truncated": false
}Turn 3at 82 s429 tokens out5,175 prompt tokens
The `to_pandas` method in `BUFRReader` is:
```python
def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):
# ... docstring ...
import pdbufr
return pdbufr.read_bufr(self.path, columns=columns, filters=filters)
```
The issue is that when `filters` is `None` (the default), it's passed as `None` to `pdbufr.read_bufr`, which then fails with `TypeError: 'NoneType' object is not iterable` inside `pdbufr/bufr_structure.py` at:
`filters = dict(filters)`
To fix this, we should ensure `filters` is passed as an empty dictionary if it is `None`.
Wait, should I check if `pdbufr.read_bufr` is supposed to handle `None`? The problem statement says "To make it work filters must be specified. E.g.: r = ds.to_pandas(columns=["latitude", "longitude"], filters={})". This strongly suggests that `pdbufr.read_bufr` (or something it calls) expects an iterable for `filters`.
Let's verify this by trying to reproduce it. Since I don't have a `synop.bufr` file, I might have to create a dummy one or mock `pdbufr.read_bufr`.
Actually, I can just write a reproduction script that mocks `pdbufr.read_bufr` to simulate the failure, but that won't prove it's failing because of the current code. I need a real BUFR file to be sure. But I are air-gapped. I should check if there are any BUFR files in the repo.
Let's check if there are any files ending in `.bufr`.
TOOL CALL · run_command
{
"command": "find . -name \"*.bufr\""
}Result of run_command 90 characters
{
"status": "ok",
"stdout": "./docs/examples/temp_10.bufr\n",
"stderr": "",
"exit_code": 0
}Turn 4at 99 s142 tokens out5,655 prompt tokens
There is a BUFR file: `./docs/examples/temp_10.bufr`. Let's try to reproduce the bug using it.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport earthkit.data\nimport pandas as pd\n\ntry:\n ds = earthkit.data.from_source(\"file\", \"docs/examples/temp_10.bufr\")\n r = ds.to_pandas(columns=[\"latitude\", \"longitude\"])\n print(\"Success!\")\nexcept Exception as e:\n import traceback\n traceback.print_exc()\nPY\n"
}Result of run_command 1,110 characters
{
"status": "ok",
"stdout": "",
"stderr": "Traceback (most recent call last):\n File \"<stdin>\", line 6, in <module>\n File \"/workspace/earthkit/data/sources/file.py\", line 107, in to_pandas\n return self._reader.to_pandas(**kwargs)\n File \"/workspace/earthkit/data/readers/bufr.py\", line 65, in to_pandas\n return pdbufr.read_bufr(self.path, columns=columns, filters=filters)\n File \"/usr/local/lib/python3.10/site-packages/pdbufr/bufr_read.py\", line 29, in read_bufr\n return reader.execute()\n File \"/usr/local/lib/python3.10/site-packages/pdbufr/readers/__init__.py\", line 45, in execute\n return _read(bufr_obj)\n File \"/usr/local/lib/python3.10/site-packages/pdbufr/readers/__init__.py\", line 39, in _read\n df = pd.DataFrame.from_records(rows)\n File \"/usr/local/lib/python3.10/site-packages/pandas/core/frame.py\", line 2459, in from_records\n first_row = next(data)\n File \"/usr/local/lib/python3.10/site-packages/pdbufr/readers/generic.py\", line 215, in read_records\n filters = dict(filters)\nTypeError: 'NoneType' object is not iterable\n",
"exit_code": 0
}Turn 5at 130 s408 tokens out6,222 prompt tokens
Reproduction successful! The error is exactly as described: `TypeError: 'NoneType' object is not iterable` coming from `pdbufr` when `filters=None`.
Now I will fix it by initializing `filters` to `{}` if it is `None` in `earthkit/data/readers/bufr.py`.
Wait, the current `to_pandas` is:
```python
def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):
# ...
import pdbufr
return pdbufr.read_bufr(self.path, columns=columns, filters=filters)
```
I should change it to:
```python
def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):
# ...
import pdbufr
if filters is None:
filters = {}
return pdbufr.read_bufr(self.path, columns=columns, filters=filters)
```
Wait, I should also check if `columns` could be `None`. The default is `COLUMNS`.
Looking at `pdbufr.read_bufr` trace, it seems it's the `filters` that's the problem.
Let's verify if `filters={}` fixes it.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport earthkit.data\nimport pandas as pd\n\ntry:\n ds = earthkit.data.from_source(\"file\", \"docs/examples/temp_10.bufr\")\n r = ds.to_pandas(columns=[\"latitude\", \"longitude\"], filters={})\n print(\"Success!\")\n print(r.head())\nexcept Exception as e:\n import traceback\n traceback.print_exc()\nPY\n"
}Result of run_command 214 characters
{
"status": "ok",
"stdout": "Success!\n latitude longitude\n0 67.37 26.63\n1 56.90 3.35\n2 58.87 5.67\n3 70.93 -8.67\n4 67.28 14.45\n",
"stderr": "",
"exit_code": 0
}Turn 6at 141 s144 tokens out6,750 prompt tokens
Yes, passing `filters={}` fixes the issue.
Now I'll apply the fix to `earthkit/data/readers/bufr.py`.
TOOL CALL · edit_file
{
"filepath": "earthkit/data/readers/bufr.py",
"new_string": " import pdbufr\n if filters is None:\n filters = {}\n\n return pdbufr.read_bufr(self.path, columns=columns, filters=filters)",
"old_string": " import pdbufr\n\n return pdbufr.read_bufr(self.path, columns=columns, filters=filters)"
}Result of edit_file 414 characters
{
"status": "ok",
"filepath": "earthkit/data/readers/bufr.py",
"occurrences": 1,
"strategy": "exact",
"diff": "--- a/earthkit/data/readers/bufr.py\n+++ b/earthkit/data/readers/bufr.py\n@@ -61,6 +61,8 @@\n \n \"\"\"\n import pdbufr\n+ if filters is None:\n+ filters = {}\n \n return pdbufr.read_bufr(self.path, columns=columns, filters=filters)\n \n",
"is_truncated": false
}Turn 7at 148 s125 tokens out7,058 prompt tokens
Now I will verify the fix.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport earthkit.data\nimport pandas as pd\n\ntry:\n ds = earthkit.data.from_source(\"file\", \"docs/examples/temp_10.bufr\")\n r = ds.to_pandas(columns=[\"latitude\", \"longitude\"])\n print(\"Success!\")\n print(r.head())\nexcept Exception as e:\n import traceback\n traceback.print_exc()\nPY\n"
}Result of run_command 214 characters
{
"status": "ok",
"stdout": "Success!\n latitude longitude\n0 67.37 26.63\n1 56.90 3.35\n2 58.87 5.67\n3 70.93 -8.67\n4 67.28 14.45\n",
"stderr": "",
"exit_code": 0
}Turn 8at 162 s162 tokens out7,303 prompt tokens
The fix works. Now I should check if there are other `BUFRReader` methods that might be affected or other reader patterns. Looking back at the `grep` results, `BUFRReader.to_pandas` was the only BUFR reader `to_pandas` method. Wait, what about other read methods? `BUFRReader` also has an `ls` method, but that's not `to_pandas`. I should also check if there are any other places in `earthkit/data` that might call `pdbufr.read_bufr` and pass `filters=None`.
TOOL CALL · run_command
{
"command": "grep -rn \"pdbufr.read_bufr\" earthkit/data"
}Result of run_command 171 characters
{
"status": "ok",
"stdout": "earthkit/data/readers/bufr.py:67: return pdbufr.read_bufr(self.path, columns=columns, filters=filters)\n",
"stderr": "",
"exit_code": 0
}Turn 9at 166 s64 tokens out7,542 prompt tokens
Only in `earthkit/data/readers/bufr.py`. Let's run existing tests for BUFR if any exist.
TOOL CALL · run_command
{
"command": "pytest tests/ -k \"bufr\" -q --tb=short --no-header"
}Result of run_command 2,311 characters
{
"status": "ok",
"stdout": "============================= test session starts ==============================\ncollected 351 items / 346 deselected / 5 selected\n\ntests/bufr/test_bufr_summary.py ....\ntests/documentation/test_notebooks.py s\n\n=============================== warnings summary ===============================\ntests/sources/test_cds.py:19\n /workspace/tests/sources/test_cds.py:19: PytestUnknownMarkWarning: Unknown pytest.mark.download - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html\n @pytest.mark.download\n\ntests/sources/test_cds.py:35\n /workspace/tests/sources/test_cds.py:35: PytestUnknownMarkWarning: Unknown pytest.mark.download - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html\n @pytest.mark.download\n\ntests/sources/test_cds.py:52\n /workspace/tests/sources/test_cds.py:52: PytestUnknownMarkWarning: Unknown pytest.mark.download - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html\n @pytest.mark.download\n\ntests/sources/test_cds.py:68\n /workspace/tests/sources/test_cds.py:68: PytestUnknownMarkWarning: Unknown pytest.mark.download - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html\n @pytest.mark.download\n\ntests/sources/test_mars.py:19\n /workspace/tests/sources/test_mars.py:19: PytestUnknownMarkWarning: Unknown pytest.mark.download - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html\n @pytest.mark.download\n\ntests/sources/test_mars.py:34\n /workspace/tests/sources/test_mars.py:34: PytestUnknownMarkWarning: Unknown pytest.mark.download - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html\n @pytest.mark.download\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n=========== 4 passed, 1 skipped, 346 deselected, 6 warnings in 0.70s ===========\n",
"stderr": "",
"exit_code": 0
}Turn 10at 173 s69 tokens out8,346 prompt tokens
`tests/bufr/test_bufr_summary.py` passed. I don't see any tests for `to_pandas` specifically for BUFR. Let me check `tests/bufr/` directory.
TOOL CALL · run_command
{
"command": "ls tests/bufr/"
}Result of run_command 82 characters
{
"status": "ok",
"stdout": "test_bufr_summary.py\n",
"stderr": "",
"exit_code": 0
}Turn 11at 176 s43 tokens out8,463 prompt tokens
Only one test file there. Let's double check if there are other BUFR tests.
TOOL CALL · run_command
{
"command": "find tests -name \"*bufr*\""
}Result of run_command 105 characters
{
"status": "ok",
"stdout": "tests/bufr\ntests/bufr/test_bufr_summary.py\n",
"stderr": "",
"exit_code": 0
}Turn 12at 195 s456 tokens out8,565 prompt tokens
It seems there aren't many tests for BUFR `to_pandas`. However, my reproduction script confirmed the fix.
Let's do a final check of the code.
`earthkit/data/readers/bufr.py`:
```python
def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):
"""Extracts BUFR data into an pandas DataFranme using :xref:`pdbufr`.
Parameters
----------
columns: str, sequence[str]
List of ecCodes BUFR keys to extract for each BUFR message/subset.
See: :xref:`read_bufr` for details.
filters: dict
Defines the conditions when to extract the specified ``columns``. See:
:xref:`read_bufr` for details.
**kwargs: dict, optional
Other keyword arguments:
Returns
-------
Pandas DataFrame
Examples
--------
:ref:`/examples/bufr.ipynb`
"""
import pdbufr
if filters is None:
filters = {}
return pdbufr.read_bufr(self.path, columns=columns, filters=filters)
```
This looks correct and follows the requirement.
Wait, should I check if `columns` can be `None`?
The default value is `COLUMNS = ("latitude", "longitude", "data_datetime")`.
If the user explicitly passes `columns=None`, will `pdbufr.read_bufr` fail?
Let's test it.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport earthkit.data\nimport pandas as pd\n\ntry:\n ds = earthkit.data.from_source(\"file\", \"docs/examples/temp_10.bufr\")\n r = ds.to_pandas(columns=None)\n print(\"Success!\")\nexcept Exception as e:\n import traceback\n traceback.print_exc()\nPY\n"
}Result of run_command 1,118 characters
{
"status": "ok",
"stdout": "",
"stderr": "Traceback (most recent call last):\n File \"<stdin>\", line 6, in <module>\n File \"/workspace/earthkit/data/sources/file.py\", line 107, in to_pandas\n return self._reader.to_pandas(**kwargs)\n File \"/workspace/earthkit/data/readers/bufr.py\", line 67, in to_pandas\n return pdbufr.read_bufr(self.path, columns=columns, filters=filters)\n File \"/usr/local/lib/python3.10/site-packages/pdbufr/bufr_read.py\", line 29, in read_bufr\n return reader.execute()\n File \"/usr/local/lib/python3.10/site-packages/pdbufr/readers/__init__.py\", line 45, in execute\n return _read(bufr_obj)\n File \"/usr/local/lib/python3.10/site-packages/pdbufr/readers/__init__.py\", line 39, in _read\n df = pd.DataFrame.from_records(rows)\n File \"/usr/local/lib/python3.10/site-packages/pandas/core/frame.py\", line 2459, in from_records\n first_row = next(data)\n File \"/usr/local/lib/python3.10/site-packages/pdbufr/readers/generic.py\", line 207, in read_records\n required_columns = set(columns)\nTypeError: 'NoneType' object is not iterable\n",
"exit_code": 0
}Turn 13at 254 s730 tokens out9,448 prompt tokens
Wow, `columns=None` also fails with `TypeError: 'NoneType' object is not iterable` in `pdbufr`.
The issue report specifically mentioned `filters`, but it seems `pdbufr` also requires `columns` to be iterable.
However, the `BUFRReader.to_pandas` has a default for `columns`: `columns=COLUMNS`.
If the user doesn't provide `columns`, it's fine.
If the user provides `columns=None`, it fails.
Should I also handle `columns is None`?
The docstring says `columns: str, sequence[str]`. It doesn't say it can be `None`.
The problem statement only mentioned the `filters` argument.
"to_pandas fails for bufr when no filters argument specified"
If I change the default of `filters` to `{}`, it would also work.
Current: `def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):`
Proposed: `def to_pandas(self, columns=COLUMNS, filters={}, **kwargs):`
BUT: using mutable defaults in Python is generally discouraged.
So `if filters is None: filters = {}` is the correct pattern.
Regarding `columns=None`, if the user explicitly passes `None`, it's their choice to override the default. But for consistency, maybe I should handle it? Or maybe the user shouldn't pass `None` if the spec says `str, sequence[str]`.
Let's look at other `to_pandas` implementations in the project to see if they handle `None` for similar arguments.
`earthkit/data/readers/grib/pandas.py`:
`def to_pandas(self, latitude=None, longitude=None, **kwargs):`
(This one seems to have different arguments)
The problem report specifically focuses on `filters`. I'll stick to fixing `filters`. If `columns` also needs to be iterable, and the user explicitly passes `None`, they are deviating from the expected type.
Wait, let me check `earthkit/data/readers/bufr.py` again.
`COLUMNS = ("latitude", "longitude", "data_datetime")`
The default is not `None`.
I think I'm good with the current fix.
One last check on the requirements: "minimal, root-cause source patch that passes every hidden fail-to-pass and pass-to-pass regression test on the first grading run."
The root cause was `filters` being `None` when passed to `pdbufr.read_bufr`, which then tried to call `dict(filters)`.
Final confirmation of the change:
```python
def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):
# ...
import pdbufr
if filters is None:
filters = {}
return pdbufr.read_bufr(self.path, columns=columns, filters=filters)
```
This handles the case where `filters` is not provided (defaults to `None`) as well as the case where it is explicitly provided as `None`.
I'll run `git status --short && git diff` before submitting.
TOOL CALL · run_command
{
"command": "git status --short && git diff"
}Result of run_command 506 characters
{
"status": "ok",
"stdout": " M earthkit/data/readers/bufr.py\ndiff --git a/earthkit/data/readers/bufr.py b/earthkit/data/readers/bufr.py\nindex 59c7672..14e9aed 100644\n--- a/earthkit/data/readers/bufr.py\n+++ b/earthkit/data/readers/bufr.py\n@@ -61,6 +61,8 @@ class BUFRReader(Reader):\n \n \"\"\"\n import pdbufr\n+ if filters is None:\n+ filters = {}\n \n return pdbufr.read_bufr(self.path, columns=columns, filters=filters)\n \n",
"stderr": "",
"exit_code": 0
}Turn 14at 255 s17 tokens out10,394 prompt tokens
The diff is clean and minimal.
TOOL CALL · submit_patch
Result of submit_patch 55 characters
{
"status": "ok",
"patch_size": 396,
"files_changed": 1
}Turn 15at 265 s172 tokens out10,451 prompt tokens
I have fixed the bug where `to_pandas` for BUFR files failed when the `filters` argument was not specified. This was due to `None` being passed to `pdbufr.read_bufr`, which expected an iterable for the `filters` parameter. I added a check to ensure `filters` is initialized to an empty dictionary if it is `None`.
Turn 16at 265 s
The issue was caused by `BUFRReader.to_pandas` passing `filters=None` to `pdbufr.read_bufr` when no filters were provided, which led to a `TypeError` as `pdbufr` attempted to call `dict(filters)`. The fix ensures that `filters` is initialized to an empty dictionary if it is `None` before being passed to the underlying `pdbufr` call.
Model calls (not matched to turns)
Generated tokens 327 tokens · stopped: STOP
The user is reporting a `TypeError: 'NoneType' object is not iterable` when calling `to_pandas()` on a dataset loaded from a BUFR file without specifying the `filters` argument.
The error originates from `git/pdbufr/pdbufr/bufr_structure.py` (wait, the path looks like it's from a different repo or a linked dependency), but it's called via `earthkit.data.from_source("file", "synop.bufr").to_pandas(...)`.
Actually, the error trace says `File "git/pdbufr/pdbufr/bufr_structure.py", line 616`. I need to check if `pdbufr` is part of this repository or an external dependency. Based on the workspace layout, I don't see `pdbufr` in the root. It might be a dependency installed in the environment. However, the task is to fix the bug in `earthkit-data`.
Wait, if the error is in `pdbufr`, but the user says "to_pandas fails for bufr when no filters argument specified", maybe `earthkit-data` is passing `None` as `filters` to `pdbufr` when it should be passing an empty dictionary.
Let's look for `to_pandas` in `earthkit/data`.<|channel>thought
The user is reporting a `TypeError: 'NoneType' object is not iterable` when calling `to_pandas()` on a dataset loaded from a BUFR file without specifying the `filters` argument.
The error originates from `git/pdbufr/pdbufr/bufr_structure.py` (wait, the path looks like it's from a different repo or a linked dependency), but it's called via `earthkit.data.from_source("file", "synop.bufr").to_pandas(...)`.
Actually, the error trace says `File "git/pdbufr/pdbufr/bufr_structure.py", line 616`. I need to check if `pdbufr` is part of this repository or an external dependency. Based on the workspace layout, I don't see `pdbufr` in the root. It might be a dependency installed in the environment. However, the task is to fix the bug in `earthkit-data`.
Wait, if the error is in `pdbufr`, but the user says "to_pandas fails for bufr when no filters argument specified", maybe `earthkit-data` is passing `None` as `filters` to `pdbufr` when it should be passing an empty dictionary.
Let's look for `to_pandas` in `earthkit/data`.<channel|><|tool_call>call:run_command{command:<|"|>grep -rn "to_pandas" earthkit/data | grep ".py"<|"|>}<tool_call|><|tool_response>
Generated tokens 167 tokens · stopped: STOP
`earthkit/data/readers/bufr.py` has a `to_pandas` method: `earthkit/data/readers/bufr.py:40: def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):` This looks like the place where the issue resides. If `filters` is `None` by default and passed to `pdbufr`, and `pdbufr` expects an iterable (like a dict), then this is the cause. Let's examine `earthkit/data/readers/bufr.py`.
`earthkit/data/readers/bufr.py` has a `to_pandas` method:
`earthkit/data/readers/bufr.py:40: def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):`
This looks like the place where the issue resides. If `filters` is `None` by default and passed to `pdbufr`, and `pdbufr` expects an iterable (like a dict), then this is the cause.
Let's examine `earthkit/data/readers/bufr.py`.<channel|><|tool_call>call:read_file{filepath:<|"|>earthkit/data/readers/bufr.py<|"|>,start_line:1,end_line:100}<tool_call|><|tool_response>
Generated tokens 429 tokens · stopped: STOP
The `to_pandas` method in `BUFRReader` is:
```python
def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):
# ... docstring ...
import pdbufr
return pdbufr.read_bufr(self.path, columns=columns, filters=filters)
```
The issue is that when `filters` is `None` (the default), it's passed as `None` to `pdbufr.read_bufr`, which then fails with `TypeError: 'NoneType' object is not iterable` inside `pdbufr/bufr_structure.py` at:
`filters = dict(filters)`
To fix this, we should ensure `filters` is passed as an empty dictionary if it is `None`.
Wait, should I check if `pdbufr.read_bufr` is supposed to handle `None`? The problem statement says "To make it work filters must be specified. E.g.: r = ds.to_pandas(columns=["latitude", "longitude"], filters={})". This strongly suggests that `pdbufr.read_bufr` (or something it calls) expects an iterable for `filters`.
Let's verify this by trying to reproduce it. Since I don't have a `synop.bufr` file, I might have to create a dummy one or mock `pdbufr.read_bufr`.
Actually, I can just write a reproduction script that mocks `pdbufr.read_bufr` to simulate the failure, but that won't prove it's failing because of the current code. I need a real BUFR file to be sure. But I are air-gapped. I should check if there are any BUFR files in the repo.
Let's check if there are any files ending in `.bufr`.
The `to_pandas` method in `BUFRReader` is:
```python
def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):
# ... docstring ...
import pdbufr
return pdbufr.read_bufr(self.path, columns=columns, filters=filters)
```
The issue is that when `filters` is `None` (the default), it's passed as `None` to `pdbufr.read_bufr`, which then fails with `TypeError: 'NoneType' object is not iterable` inside `pdbufr/bufr_structure.py` at:
`filters = dict(filters)`
To fix this, we should ensure `filters` is passed as an empty dictionary if it is `None`.
Wait, should I check if `pdbufr.read_bufr` is supposed to handle `None`? The problem statement says "To make it work filters must be specified. E.g.: r = ds.to_pandas(columns=["latitude", "longitude"], filters={})". This strongly suggests that `pdbufr.read_bufr` (or something it calls) expects an iterable for `filters`.
Let's verify this by trying to reproduce it. Since I don't have a `synop.bufr` file, I might have to create a dummy one or mock `pdbufr.read_bufr`.
Actually, I can just write a reproduction script that mocks `pdbufr.read_bufr` to simulate the failure, but that won't prove it's failing because of the current code. I need a real BUFR file to be sure. But I are air-gapped. I should check if there are any BUFR files in the repo.
Let's check if there are any files ending in `.bufr`.
<channel|><|tool_call>call:run_command{command:<|"|>find . -name "*.bufr"<|"|>}<tool_call|><|tool_response>
Generated tokens 142 tokens · stopped: STOP
There is a BUFR file: `./docs/examples/temp_10.bufr`. Let's try to reproduce the bug using it.
There is a BUFR file: `./docs/examples/temp_10.bufr`.
Let's try to reproduce the bug using it.
<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import earthkit.data
import pandas as pd
try:
ds = earthkit.data.from_source("file", "docs/examples/temp_10.bufr")
r = ds.to_pandas(columns=["latitude", "longitude"])
print("Success!")
except Exception as e:
import traceback
traceback.print_exc()
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 408 tokens · stopped: STOP
Reproduction successful! The error is exactly as described: `TypeError: 'NoneType' object is not iterable` coming from `pdbufr` when `filters=None`.
Now I will fix it by initializing `filters` to `{}` if it is `None` in `earthkit/data/readers/bufr.py`.
Wait, the current `to_pandas` is:
```python
def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):
# ...
import pdbufr
return pdbufr.read_bufr(self.path, columns=columns, filters=filters)
```
I should change it to:
```python
def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):
# ...
import pdbufr
if filters is None:
filters = {}
return pdbufr.read_bufr(self.path, columns=columns, filters=filters)
```
Wait, I should also check if `columns` could be `None`. The default is `COLUMNS`.
Looking at `pdbufr.read_bufr` trace, it seems it's the `filters` that's the problem.
Let's verify if `filters={}` fixes it.
Reproduction successful! The error is exactly as described: `TypeError: 'NoneType' object is not iterable` coming from `pdbufr` when `filters=None`.
Now I will fix it by initializing `filters` to `{}` if it is `None` in `earthkit/data/readers/bufr.py`.
Wait, the current `to_pandas` is:
```python
def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):
# ...
import pdbufr
return pdbufr.read_bufr(self.path, columns=columns, filters=filters)
```
I should change it to:
```python
def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):
# ...
import pdbufr
if filters is None:
filters = {}
return pdbufr.read_bufr(self.path, columns=columns, filters=filters)
```
Wait, I should also check if `columns` could be `None`. The default is `COLUMNS`.
Looking at `pdbufr.read_bufr` trace, it seems it's the `filters` that's the problem.
Let's verify if `filters={}` fixes it.
<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import earthkit.data
import pandas as pd
try:
ds = earthkit.data.from_source("file", "docs/examples/temp_10.bufr")
r = ds.to_pandas(columns=["latitude", "longitude"], filters={})
print("Success!")
print(r.head())
except Exception as e:
import traceback
traceback.print_exc()
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 144 tokens · stopped: STOP
Yes, passing `filters={}` fixes the issue.
Now I'll apply the fix to `earthkit/data/readers/bufr.py`.
Yes, passing `filters={}` fixes the issue.
Now I'll apply the fix to `earthkit/data/readers/bufr.py`.
<channel|><|tool_call>call:edit_file{filepath:<|"|>earthkit/data/readers/bufr.py<|"|>,new_string:<|"|> import pdbufr
if filters is None:
filters = {}
return pdbufr.read_bufr(self.path, columns=columns, filters=filters)<|"|>,old_string:<|"|> import pdbufr
return pdbufr.read_bufr(self.path, columns=columns, filters=filters)<|"|>}<tool_call|><|tool_response>
Generated tokens 125 tokens · stopped: STOP
Now I will verify the fix.
Now I will verify the fix.
<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import earthkit.data
import pandas as pd
try:
ds = earthkit.data.from_source("file", "docs/examples/temp_10.bufr")
r = ds.to_pandas(columns=["latitude", "longitude"])
print("Success!")
print(r.head())
except Exception as e:
import traceback
traceback.print_exc()
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 162 tokens · stopped: STOP
The fix works. Now I should check if there are other `BUFRReader` methods that might be affected or other reader patterns. Looking back at the `grep` results, `BUFRReader.to_pandas` was the only BUFR reader `to_pandas` method. Wait, what about other read methods? `BUFRReader` also has an `ls` method, but that's not `to_pandas`. I should also check if there are any other places in `earthkit/data` that might call `pdbufr.read_bufr` and pass `filters=None`.
The fix works. Now I should check if there are other `BUFRReader` methods that might be affected or other reader patterns.
Looking back at the `grep` results, `BUFRReader.to_pandas` was the only BUFR reader `to_pandas` method.
Wait, what about other read methods? `BUFRReader` also has an `ls` method, but that's not `to_pandas`.
I should also check if there are any other places in `earthkit/data` that might call `pdbufr.read_bufr` and pass `filters=None`.
<channel|><|tool_call>call:run_command{command:<|"|>grep -rn "pdbufr.read_bufr" earthkit/data<|"|>}<tool_call|><|tool_response>
Generated tokens 64 tokens · stopped: STOP
Only in `earthkit/data/readers/bufr.py`. Let's run existing tests for BUFR if any exist.
Only in `earthkit/data/readers/bufr.py`.
Let's run existing tests for BUFR if any exist.
<channel|><|tool_call>call:run_command{command:<|"|>pytest tests/ -k "bufr" -q --tb=short --no-header<|"|>}<tool_call|><|tool_response>
Generated tokens 69 tokens · stopped: STOP
`tests/bufr/test_bufr_summary.py` passed. I don't see any tests for `to_pandas` specifically for BUFR. Let me check `tests/bufr/` directory.
`tests/bufr/test_bufr_summary.py` passed. I don't see any tests for `to_pandas` specifically for BUFR. Let me check `tests/bufr/` directory.
<channel|><|tool_call>call:run_command{command:<|"|>ls tests/bufr/<|"|>}<tool_call|><|tool_response>
Generated tokens 43 tokens · stopped: STOP
Only one test file there. Let's double check if there are other BUFR tests.
Only one test file there. Let's double check if there are other BUFR tests.
<channel|><|tool_call>call:run_command{command:<|"|>find tests -name "*bufr*"<|"|>}<tool_call|><|tool_response>
Generated tokens 456 tokens · stopped: STOP
It seems there aren't many tests for BUFR `to_pandas`. However, my reproduction script confirmed the fix.
Let's do a final check of the code.
`earthkit/data/readers/bufr.py`:
```python
def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):
"""Extracts BUFR data into an pandas DataFranme using :xref:`pdbufr`.
Parameters
----------
columns: str, sequence[str]
List of ecCodes BUFR keys to extract for each BUFR message/subset.
See: :xref:`read_bufr` for details.
filters: dict
Defines the conditions when to extract the specified ``columns``. See:
:xref:`read_bufr` for details.
**kwargs: dict, optional
Other keyword arguments:
Returns
-------
Pandas DataFrame
Examples
--------
:ref:`/examples/bufr.ipynb`
"""
import pdbufr
if filters is None:
filters = {}
return pdbufr.read_bufr(self.path, columns=columns, filters=filters)
```
This looks correct and follows the requirement.
Wait, should I check if `columns` can be `None`?
The default value is `COLUMNS = ("latitude", "longitude", "data_datetime")`.
If the user explicitly passes `columns=None`, will `pdbufr.read_bufr` fail?
Let's test it.
It seems there aren't many tests for BUFR `to_pandas`. However, my reproduction script confirmed the fix.
Let's do a final check of the code.
`earthkit/data/readers/bufr.py`:
```python
def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):
"""Extracts BUFR data into an pandas DataFranme using :xref:`pdbufr`.
Parameters
----------
columns: str, sequence[str]
List of ecCodes BUFR keys to extract for each BUFR message/subset.
See: :xref:`read_bufr` for details.
filters: dict
Defines the conditions when to extract the specified ``columns``. See:
:xref:`read_bufr` for details.
**kwargs: dict, optional
Other keyword arguments:
Returns
-------
Pandas DataFrame
Examples
--------
:ref:`/examples/bufr.ipynb`
"""
import pdbufr
if filters is None:
filters = {}
return pdbufr.read_bufr(self.path, columns=columns, filters=filters)
```
This looks correct and follows the requirement.
Wait, should I check if `columns` can be `None`?
The default value is `COLUMNS = ("latitude", "longitude", "data_datetime")`.
If the user explicitly passes `columns=None`, will `pdbufr.read_bufr` fail?
Let's test it.
<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import earthkit.data
import pandas as pd
try:
ds = earthkit.data.from_source("file", "docs/examples/temp_10.bufr")
r = ds.to_pandas(columns=None)
print("Success!")
except Exception as e:
import traceback
traceback.print_exc()
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 730 tokens · stopped: STOP
Wow, `columns=None` also fails with `TypeError: 'NoneType' object is not iterable` in `pdbufr`.
The issue report specifically mentioned `filters`, but it seems `pdbufr` also requires `columns` to be iterable.
However, the `BUFRReader.to_pandas` has a default for `columns`: `columns=COLUMNS`.
If the user doesn't provide `columns`, it's fine.
If the user provides `columns=None`, it fails.
Should I also handle `columns is None`?
The docstring says `columns: str, sequence[str]`. It doesn't say it can be `None`.
The problem statement only mentioned the `filters` argument.
"to_pandas fails for bufr when no filters argument specified"
If I change the default of `filters` to `{}`, it would also work.
Current: `def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):`
Proposed: `def to_pandas(self, columns=COLUMNS, filters={}, **kwargs):`
BUT: using mutable defaults in Python is generally discouraged.
So `if filters is None: filters = {}` is the correct pattern.
Regarding `columns=None`, if the user explicitly passes `None`, it's their choice to override the default. But for consistency, maybe I should handle it? Or maybe the user shouldn't pass `None` if the spec says `str, sequence[str]`.
Let's look at other `to_pandas` implementations in the project to see if they handle `None` for similar arguments.
`earthkit/data/readers/grib/pandas.py`:
`def to_pandas(self, latitude=None, longitude=None, **kwargs):`
(This one seems to have different arguments)
The problem report specifically focuses on `filters`. I'll stick to fixing `filters`. If `columns` also needs to be iterable, and the user explicitly passes `None`, they are deviating from the expected type.
Wait, let me check `earthkit/data/readers/bufr.py` again.
`COLUMNS = ("latitude", "longitude", "data_datetime")`
The default is not `None`.
I think I'm good with the current fix.
One last check on the requirements: "minimal, root-cause source patch that passes every hidden fail-to-pass and pass-to-pass regression test on the first grading run."
The root cause was `filters` being `None` when passed to `pdbufr.read_bufr`, which then tried to call `dict(filters)`.
Final confirmation of the change:
```python
def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):
# ...
import pdbufr
if filters is None:
filters = {}
return pdbufr.read_bufr(self.path, columns=columns, filters=filters)
```
This handles the case where `filters` is not provided (defaults to `None`) as well as the case where it is explicitly provided as `None`.
I'll run `git status --short && git diff` before submitting.
Wow, `columns=None` also fails with `TypeError: 'NoneType' object is not iterable` in `pdbufr`.
The issue report specifically mentioned `filters`, but it seems `pdbufr` also requires `columns` to be iterable.
However, the `BUFRReader.to_pandas` has a default for `columns`: `columns=COLUMNS`.
If the user doesn't provide `columns`, it's fine.
If the user provides `columns=None`, it fails.
Should I also handle `columns is None`?
The docstring says `columns: str, sequence[str]`. It doesn't say it can be `None`.
The problem statement only mentioned the `filters` argument.
"to_pandas fails for bufr when no filters argument specified"
If I change the default of `filters` to `{}`, it would also work.
Current: `def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):`
Proposed: `def to_pandas(self, columns=COLUMNS, filters={}, **kwargs):`
BUT: using mutable defaults in Python is generally discouraged.
So `if filters is None: filters = {}` is the correct pattern.
Regarding `columns=None`, if the user explicitly passes `None`, it's their choice to override the default. But for consistency, maybe I should handle it? Or maybe the user shouldn't pass `None` if the spec says `str, sequence[str]`.
Let's look at other `to_pandas` implementations in the project to see if they handle `None` for similar arguments.
`earthkit/data/readers/grib/pandas.py`:
`def to_pandas(self, latitude=None, longitude=None, **kwargs):`
(This one seems to have different arguments)
The problem report specifically focuses on `filters`. I'll stick to fixing `filters`. If `columns` also needs to be iterable, and the user explicitly passes `None`, they are deviating from the expected type.
Wait, let me check `earthkit/data/readers/bufr.py` again.
`COLUMNS = ("latitude", "longitude", "data_datetime")`
The default is not `None`.
I think I'm good with the current fix.
One last check on the requirements: "minimal, root-cause source patch that passes every hidden fail-to-pass and pass-to-pass regression test on the first grading run."
The root cause was `filters` being `None` when passed to `pdbufr.read_bufr`, which then tried to call `dict(filters)`.
Final confirmation of the change:
```python
def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):
# ...
import pdbufr
if filters is None:
filters = {}
return pdbufr.read_bufr(self.path, columns=columns, filters=filters)
```
This handles the case where `filters` is not provided (defaults to `None`) as well as the case where it is explicitly provided as `None`.
I'll run `git status --short && git diff` before submitting.
<channel|><|tool_call>call:run_command{command:<|"|>git status --short && git diff<|"|>}<tool_call|><|tool_response>
Generated tokens 17 tokens · stopped: STOP
The diff is clean and minimal.
The diff is clean and minimal.<channel|><|tool_call>call:submit_patch{}<tool_call|><|tool_response>
Patch, tests and logs
Final code change Included
diff --git a/earthkit/data/readers/bufr.py b/earthkit/data/readers/bufr.py
index 59c7672..14e9aed 100644
--- a/earthkit/data/readers/bufr.py
+++ b/earthkit/data/readers/bufr.py
@@ -61,6 +61,8 @@ class BUFRReader(Reader):
"""
import pdbufr
+ if filters is None:
+ filters = {}
return pdbufr.read_bufr(self.path, columns=columns, filters=filters)
Test output Included
============================= test session starts ============================== collecting ... collected 3 items tests/bufr/test_bufr_convert.py::test_bufr_to_pandas_no_filters[_kwargs0] PASSED tests/bufr/test_bufr_convert.py::test_bufr_to_pandas_no_filters[_kwargs1] PASSED tests/bufr/test_bufr_convert.py::test_bufr_to_pandas_filters PASSED ==================================== PASSES ==================================== - generated xml file: /tmp/rebench-grade-b04cf5c5d68044ba8c0ab18cddd3fb90.xml -- =========================== short test summary info ============================ PASSED tests/bufr/test_bufr_convert.py::test_bufr_to_pandas_no_filters[_kwargs0] PASSED tests/bufr/test_bufr_convert.py::test_bufr_to_pandas_no_filters[_kwargs1] PASSED tests/bufr/test_bufr_convert.py::test_bufr_to_pandas_filters ============================== 3 passed in 1.40s ===============================
Test errors Included
Test report (JUnit) Included
<?xml version="1.0" encoding="utf-8"?><testsuites name="pytest tests"><testsuite name="pytest" errors="0" failures="0" skipped="0" tests="3" time="1.401" timestamp="2026-11-14T04:30:42.778221+00:00" hostname="bb80311bb766"><testcase classname="tests.bufr.test_bufr_convert" name="test_bufr_to_pandas_no_filters[_kwargs0]" time="0.440" /><testcase classname="tests.bufr.test_bufr_convert" name="test_bufr_to_pandas_no_filters[_kwargs1]" time="0.058" /><testcase classname="tests.bufr.test_bufr_convert" name="test_bufr_to_pandas_filters" time="0.058" /></testsuite></testsuites>
Agent log Included
[ 0.0s] 📋 System Prompt: You are a principal Python software engineer resolving a repository issue in `/workspace`.
[ 0.0s] 🎯 Task Prompt: You are evaluating a software engineering task for repository ecmwf/earthkit-data.
[ 26.7s] 💭 (1029 chars) "The user is reporting a `TypeError: 'NoneType' object is not iterable` when calling
`to_pandas()` on a dataset loaded fr..."
[ 26.7s] 🔧 run_command grep -rn "to_pandas" earthkit/data | grep ".py"
[ 26.7s] → earthkit/data/core/statistics.py:71: def to_pandas(self):
[ 45.1s] 💭 (388 chars) "`earthkit/data/readers/bufr.py` has a `to_pandas` method:
`earthkit/data/readers/bufr.py:40: def to_pandas(self, colu..."
[ 45.1s] 📖 read_file (earthkit/data/readers/bufr.py)
[ 45.2s] ✓ {'status': 'ok', 'filepath': 'earthkit/data/readers/bufr.py', 'content': '# (C) Copyright 2020
ECMWF.\n#\n# This softwar…
[ 78.4s] 💭 (1388 chars) "The `to_pandas` method in `BUFRReader` is:
```python
def to_pandas(self, columns=COLUMNS, filters=None, **kwargs):
..."
[ 78.4s] 🔧 run_command find . -name "*.bufr"
[ 78.5s] → ./docs/examples/temp_10.bufr
[ 95.7s] 💭 (94 chars) "There is a BUFR file: `./docs/examples/temp_10.bufr`.
Let's try to reproduce the bug using it."
[ 95.7s] 🔧 run_command (12 lines) python3 - <<'PY'
[ 97.2s] 🔧
[ 125.8s] 💭 (960 chars) "Reproduction successful! The error is exactly as described: `TypeError: 'NoneType' object is
not iterable` coming from `..."
[ 125.8s] 🔧 run_command (13 lines) python3 - <<'PY'
[ 126.4s] → Success!
[ 137.7s] 💭 (102 chars) "Yes, passing `filters={}` fixes the issue.
Now I'll apply the fix to `earthkit/data/readers/bufr.py`."
[ 137.7s] ✏️ edit_file (earthkit/data/readers/bufr.py)
[ 137.8s] ✓ {'status': 'ok', 'filepath': 'earthkit/data/readers/bufr.py', 'occurrences': 1, 'strategy': 'exact',
'diff': '--- a/eart…
[ 143.9s] 💭 (26 chars) "Now I will verify the fix."
[ 143.9s] 🔧 run_command (13 lines) python3 - <<'PY'
[ 144.5s] → Success!
[ 157.9s] 💭 (460 chars) "The fix works. Now I should check if there are other `BUFRReader` methods that might be
affected or other reader pattern..."
[ 157.9s] 🔧 run_command grep -rn "pdbufr.read_bufr" earthkit/data
[ 158.0s] → earthkit/data/readers/bufr.py:67: return pdbufr.read_bufr(self.path, columns=columns,
filters=filters)
[ 161.9s] 💭 (89 chars) "Only in `earthkit/data/readers/bufr.py`.
Let's run existing tests for BUFR if any exist."
[ 161.9s] 🔧 run_command pytest tests/ -k "bufr" -q --tb=short --no-header
[ 163.0s] → ============================= test session starts ==============================
[ 169.4s] 💭 (140 chars) "`tests/bufr/test_bufr_summary.py` passed. I don't see any tests for `to_pandas` specifically
for BUFR. Let me check `tes..."
[ 169.4s] 🔧 run_command ls tests/bufr/
[ 169.4s] → test_bufr_summary.py
[ 172.6s] 💭 (75 chars) "Only one test file there. Let's double check if there are other BUFR tests."
[ 172.6s] 🔧 run_command find tests -name "*bufr*"
[ 172.6s] → tests/bufr
[ 191.6s] 💭 (1315 chars) "It seems there aren't many tests for BUFR `to_pandas`. However, my reproduction script
confirmed the fix.
Let's do a fi..."
[ 191.6s] 🔧 run_command (12 lines) python3 - <<'PY'
[ 192.1s] 🔧
[ 249.7s] 💭 (2637 chars) "Wow, `columns=None` also fails with `TypeError: 'NoneType' object is not iterable` in
`pdbufr`.
The issue report specif..."
[ 249.7s] 🔧 run_command git status --short && git diff
[ 249.8s] → M earthkit/data/readers/bufr.py
[ 251.0s] 💭 (30 chars) "The diff is clean and minimal."
[ 251.0s] 🤖 submit_patch
[ 251.1s] → submit_patch: {"status": "ok", "patch_size": 396, "files_changed": 1}
[ 261.4s] 💭 (313 chars) "I have fixed the bug where `to_pandas` for BUFR files failed when the `filters` argument was
not specified. This was due..."
[ 261.4s] ✅ Agent finished: The issue was caused by `BUFRReader.to_pandas` passing `filters=None` to
`pdbufr.read_bufr` when no filters were provided, which led to a `TypeError` as `pdbufr` attempted to call
`dict(filters)`. The...
Native result row
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"duration_seconds": 270.11,
"error": null,
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"collected_tests": 3,
"competition_junit_ok": true,
"error": null,
"required_issues_count": 0,
"resolved": true,
"status_counts": {
"PASSED": 3
},
"strict_clean_patch": true,
"test_exit_code": 0
},
"instance_id": "ecmwf__earthkit-data-111",
"pass_idx": 0,
"patch_chars": 396,
"phase1_seconds": 267.44,
"repo": "ecmwf/earthkit-data",
"request_log_path": "/kaggle-root/working/r31/rollouts_X/requests/ecmwf__earthkit-data-111__p0__r3.jsonl",
"resolved": true,
"rollout_idx": 3,
"run_key": "ecmwf__earthkit-data-111__p0__r3",
"strict_clean_patch": true,
"tool_calls": 13,
"total_llm_calls": 15,
"trace_path": "/kaggle-root/working/r31/rollouts_X/traces/trace_ecmwf__earthkit-data-111__p0__r3.json"
}