ROLLOUT 4 · jazzband/tablib
jazzband__tablib-613
Solved
456 stotal time
18tool calls
19model calls
6,712tokens generated
154,185prompt tokens read
Agent exceeded session timeout (7.5 min)
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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 2,358 characters
You are evaluating a software engineering task for repository jazzband/tablib.
Problem Statement:
ODS loading issue - ValueError: 'value' is not in list
When saving data containing the empty string to ODS format, the resulting ODS file is not loadable by tablib. The code below reproduces the problem.
```python
book = tablib.Databook()
book.load(
tablib.Databook(sets=[tablib.Dataset(("",))]).export("ods"),
format="ods",
)
```
If the empty string is replaced with `None` the problem does not occur.
Would it be possible for tablib to handle this situation in a more robust manner?
## 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):
```
./AUTHORS
./CODE_OF_CONDUCT.md
./HISTORY.md
./LICENSE
./README.md
./RELEASING.md
./docs
./pyproject.toml
./pytest.ini
./src
./src/tablib
./src/tablib/__init__.py
./src/tablib/_vendor
./src/tablib/core.py
./src/tablib/exceptions.py
./src/tablib/formats
./src/tablib/utils.py
./tests
./tox.ini
```
Turn 1at 10.0 s163 tokens out2,641 prompt tokens
The user is reporting a `ValueError: 'value' is not in list` when loading an ODS file that was exported from a `tablib.Dataset` containing an empty string.
Example:
```python
book = tablib.Databook()
book.load(
tablib.Databook(sets=[tablib.Dataset(("",))]).export("ods"),
format="ods",
)
```
I need to investigate the ODS export and import logic in `tablib`.
First, I'll locate the ODS implementation in the codebase.
TOOL CALL · run_command
{
"command": "grep -rn --include=\"*.py\" \"ods\" src/tablib | grep -v \"tests\""
}Result of run_command 1,643 characters
{
"status": "ok",
"stdout": "src/tablib/_vendor/dbfpy/header.py:56: # instance construction and initialization methods\nsrc/tablib/_vendor/dbfpy/header.py:176: # internal methods\nsrc/tablib/_vendor/dbfpy/header.py:208: # interface methods\nsrc/tablib/_vendor/dbfpy/record.py:160: # protected methods\nsrc/tablib/_vendor/dbfpy/record.py:183: # utility methods\nsrc/tablib/_vendor/dbfpy/record.py:201: # interface methods\nsrc/tablib/_vendor/dbfpy/dbf.py:53:20-dec-2005 [yc] removed fromStream and newDbf methods:\nsrc/tablib/_vendor/dbfpy/dbf.py:61:24-aug-1998 [jjk] add some encodeValue methods (not tested), other tweaks\nsrc/tablib/_vendor/dbfpy/dbf.py:163: # protected methods\nsrc/tablib/_vendor/dbfpy/dbf.py:189: # interface methods\nsrc/tablib/_vendor/dbfpy/dbf.py:233: # 'magic' methods (representation and sequence interface)\nsrc/tablib/formats/_ods.py:67: title = 'ods'\nsrc/tablib/formats/_ods.py:68: extensions = ('ods',)\nsrc/tablib/formats/_ods.py:178: ods_book = opendocument.load(in_stream)\nsrc/tablib/formats/_ods.py:179: for sheet in ods_book.spreadsheet.childNodes:\nsrc/tablib/formats/_ods.py:189: ods_book = opendocument.load(in_stream)\nsrc/tablib/formats/_ods.py:191: for sheet in ods_book.spreadsheet.childNodes:\nsrc/tablib/formats/__init__.py:16: \"ods\": {\"package_name\": \"odfpy package\", \"extras_name\": \"ods\"},\nsrc/tablib/formats/__init__.py:76: # and Dataset.get_<format>/set_<format> methods.\nsrc/tablib/formats/__init__.py:99: self.register('ods', 'tablib.formats._ods.ODSFormat')\n",
"stderr": "",
"exit_code": 0
}Turn 2at 18 s135 tokens out3,434 prompt tokens
The ODS format logic seems to be in `src/tablib/formats/_ods.py`. Now I'll reproduce the issue.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport tablib\ntry:\n book = tablib.Databook()\n book.load(\n tablib.Databook(sets=[tablib.Dataset((\"\",))]).export(\"ods\"),\n format=\"ods\",\n )\n print(\"Success\")\nexcept Exception as e:\n import traceback\n traceback.print_exc()\nPY\n"
}Result of run_command 1,071 characters
{
"status": "ok",
"stdout": "",
"stderr": "Traceback (most recent call last):\n File \"<stdin>\", line 4, in <module>\n File \"/tablib/src/tablib/core.py\", line 903, in load\n fmt.import_book(self, stream, **kwargs)\n File \"/tablib/src/tablib/formats/_ods.py\", line 195, in import_book\n cls.import_sheet(dset, sheet, headers)\n File \"/tablib/src/tablib/formats/_ods.py\", line 121, in import_sheet\n row_vals = [cls.read_cell(cell) for cell in row.childNodes if is_real_cell(cell)]\n File \"/tablib/src/tablib/formats/_ods.py\", line 121, in <listcomp>\n row_vals = [cls.read_cell(cell) for cell in row.childNodes if is_real_cell(cell)]\n File \"/tablib/src/tablib/formats/_ods.py\", line 168, in read_cell\n value = cls.read_cell(subnode, value_type)\n File \"/tablib/src/tablib/formats/_ods.py\", line 158, in read_cell\n value = cell.getAttribute('value')\n File \"/usr/local/lib/python3.10/site-packages/odf/element.py\", line 547, in getAttribute\n i = allowed_args.index(attr)\nValueError: 'value' is not in list\n",
"exit_code": 0
}Turn 3at 26 s108 tokens out3,989 prompt tokens
Okay, I reproduced it. The error comes from `odf/element.py:547` when calling `cell.getAttribute('value')`.
The traceback points to `src/tablib/formats/_ods.py`, lines 168, 158, 121.
Let's examine `src/tablib/formats/_ods.py`.
TOOL CALL · read_file
{
"filepath": "src/tablib/formats/_ods.py"
}Result of read_file 5,003 characters
{
"status": "ok",
"filepath": "src/tablib/formats/_ods.py",
"content": "\"\"\" Tablib - ODF Support.\n\"\"\"\n\nimport datetime as dt\nimport numbers\nfrom io import BytesIO\n\nfrom odf import number, opendocument, style, table, text\n\nimport tablib\n\nbold = style.Style(name=\"bold\", family=\"paragraph\")\nbold.addElement(style.TextProperties(\n fontweight=\"bold\",\n fontweightasian=\"bold\",\n fontweightcomplex=\"bold\",\n))\n\n\ndef set_date_style(style):\n style.addElement(number.Year(style=\"long\"))\n style.addElement(number.Text(text=\"-\"))\n style.addElement(number.Month(style=\"long\"))\n style.addElement(number.Text(text=\"-\"))\n style.addElement(number.Day(style=\"long\"))\n\n\ndef set_time_style(style):\n style.addElement(number.Hours(style=\"long\"))\n style.addElement(number.Text(text=\":\"))\n style.addElement(number.Minutes(style=\"long\"))\n style.addElement(number.Text(text=\":\"))\n style.addElement(number.Seconds(style=\"long\", decimalplaces=\"0\"))\n\n\ndate_style = number.DateStyle(name=\"date-style1\")\nset_date_style(date_style)\nds = style.Style(\n name=\"ds1\",\n datastylename=\"date-style1\",\n parentstylename=\"Default\",\n family=\"table-cell\",\n)\n\ntime_style = number.DateStyle(name=\"time-style1\")\nset_time_style(time_style)\nts = style.Style(\n name=\"ts1\",\n datastylename=\"time-style1\",\n parentstylename=\"Default\",\n family=\"table-cell\",\n)\n\ndatetime_style = number.DateStyle(name=\"datetime-style1\")\nset_date_style(datetime_style)\ndatetime_style.addElement(number.Text(text=\" \"))\nset_time_style(datetime_style)\ndts = style.Style(\n name=\"dts1\",\n datastylename=\"datetime-style1\",\n parentstylename=\"Default\",\n family=\"table-cell\",\n)\n\n\nclass ODSFormat:\n title = 'ods'\n extensions = ('ods',)\n\n @classmethod\n def export_set(cls, dataset):\n \"\"\"Returns ODF representation of Dataset.\"\"\"\n\n wb = opendocument.OpenDocumentSpreadsheet()\n wb.automaticstyles.addElement(bold)\n wb.styles.addElement(date_style)\n wb.automaticstyles.addElement(ds)\n wb.styles.addElement(time_style)\n wb.automaticstyles.addElement(ts)\n wb.styles.addElement(datetime_style)\n wb.automaticstyles.addElement(dts)\n\n ws = table.Table(name=dataset.title if dataset.title else 'Tablib Dataset')\n wb.spreadsheet.addElement(ws)\n cls.dset_sheet(dataset, ws)\n\n stream = BytesIO()\n wb.save(stream)\n return stream.getvalue()\n\n @classmethod\n def export_book(cls, databook):\n \"\"\"Returns ODF representation of DataBook.\"\"\"\n\n wb = opendocument.OpenDocumentSpreadsheet()\n wb.automaticstyles.addElement(bold)\n\n for i, dset in enumerate(databook._datasets):\n ws = table.Table(name=dset.title if dset.title else f\"Sheet{i}\")\n wb.spreadsheet.addElement(ws)\n cls.dset_sheet(dset, ws)\n\n stream = BytesIO()\n wb.save(stream)\n return stream.getvalue()\n\n @classmethod\n def import_sheet(cls, dset, sheet, headers=True, skip_lines=0):\n \"\"\"Populate dataset `dset` with sheet data.\"\"\"\n\n dset.title = sheet.getAttribute('name')\n\n def is_real_cell(cell):\n return cell.hasChildNodes() or not cell.getAttribute('numbercolumnsrepeated')\n\n for i, row in enumerate(sheet.childNodes):\n if row.tagName != 'table:table-row':\n continue\n if i < skip_lines:\n continue\n row_vals = [cls.read_cell(cell) for cell in row.childNodes if is_real_cell(cell)]\n if not row_vals:\n continue\n if i == skip_lines and headers:\n dset.headers = row_vals\n else:\n if i > skip_lines and len(row_vals) < dset.width:\n row_vals += [''] * (dset.width - len(row_vals))\n dset.append(row_vals)\n\n @classmethod\n def read_cell(cls, cell, value_type=None):\n def convert_date(val):\n if 'T' in val:\n return dt.datetime.strptime(val, \"%Y-%m-%dT%H:%M:%S\")\n else:\n return dt.datetime.strptime(val, \"%Y-%m-%d\").date()\n\n if value_type is None:\n value_type = cell.getAttribute('valuetype')\n if value_type == 'date':\n date_value = cell.getAttribute('datevalue')\n if date_value:\n return convert_date(date_value)\n if value_type == 'time':\n time_value = cell.getAttribute('timevalue')\n try:\n return dt.datetime.strptime(time_value, \"PT%HH%MM%SS\").time()\n except ValueError:\n # backwards compatibility for times exported with older tablib versions",
"start_line": 1,
"end_line": 150,
"total_lines": 249,
"is_truncated": true
}Turn 4at 32 s53 tokens out5,618 prompt tokens
I need to read the rest of `src/tablib/formats/_ods.py`.
TOOL CALL · read_file
{
"filepath": "src/tablib/formats/_ods.py",
"start_line": 151
}Result of read_file 4,161 characters
{
"status": "ok",
"filepath": "src/tablib/formats/_ods.py",
"content": " return dt.datetime.strptime(time_value, \"%H:%M:%S\").time()\n if value_type == 'boolean':\n bool_value = cell.getAttribute('booleanvalue')\n return bool_value == 'true'\n if not cell.childNodes:\n value = getattr(cell, 'data', None)\n if value is None:\n value = cell.getAttribute('value')\n if value is None:\n return ''\n if value_type == 'float':\n return float(value)\n if value_type == 'date':\n return convert_date(value)\n return value # Any other type default to 'string'\n\n for subnode in cell.childNodes:\n value = cls.read_cell(subnode, value_type)\n if value:\n return value\n\n @classmethod\n def import_set(cls, dset, in_stream, headers=True, skip_lines=0):\n \"\"\"Populate dataset `dset` from ODS stream.\"\"\"\n\n dset.wipe()\n\n ods_book = opendocument.load(in_stream)\n for sheet in ods_book.spreadsheet.childNodes:\n if sheet.qname[1] == 'table':\n cls.import_sheet(dset, sheet, headers, skip_lines)\n\n @classmethod\n def import_book(cls, dbook, in_stream, headers=True):\n \"\"\"Populate databook `dbook` from ODS stream.\"\"\"\n\n dbook.wipe()\n\n ods_book = opendocument.load(in_stream)\n\n for sheet in ods_book.spreadsheet.childNodes:\n if sheet.qname[1] != 'table':\n continue\n dset = tablib.Dataset()\n cls.import_sheet(dset, sheet, headers)\n dbook.add_sheet(dset)\n\n @classmethod\n def dset_sheet(cls, dataset, ws):\n \"\"\"Completes given worksheet from given Dataset.\"\"\"\n _package = dataset._package(dicts=False)\n\n for i, sep in enumerate(dataset._separators):\n _offset = i\n _package.insert((sep[0] + _offset), (sep[1],))\n\n for row_number, row in enumerate(_package, start=1):\n is_header = row_number == 1 and dataset.headers\n style = bold if is_header else None\n odf_row = table.TableRow(stylename=style)\n ws.addElement(odf_row)\n for j, col in enumerate(row):\n if isinstance(col, numbers.Number):\n cell = table.TableCell(valuetype=\"float\", value=col)\n elif isinstance(col, dt.datetime):\n cell = table.TableCell(\n valuetype=\"date\",\n datevalue=col.strftime('%Y-%m-%dT%H:%M:%S'),\n stylename=dts,\n )\n cell.addElement(text.P(text=col.strftime('%Y-%m-%d %H:%M:%S')))\n elif isinstance(col, dt.date):\n date_value = col.strftime('%Y-%m-%d')\n cell = table.TableCell(valuetype=\"date\", datevalue=date_value, stylename=ds)\n cell.addElement(text.P(text=date_value))\n elif isinstance(col, dt.time):\n cell = table.TableCell(\n valuetype=\"time\",\n timevalue=col.strftime('PT%HH%MM%SS'),\n stylename=ts,\n )\n cell.addElement(text.P(text=col.strftime('%H:%M:%S')))\n elif col is None:\n cell = table.TableCell(valuetype=\"void\")\n else:\n cell = table.TableCell(valuetype=\"string\")\n cell.addElement(text.P(text=str(col), stylename=style))\n odf_row.addElement(cell)\n\n @classmethod\n def detect(cls, stream):\n if isinstance(stream, bytes):\n # load expects a file-like object.\n stream = BytesIO(stream)\n try:\n opendocument.load(stream)\n return True\n except Exception:\n return False",
"start_line": 151,
"end_line": 249,
"total_lines": 249,
"is_truncated": false
}Turn 5at 155 s1,964 tokens out6,805 prompt tokens
Let's trace the failure.
In `import_sheet`:
```python
for i, row in enumerate(sheet.childNodes):
# ...
row_vals = [cls.read_cell(cell) for cell in row.childNodes if is_real_cell(cell)]
```
In `read_cell`:
```python
@classmethod
def read_cell(cls, cell, value_type=None):
def convert_date(val):
# ...
if value_type is None:
value_type = cell.getAttribute('valuetype')
# ...
if not cell.childNodes:
value = getattr(cell, 'data', None)
if value is None:
value = cell.getAttribute('value') # <--- This is where it fails!
if value is None:
return ''
# ...
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
if value:
return value
```
The error is `ValueError: 'value' is not in list` which comes from `odf/element.py:547` in `getAttribute`.
Looking at `odfpy` (which is what `odf` is), `getAttribute` probably checks if the attribute being requested is allowed for that element type.
If `cell` is a `TableCell`, let's see what attributes it has.
Wait, look at the code:
```python
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
if value:
return value
```
If `cell` has child nodes, it iterates through them and calls `read_cell` recursively.
If the cell was exported as:
```python
else:
cell = table.TableCell(valuetype="string")
cell.addElement(text.P(text=str(col), stylename=style))
```
And `col` was `""` (empty string), then `text.P(text="")`.
When importing:
1. `read_cell(cell)` is called. `cell` is the `TableCell`.
2. `cell.childNodes` will contain the `text.P` element.
3. `read_cell` iterates through `cell.childNodes`.
4. `read_cell(subnode, value_type)` is called where `subnode` is the `text.P` element.
5. In the recursive call:
- `subnode.childNodes` might be empty (if it's just a `P` element with text).
- If `subnode.childNodes` is empty:
- `value = getattr(subnode, 'data', None)`
- If `value` is `None`:
- `value = subnode.getAttribute('value')` <--- This is probably where the crash happens! Because `text.P` (a paragraph) likely doesn't have a `value` attribute.
Let's verify what `subnode` is.
In `read_cell`:
```python
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
if value:
return value
```
If `value` is `""` (empty string), `if value:` is False, so it continues.
If all subnodes return `""` or `None`, `read_cell` finally returns `None` (implicitly).
But wait, the traceback says:
```
File "/tablib/src/tablib/formats/_ods.py", line 168, in read_cell
value = cls.read_cell(subnode, value_type)
File "/tablib/src/tablib/formats/_ods.py", line 158, in read_cell
value = cell.getAttribute('value')
File "/usr/local/lib/python3.10/site-packages/odf/element.py", line 547, in getAttribute
i = allowed_args.index(attr)
ValueError: 'value' is not in list
```
Line 168: `value = cls.read_cell(subnode, value_type)`
Line 158: `value = cell.getAttribute('value')`
So it's exactly as I thought. `read_cell` was called with `subnode` as the first argument, and then it tried to call `subnode.getAttribute('value')`.
If `col` was `""`, `cell.addElement(text.P(text=str(col), stylename=style))` creates a `<text:P>` element with empty text.
When importing:
`cell` (TableCell) has a child `subnode` (text:P).
`read_cell(subnode, value_type)` is called.
`subnode` (text:P) has no child nodes (usually text is in `.data` or further nested, but let's see).
Actually, if it's `text.P(text="")`, maybe it has no child nodes.
Then it goes to `if not cell.childNodes:` (where `cell` is now the `subnode` text:P).
It tries `getattr(cell, 'data', None)`.
If that's `None`, it tries `cell.getAttribute('value')`.
And `text:P` does not have a `value` attribute, so `odfpy` raises `ValueError`.
We should avoid calling `getAttribute('value')` on elements that don't support it, or check if the element is indeed a `TableCell`.
Wait, `read_cell` is designed to be recursive. It's called on the `TableCell` initially, and then potentially on its children.
If it's a `TableCell`, it might have a `value` attribute (e.g. for floats).
If it's a `text:P`, it should use `data` or some other way to get the text.
Actually, if `cell.childNodes` is empty, we are trying to get the value.
If the `cell` passed to `read_cell` is not a `TableCell`, should we be calling `getAttribute('value')` on it?
In `import_sheet`:
```python
row_vals = [cls.read_cell(cell) for cell in row.childNodes if is_real_cell(cell)]
```
Here `cell` is guaranteed to be a `TableCell` (or something similar in the ODS row).
Then `read_cell` does:
```python
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
if value:
return value
```
It's recursively calling `read_cell` on the children. The children of a `TableCell` are usually `text:P` etc.
If `subnode` is a `text:P`, and it has no children, we reach:
```python
if not cell.childNodes:
value = getattr(cell, 'data', None)
if value is None:
value = cell.getAttribute('value')
```
Here `cell` is the `subnode` (text:P). `text:P` doesn't have a `value` attribute.
The problem is that `if value:` is used to decide whether to return the result of the recursive call. If the result is `""`, it's falsy, so it continues and eventually returns `None` (or keeps looking).
But if the recursive call *crashed* because it tried to call `getAttribute('value')` on a `text:P` element, then we have a problem.
Why does it call `getAttribute('value')` on a `text:P` element? Because `text:P` has no child nodes and no `.data` attribute (maybe?).
Wait, if `text.P(text="")` was created, maybe `data` is `None` or empty.
Let's see what happens if we change:
```python
if value is None:
value = cell.getAttribute('value')
```
to something more safe.
But first, let's check what `cell` is when it crashes.
I'll add a print to `src/tablib/formats/_ods.py`.
TOOL CALL · edit_file
{
"filepath": "src/tablib/formats/_ods.py",
"new_string": " if value is None:\n try:\n value = cell.getAttribute('value')\n except ValueError:\n value = None",
"old_string": " if value is None:\n value = cell.getAttribute('value')"
}Result of edit_file 643 characters
{
"status": "ok",
"filepath": "src/tablib/formats/_ods.py",
"occurrences": 1,
"strategy": "exact",
"diff": "--- a/src/tablib/formats/_ods.py\n+++ b/src/tablib/formats/_ods.py\n@@ -155,7 +155,10 @@\n if not cell.childNodes:\n value = getattr(cell, 'data', None)\n if value is None:\n- value = cell.getAttribute('value')\n+ try:\n+ value = cell.getAttribute('value')\n+ except ValueError:\n+ value = None\n if value is None:\n return ''\n if value_type == 'float':\n",
"is_truncated": false
}Turn 6at 163 s130 tokens out8,970 prompt tokens
Now let's run the reproduction.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport tablib\ntry:\n book = tablib.Databook()\n book.load(\n tablib.Databook(sets=[tablib.Dataset((\"\",))]).export(\"ods\"),\n format=\"ods\",\n )\n print(\"Success\")\n print(f\"Dataset content: {book._datasets[0]}\")\nexcept Exception as e:\n import traceback\n traceback.print_exc()\nPY\n"
}Result of run_command 98 characters
{
"status": "ok",
"stdout": "Success\nDataset content: None\n----\n",
"stderr": "",
"exit_code": 0
}Turn 7at 172 s167 tokens out9,149 prompt tokens
Wait, "Dataset content: None" is not what I expected. `book._datasets[0]` should be the dataset. Ah, `Databook`'s `__str__` or `__repr__` might be weird. Let's check the content.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport tablib\nbook = tablib.Databook()\nbook.load(\n tablib.Databook(sets=[tablib.Dataset((\"\",))]).export(\"ods\"),\n format=\"ods\",\n)\ndset = book._datasets[0]\nprint(f\"Headers: {dset.headers}\")\nprint(f\"Rows: {list(dset)}\")\nPY\n"
}Result of run_command 87 characters
{
"status": "ok",
"stdout": "Headers: [None]\nRows: []\n",
"stderr": "",
"exit_code": 0
}Turn 8at 191 s268 tokens out9,365 prompt tokens
Wait, the rows are empty! `Rows: []`.
But the original dataset had one row: `[("",)]`.
Actually, the original dataset had no headers, so `("",)` is the first row.
If `headers=True` (default), then `("",)` becomes the header.
And there are no data rows.
Let's check with a dataset that has headers and then a row with an empty string.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport tablib\nds = tablib.Dataset(headers=[\"col1\"])\nds.append(\"\") # This might be tricky, Dataset.append expects a sequence.\n# Let's use:\nds = tablib.Dataset(headers=[\"col1\"])\nds.append([\"\"])\n\nbook = tablib.Databook(sets=[ds])\nexported = book.export(\"ods\")\n\nbook_load = tablib.Databook()\nbook_load.load(exported, format=\"ods\")\ndset_load = book_load._datasets[0]\nprint(f\"Headers: {dset_load.headers}\")\nprint(f\"Rows: {list(dset_load)}\")\nPY\n"
}Result of run_command 96 characters
{
"status": "ok",
"stdout": "Headers: ['col1']\nRows: [(None,)]\n",
"stderr": "",
"exit_code": 0
}Turn 9at 225 s523 tokens out9,687 prompt tokens
`Rows: [(None,)]`. It should be `[('',)]` or `[(None,)]` depending on how tablib handles empty strings. But wait, the original was `[""]`.
In `read_cell`:
```python
if not cell.childNodes:
value = getattr(cell, 'data', None)
if value is None:
try:
value = cell.getAttribute('value')
except ValueError:
value = None
if value is None:
return ''
```
If `value` is `None`, it returns `''`.
Wait, let's look at the recursive part:
```python
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
if value:
return value
```
If `value` is `''`, then `if value:` is False!
So if a cell contains an empty string, the recursive call returns `''`, and the loop continues.
If there are no other subnodes, the function reaches the end and returns `None` implicitly.
And if `read_cell` returns `None`, `import_sheet` does:
```python
row_vals = [cls.read_cell(cell) for cell in row.childNodes if is_real_cell(cell)]
```
So `row_vals` will contain `None` for cells that were empty strings.
Wait, tablib `Dataset` might convert `None` to something else or keep it.
If I use `None` in the original dataset, does it work?
The problem statement says: "If the empty string is replaced with `None` the problem does not occur."
Let's test that.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport tablib\nds = tablib.Dataset(headers=[\"col1\"])\nds.append([None])\n\nbook = tablib.Databook(sets=[ds])\nexported = book.export(\"ods\")\n\nbook_load = tablib.Databook()\nbook_load.load(exported, format=\"ods\")\ndset_load = book_load._datasets[0]\nprint(f\"Headers: {dset_load.headers}\")\nprint(f\"Rows: {list(dset_load)}\")\nPY\n"
}Result of run_command 94 characters
{
"status": "ok",
"stdout": "Headers: ['col1']\nRows: [('',)]\n",
"stderr": "",
"exit_code": 0
}Turn 10at 239 s219 tokens out10,263 prompt tokens
Interesting! When I put `None`, I get `''` back. When I put `''`, I get `None` back (or rather, `(None,)` in the rows).
Wait, tablib's `Dataset` representation of rows can be a bit confusing.
Let's see what `Tablib` does.
If I have `ds.append([""])`, then `list(ds)` should be `[('',)]`.
If I have `ds.append([None])`, then `list(ds)` should be `[(None,)]`.
Wait, let me check.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport tablib\nds1 = tablib.Dataset()\nds1.append([\"\"])\nprint(f\"ds1: {list(ds1)}\")\n\nds2 = tablib.Dataset()\nds2.append([None])\nprint(f\"ds2: {list(ds2)}\")\nPY\n"
}Result of run_command 90 characters
{
"status": "ok",
"stdout": "ds1: [('',)]\nds2: [(None,)]\n",
"stderr": "",
"exit_code": 0
}Turn 11at 272 s608 tokens out10,536 prompt tokens
Okay, so `ds1` has `''` and `ds2` has `None`.
Now let's see what happens after round-trip for each.
Case 1: `""`
Round-trip: `""` -> ODS -> `None`
Case 2: `None`
Round-trip: `None` -> ODS -> `""`
Wait, this means `read_cell` is returning `None` when it should be returning `""`.
Look at the code again:
```python
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
if value:
return value
```
If `value` is `''`, it's falsy, so it's ignored!
It should be `if value is not None:`.
Let's test this hypothesis.
Wait, if I change `if value:` to `if value is not None:`, let's see what happens.
But there's another thing. In `read_cell`, when `not cell.childNodes`:
```python
if not cell.childNodes:
value = getattr(cell, 'data', None)
if value is None:
try:
value = cell.getAttribute('value')
except ValueError:
value = None
if value is None:
return ''
```
It returns `''` if no value is found.
So if `subnode` (e.g. `text:P`) has no child nodes and no data, it returns `''`.
Then back in the loop:
```python
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
if value:
return value
```
`value` is `''`, so `if value:` is False. The loop continues. If no other subnode has a truthy value, the function returns `None` (implicitly).
So changing `if value:` to `if value is not None:` should fix it.
Let's verify this. I'll apply both the `try-except` on `getAttribute` AND the `is not None` check.
Wait, the `try-except` on `getAttribute` was a fix for the crash. Now let's fix the logic.
Turn 12at 272 s
<|tool_call>call edit_file{filepath:<|"|>src/tablib/formats/_ods.py<|"|>,new_string:<|"|> value = cls.read_cell(subnode, value_type)
if value is not None:
return value<|"|>,old_string:<|"|> value = cls.read_cell(subnode, value_type)
if value:
return value<|"|>}<tool_call|>
System instructions 286 characters
Your previous response reached the token limit before the tool call finished closing (<|tool_call|> was cut off). Do NOT repeat your prior reasoning in thought—emit your next tool call immediately, and if calling edit_file or write_file, split the change into smaller incremental edits.
Turn 13at 279 s95 tokens out7,842 prompt tokens
TOOL CALL · edit_file
{
"filepath": "src/tablib/formats/_ods.py",
"new_string": " value = cls.read_cell(subnode, value_type)\n if value is not None:\n return value",
"old_string": " value = cls.read_cell(subnode, value_type)\n if value:\n return value"
}Result of edit_file 436 characters
{
"status": "ok",
"filepath": "src/tablib/formats/_ods.py",
"occurrences": 1,
"strategy": "exact",
"diff": "--- a/src/tablib/formats/_ods.py\n+++ b/src/tablib/formats/_ods.py\n@@ -169,7 +169,7 @@\n \n for subnode in cell.childNodes:\n value = cls.read_cell(subnode, value_type)\n- if value:\n+ if value is not None:\n return value\n \n @classmethod\n",
"is_truncated": false
}Turn 14at 312 s540 tokens out8,096 prompt tokens
The previous `edit_file` changed `if value:` to `if value is not None:`.
Now let's verify if the empty string is correctly preserved.
Reproduction case 1: `tablib.Dataset(("",))`
In ODS export:
`elif col is None: cell = table.TableCell(valuetype="void")`
`else: cell = table.TableCell(valuetype="string"); cell.addElement(text.P(text=str(col), ...))`
So `""` becomes a cell with `valuetype="string"` and a child node `text.P(text="")`.
In ODS import `read_cell`:
1. `value_type = cell.getAttribute('valuetype')` (which is 'string')
2. `if not cell.childNodes:` is False because there is a `text.P` child node.
3. `for subnode in cell.childNodes:` loop starts.
4. `value = cls.read_cell(subnode, 'string')`
5. Inside the recursive call for `subnode` (`text.P`):
`value_type` is 'string'.
`if not subnode.childNodes:` depends on whether `text.P` has children (usually it has text content).
Actually, `odfpy` nodes for text usually store text in `.data`.
`value = getattr(subnode, 'data', None)` will likely be `""`.
`if value is None:` will be False.
The function will return `value` (which is `""`).
6. Back in the caller loop:
`if value is not None:` is True for `value=""`.
It returns `""`.
This looks correct now. Let's test.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport tablib\nds = tablib.Dataset(headers=[\"col1\"])\nds.append([\"\"])\n\nbook = tablib.Databook(sets=[ds])\nexported = book.export(\"ods\")\n\nbook_load = tablib.Databook()\nbook_load.load(exported, format=\"ods\")\ndset_load = book_load._datasets[0]\nprint(f\"Headers: {dset_load.headers}\")\nprint(f\"Rows: {list(dset_load)}\")\nassert list(dset_load) == [('',)]\nPY\n"
}Result of run_command 94 characters
{
"status": "ok",
"stdout": "Headers: ['col1']\nRows: [('',)]\n",
"stderr": "",
"exit_code": 0
}Turn 15at 346 s444 tokens out8,690 prompt tokens
Now let's check the case with `None`.
In ODS export: `col is None` -> `table.TableCell(valuetype="void")`.
In ODS import `read_cell`:
1. `value_type` is 'void'.
2. `cell.childNodes` is empty for `valuetype="void"`.
3. `if not cell.childNodes:` is True.
4. `value = getattr(cell, 'data', None)` is None.
5. `value = cell.getAttribute('value')`. For `valuetype="void"`, the 'value' attribute might not exist, triggering the `ValueError` that I just fixed.
6. My fix catches `ValueError` and sets `value = None`.
7. `if value is None: return ''`.
So `None` becomes `''` (empty string).
Wait, if `col is None` in Dataset, it becomes `''` after ODS roundtrip.
If `col == ""` in Dataset, it becomes `''` after ODS roundtrip.
Is this acceptable?
The issue statement says: "If the empty string is replaced with None the problem does not occur."
It didn't explicitly say they must be distinguished.
However, Tablib usually tries to preserve types where possible.
But ODS format (and `odfpy`) might not distinguish between empty string and null values in a simple way.
Let's check what happens with `None` again.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport tablib\nds = tablib.Dataset(headers=[\"col1\"])\nds.append([None])\n\nbook = tablib.Databook(sets=[ds])\nexported = book.export(\"ods\")\n\nbook_load = tablib.Databook()\nbook_load.load(exported, format=\"ods\")\ndset_load = book_load._datasets[0]\nprint(f\"Rows: {list(dset_load)}\")\nPY\n"
}Result of run_command 75 characters
{
"status": "ok",
"stdout": "Rows: [('',)]\n",
"stderr": "",
"exit_code": 0
}Turn 16at 355 s150 tokens out9,179 prompt tokens
Okay, so `None` becomes `''`. Let's check if `Dataset(("",))` also becomes `('',)`.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport tablib\nds = tablib.Dataset(headers=[\"col1\"])\nds.append([\"\"])\n\nbook = tablib.Databook(sets=[ds])\nexported = book.export(\"ods\")\n\nbook_load = tablib.Databook()\nbook_load.load(exported, format=\"ods\")\ndset_load = book_load._datasets[0]\nprint(f\"Rows: {list(dset_load)}\")\nPY\n"
}Result of run_command 75 characters
{
"status": "ok",
"stdout": "Rows: [('',)]\n",
"stderr": "",
"exit_code": 0
}Turn 17at 368 s312 tokens out9,374 prompt tokens
Both `None` and `""` result in `""`.
Is this what the user wanted?
"When saving data containing the empty string to ODS format, the resulting ODS file is not loadable by tablib."
The goal was to make it "loadable".
One more thing: the reproduction code provided:
```python
book = tablib.Databook()
book.load(
tablib.Databook(sets=[tablib.Dataset(("",))]).export("ods"),
format="ods",
)
```
This creates a Dataset with no headers (by default `Dataset(("",))` has no headers if not specified) and one row `("",)`.
Wait, `Dataset(("",))` is initialization with data.
Let's run the EXACT reproduction code.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport tablib\ntry:\n book = tablib.Databook()\n book.load(\n tablib.Databook(sets=[tablib.Dataset((\"\",))]).export(\"ods\"),\n format=\"ods\",\n )\n print(\"Success\")\n print(f\"Book datasets: {len(book._datasets)}\")\n print(f\"First dataset rows: {list(book._datasets[0])}\")\nexcept Exception as e:\n import traceback\n traceback.print_exc()\nPY\n"
}Result of run_command 111 characters
{
"status": "ok",
"stdout": "Success\nBook datasets: 1\nFirst dataset rows: []\n",
"stderr": "",
"exit_code": 0
}Turn 18at 391 s405 tokens out9,741 prompt tokens
Wait, `First dataset rows: []`?
Why is it empty?
Ah, look at `import_sheet` in `_ods.py`:
```python
for i, row in enumerate(sheet.childNodes):
if row.tagName != 'table:table-row':
continue
if i < skip_lines:
continue
row_vals = [cls.read_cell(cell) for cell in row.childNodes if is_real_cell(cell)]
if not row_vals:
continue
if i == skip_lines and headers:
dset.headers = row_vals
else:
if i > skip_lines and len(row_vals) < dset.width:
row_vals += [''] * (dset.width - len(row_vals))
dset.append(row_vals)
```
`headers` defaults to `True` in `import_book` (which is called by `load`).
When `Dataset(("",))` is exported as ODS:
It has no headers. So the first row of data `("",)` is treated as the header row during import.
Thus `dset.headers = [('',)]` (or `[None]` if it's void) and no rows are appended.
That's why `list(book._datasets[0])` is `[]`.
Let's check headers.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport tablib\nbook = tablib.Databook()\nbook.load(\n tablib.Databook(sets=[tablib.Dataset((\"\",))]).export(\"ods\"),\n format=\"ods\",\n)\nprint(f\"Headers: {book._datasets[0].headers}\")\nPY\n"
}Result of run_command 75 characters
{
"status": "ok",
"stdout": "Headers: ['']\n",
"stderr": "",
"exit_code": 0
}Turn 19at 414 s360 tokens out10,190 prompt tokens
Okay, so it's working correctly (it doesn't crash, and it loads the data, albeit into headers because of the default `headers=True`).
I've fixed the `ValueError` and ensured `None` as a return value from `read_cell`'s recursive call is handled so that empty strings are preserved.
Final check on the `ValueError` fix:
```python
if value is None:
try:
value = cell.getAttribute('value')
except ValueError:
value = None
```
This is specifically for cases where `cell` (which is a `TableCell` or similar) does not have a `value` attribute in the `odfpy` sense (i.e., it's not in `allowed_args`).
For `valuetype="void"`, it likely has no `value` attribute.
Now, I should verify that I didn't break other types like floats or dates.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport tablib\nimport datetime as dt\nds = tablib.Dataset(headers=[\"float\", \"date\", \"string\"])\nds.append([1.23, dt.date(2023, 1, 1), \"hello\"])\n\nbook = tablib.Databook(sets=[ds])\nexported = book.export(\"ods\")\n\nbook_load = tablib.Databook()\nbook_load.load(exported, format=\"ods\")\ndset_load = book_load._datasets[0]\nprint(f\"Rows: {list(dset_load)}\")\nPY\n"
}Result of run_command 112 characters
{
"status": "ok",
"stdout": "Rows: [(1.23, datetime.date(2023, 1, 1), 'hello')]\n",
"stderr": "",
"exit_code": 0
}Turn 20at 418 s68 tokens out10,616 prompt tokens
Everything looks good. I will now remove any temporary files if I created any (I didn't, I used `python3 - <<'PY'`). Actually, I should check if I have any untracked files.
TOOL CALL · run_command
{
"command": "git status --short"
}Result of run_command 91 characters
{
"status": "ok",
"stdout": " M src/tablib/formats/_ods.py\n",
"stderr": "",
"exit_code": 0
}Model calls (not matched to turns)
Generated tokens 163 tokens · stopped: STOP
The user is reporting a `ValueError: 'value' is not in list` when loading an ODS file that was exported from a `tablib.Dataset` containing an empty string.
Example:
```python
book = tablib.Databook()
book.load(
tablib.Databook(sets=[tablib.Dataset(("",))]).export("ods"),
format="ods",
)
```
I need to investigate the ODS export and import logic in `tablib`.
First, I'll locate the ODS implementation in the codebase.<|channel>thought
The user is reporting a `ValueError: 'value' is not in list` when loading an ODS file that was exported from a `tablib.Dataset` containing an empty string.
Example:
```python
book = tablib.Databook()
book.load(
tablib.Databook(sets=[tablib.Dataset(("",))]).export("ods"),
format="ods",
)
```
I need to investigate the ODS export and import logic in `tablib`.
First, I'll locate the ODS implementation in the codebase.<channel|><|tool_call>call:run_command{command:<|"|>grep -rn --include="*.py" "ods" src/tablib | grep -v "tests"<|"|>}<tool_call|><|tool_response>
Generated tokens 135 tokens · stopped: STOP
The ODS format logic seems to be in `src/tablib/formats/_ods.py`. Now I'll reproduce the issue.
The ODS format logic seems to be in `src/tablib/formats/_ods.py`.
Now I'll reproduce the issue.
<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import tablib
try:
book = tablib.Databook()
book.load(
tablib.Databook(sets=[tablib.Dataset(("",))]).export("ods"),
format="ods",
)
print("Success")
except Exception as e:
import traceback
traceback.print_exc()
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 108 tokens · stopped: STOP
Okay, I reproduced it. The error comes from `odf/element.py:547` when calling `cell.getAttribute('value')`.
The traceback points to `src/tablib/formats/_ods.py`, lines 168, 158, 121.
Let's examine `src/tablib/formats/_ods.py`.
Okay, I reproduced it. The error comes from `odf/element.py:547` when calling `cell.getAttribute('value')`.
The traceback points to `src/tablib/formats/_ods.py`, lines 168, 158, 121.
Let's examine `src/tablib/formats/_ods.py`.
<channel|><|tool_call>call:read_file{filepath:<|"|>src/tablib/formats/_ods.py<|"|>}<tool_call|><|tool_response>
Generated tokens 53 tokens · stopped: STOP
I need to read the rest of `src/tablib/formats/_ods.py`.
I need to read the rest of `src/tablib/formats/_ods.py`.
<channel|><|tool_call>call:read_file{filepath:<|"|>src/tablib/formats/_ods.py<|"|>,start_line:151}<tool_call|><|tool_response>
Generated tokens 1,964 tokens · stopped: STOP
Let's trace the failure.
In `import_sheet`:
```python
for i, row in enumerate(sheet.childNodes):
# ...
row_vals = [cls.read_cell(cell) for cell in row.childNodes if is_real_cell(cell)]
```
In `read_cell`:
```python
@classmethod
def read_cell(cls, cell, value_type=None):
def convert_date(val):
# ...
if value_type is None:
value_type = cell.getAttribute('valuetype')
# ...
if not cell.childNodes:
value = getattr(cell, 'data', None)
if value is None:
value = cell.getAttribute('value') # <--- This is where it fails!
if value is None:
return ''
# ...
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
if value:
return value
```
The error is `ValueError: 'value' is not in list` which comes from `odf/element.py:547` in `getAttribute`.
Looking at `odfpy` (which is what `odf` is), `getAttribute` probably checks if the attribute being requested is allowed for that element type.
If `cell` is a `TableCell`, let's see what attributes it has.
Wait, look at the code:
```python
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
if value:
return value
```
If `cell` has child nodes, it iterates through them and calls `read_cell` recursively.
If the cell was exported as:
```python
else:
cell = table.TableCell(valuetype="string")
cell.addElement(text.P(text=str(col), stylename=style))
```
And `col` was `""` (empty string), then `text.P(text="")`.
When importing:
1. `read_cell(cell)` is called. `cell` is the `TableCell`.
2. `cell.childNodes` will contain the `text.P` element.
3. `read_cell` iterates through `cell.childNodes`.
4. `read_cell(subnode, value_type)` is called where `subnode` is the `text.P` element.
5. In the recursive call:
- `subnode.childNodes` might be empty (if it's just a `P` element with text).
- If `subnode.childNodes` is empty:
- `value = getattr(subnode, 'data', None)`
- If `value` is `None`:
- `value = subnode.getAttribute('value')` <--- This is probably where the crash happens! Because `text.P` (a paragraph) likely doesn't have a `value` attribute.
Let's verify what `subnode` is.
In `read_cell`:
```python
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
if value:
return value
```
If `value` is `""` (empty string), `if value:` is False, so it continues.
If all subnodes return `""` or `None`, `read_cell` finally returns `None` (implicitly).
But wait, the traceback says:
```
File "/tablib/src/tablib/formats/_ods.py", line 168, in read_cell
value = cls.read_cell(subnode, value_type)
File "/tablib/src/tablib/formats/_ods.py", line 158, in read_cell
value = cell.getAttribute('value')
File "/usr/local/lib/python3.10/site-packages/odf/element.py", line 547, in getAttribute
i = allowed_args.index(attr)
ValueError: 'value' is not in list
```
Line 168: `value = cls.read_cell(subnode, value_type)`
Line 158: `value = cell.getAttribute('value')`
So it's exactly as I thought. `read_cell` was called with `subnode` as the first argument, and then it tried to call `subnode.getAttribute('value')`.
If `col` was `""`, `cell.addElement(text.P(text=str(col), stylename=style))` creates a `<text:P>` element with empty text.
When importing:
`cell` (TableCell) has a child `subnode` (text:P).
`read_cell(subnode, value_type)` is called.
`subnode` (text:P) has no child nodes (usually text is in `.data` or further nested, but let's see).
Actually, if it's `text.P(text="")`, maybe it has no child nodes.
Then it goes to `if not cell.childNodes:` (where `cell` is now the `subnode` text:P).
It tries `getattr(cell, 'data', None)`.
If that's `None`, it tries `cell.getAttribute('value')`.
And `text:P` does not have a `value` attribute, so `odfpy` raises `ValueError`.
We should avoid calling `getAttribute('value')` on elements that don't support it, or check if the element is indeed a `TableCell`.
Wait, `read_cell` is designed to be recursive. It's called on the `TableCell` initially, and then potentially on its children.
If it's a `TableCell`, it might have a `value` attribute (e.g. for floats).
If it's a `text:P`, it should use `data` or some other way to get the text.
Actually, if `cell.childNodes` is empty, we are trying to get the value.
If the `cell` passed to `read_cell` is not a `TableCell`, should we be calling `getAttribute('value')` on it?
In `import_sheet`:
```python
row_vals = [cls.read_cell(cell) for cell in row.childNodes if is_real_cell(cell)]
```
Here `cell` is guaranteed to be a `TableCell` (or something similar in the ODS row).
Then `read_cell` does:
```python
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
if value:
return value
```
It's recursively calling `read_cell` on the children. The children of a `TableCell` are usually `text:P` etc.
If `subnode` is a `text:P`, and it has no children, we reach:
```python
if not cell.childNodes:
value = getattr(cell, 'data', None)
if value is None:
value = cell.getAttribute('value')
```
Here `cell` is the `subnode` (text:P). `text:P` doesn't have a `value` attribute.
The problem is that `if value:` is used to decide whether to return the result of the recursive call. If the result is `""`, it's falsy, so it continues and eventually returns `None` (or keeps looking).
But if the recursive call *crashed* because it tried to call `getAttribute('value')` on a `text:P` element, then we have a problem.
Why does it call `getAttribute('value')` on a `text:P` element? Because `text:P` has no child nodes and no `.data` attribute (maybe?).
Wait, if `text.P(text="")` was created, maybe `data` is `None` or empty.
Let's see what happens if we change:
```python
if value is None:
value = cell.getAttribute('value')
```
to something more safe.
But first, let's check what `cell` is when it crashes.
I'll add a print to `src/tablib/formats/_ods.py`.
Let's trace the failure.
In `import_sheet`:
```python
for i, row in enumerate(sheet.childNodes):
# ...
row_vals = [cls.read_cell(cell) for cell in row.childNodes if is_real_cell(cell)]
```
In `read_cell`:
```python
@classmethod
def read_cell(cls, cell, value_type=None):
def convert_date(val):
# ...
if value_type is None:
value_type = cell.getAttribute('valuetype')
# ...
if not cell.childNodes:
value = getattr(cell, 'data', None)
if value is None:
value = cell.getAttribute('value') # <--- This is where it fails!
if value is None:
return ''
# ...
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
if value:
return value
```
The error is `ValueError: 'value' is not in list` which comes from `odf/element.py:547` in `getAttribute`.
Looking at `odfpy` (which is what `odf` is), `getAttribute` probably checks if the attribute being requested is allowed for that element type.
If `cell` is a `TableCell`, let's see what attributes it has.
Wait, look at the code:
```python
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
if value:
return value
```
If `cell` has child nodes, it iterates through them and calls `read_cell` recursively.
If the cell was exported as:
```python
else:
cell = table.TableCell(valuetype="string")
cell.addElement(text.P(text=str(col), stylename=style))
```
And `col` was `""` (empty string), then `text.P(text="")`.
When importing:
1. `read_cell(cell)` is called. `cell` is the `TableCell`.
2. `cell.childNodes` will contain the `text.P` element.
3. `read_cell` iterates through `cell.childNodes`.
4. `read_cell(subnode, value_type)` is called where `subnode` is the `text.P` element.
5. In the recursive call:
- `subnode.childNodes` might be empty (if it's just a `P` element with text).
- If `subnode.childNodes` is empty:
- `value = getattr(subnode, 'data', None)`
- If `value` is `None`:
- `value = subnode.getAttribute('value')` <--- This is probably where the crash happens! Because `text.P` (a paragraph) likely doesn't have a `value` attribute.
Let's verify what `subnode` is.
In `read_cell`:
```python
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
if value:
return value
```
If `value` is `""` (empty string), `if value:` is False, so it continues.
If all subnodes return `""` or `None`, `read_cell` finally returns `None` (implicitly).
But wait, the traceback says:
```
File "/tablib/src/tablib/formats/_ods.py", line 168, in read_cell
value = cls.read_cell(subnode, value_type)
File "/tablib/src/tablib/formats/_ods.py", line 158, in read_cell
value = cell.getAttribute('value')
File "/usr/local/lib/python3.10/site-packages/odf/element.py", line 547, in getAttribute
i = allowed_args.index(attr)
ValueError: 'value' is not in list
```
Line 168: `value = cls.read_cell(subnode, value_type)`
Line 158: `value = cell.getAttribute('value')`
So it's exactly as I thought. `read_cell` was called with `subnode` as the first argument, and then it tried to call `subnode.getAttribute('value')`.
If `col` was `""`, `cell.addElement(text.P(text=str(col), stylename=style))` creates a `<text:P>` element with empty text.
When importing:
`cell` (TableCell) has a child `subnode` (text:P).
`read_cell(subnode, value_type)` is called.
`subnode` (text:P) has no child nodes (usually text is in `.data` or further nested, but let's see).
Actually, if it's `text.P(text="")`, maybe it has no child nodes.
Then it goes to `if not cell.childNodes:` (where `cell` is now the `subnode` text:P).
It tries `getattr(cell, 'data', None)`.
If that's `None`, it tries `cell.getAttribute('value')`.
And `text:P` does not have a `value` attribute, so `odfpy` raises `ValueError`.
We should avoid calling `getAttribute('value')` on elements that don't support it, or check if the element is indeed a `TableCell`.
Wait, `read_cell` is designed to be recursive. It's called on the `TableCell` initially, and then potentially on its children.
If it's a `TableCell`, it might have a `value` attribute (e.g. for floats).
If it's a `text:P`, it should use `data` or some other way to get the text.
Actually, if `cell.childNodes` is empty, we are trying to get the value.
If the `cell` passed to `read_cell` is not a `TableCell`, should we be calling `getAttribute('value')` on it?
In `import_sheet`:
```python
row_vals = [cls.read_cell(cell) for cell in row.childNodes if is_real_cell(cell)]
```
Here `cell` is guaranteed to be a `TableCell` (or something similar in the ODS row).
Then `read_cell` does:
```python
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
if value:
return value
```
It's recursively calling `read_cell` on the children. The children of a `TableCell` are usually `text:P` etc.
If `subnode` is a `text:P`, and it has no children, we reach:
```python
if not cell.childNodes:
value = getattr(cell, 'data', None)
if value is None:
value = cell.getAttribute('value')
```
Here `cell` is the `subnode` (text:P). `text:P` doesn't have a `value` attribute.
The problem is that `if value:` is used to decide whether to return the result of the recursive call. If the result is `""`, it's falsy, so it continues and eventually returns `None` (or keeps looking).
But if the recursive call *crashed* because it tried to call `getAttribute('value')` on a `text:P` element, then we have a problem.
Why does it call `getAttribute('value')` on a `text:P` element? Because `text:P` has no child nodes and no `.data` attribute (maybe?).
Wait, if `text.P(text="")` was created, maybe `data` is `None` or empty.
Let's see what happens if we change:
```python
if value is None:
value = cell.getAttribute('value')
```
to something more safe.
But first, let's check what `cell` is when it crashes.
I'll add a print to `src/tablib/formats/_ods.py`.
<channel|><|tool_call>call:edit_file{filepath:<|"|>src/tablib/formats/_ods.py<|"|>,new_string:<|"|> if value is None:
try:
value = cell.getAttribute('value')
except ValueError:
value = None<|"|>,old_string:<|"|> if value is None:
value = cell.getAttribute('value')<|"|>}<tool_call|><|tool_response>
Generated tokens 130 tokens · stopped: STOP
Now let's run the reproduction.
Now let's run the reproduction.
<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import tablib
try:
book = tablib.Databook()
book.load(
tablib.Databook(sets=[tablib.Dataset(("",))]).export("ods"),
format="ods",
)
print("Success")
print(f"Dataset content: {book._datasets[0]}")
except Exception as e:
import traceback
traceback.print_exc()
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 167 tokens · stopped: STOP
Wait, "Dataset content: None" is not what I expected. `book._datasets[0]` should be the dataset. Ah, `Databook`'s `__str__` or `__repr__` might be weird. Let's check the content.
Wait, "Dataset content: None" is not what I expected. `book._datasets[0]` should be the dataset.
Ah, `Databook`'s `__str__` or `__repr__` might be weird. Let's check the content.
<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import tablib
book = tablib.Databook()
book.load(
tablib.Databook(sets=[tablib.Dataset(("",))]).export("ods"),
format="ods",
)
dset = book._datasets[0]
print(f"Headers: {dset.headers}")
print(f"Rows: {list(dset)}")
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 268 tokens · stopped: STOP
Wait, the rows are empty! `Rows: []`.
But the original dataset had one row: `[("",)]`.
Actually, the original dataset had no headers, so `("",)` is the first row.
If `headers=True` (default), then `("",)` becomes the header.
And there are no data rows.
Let's check with a dataset that has headers and then a row with an empty string.
Wait, the rows are empty! `Rows: []`.
But the original dataset had one row: `[("",)]`.
Actually, the original dataset had no headers, so `("",)` is the first row.
If `headers=True` (default), then `("",)` becomes the header.
And there are no data rows.
Let's check with a dataset that has headers and then a row with an empty string.
<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import tablib
ds = tablib.Dataset(headers=["col1"])
ds.append("") # This might be tricky, Dataset.append expects a sequence.
# Let's use:
ds = tablib.Dataset(headers=["col1"])
ds.append([""])
book = tablib.Databook(sets=[ds])
exported = book.export("ods")
book_load = tablib.Databook()
book_load.load(exported, format="ods")
dset_load = book_load._datasets[0]
print(f"Headers: {dset_load.headers}")
print(f"Rows: {list(dset_load)}")
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 523 tokens · stopped: STOP
`Rows: [(None,)]`. It should be `[('',)]` or `[(None,)]` depending on how tablib handles empty strings. But wait, the original was `[""]`.
In `read_cell`:
```python
if not cell.childNodes:
value = getattr(cell, 'data', None)
if value is None:
try:
value = cell.getAttribute('value')
except ValueError:
value = None
if value is None:
return ''
```
If `value` is `None`, it returns `''`.
Wait, let's look at the recursive part:
```python
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
if value:
return value
```
If `value` is `''`, then `if value:` is False!
So if a cell contains an empty string, the recursive call returns `''`, and the loop continues.
If there are no other subnodes, the function reaches the end and returns `None` implicitly.
And if `read_cell` returns `None`, `import_sheet` does:
```python
row_vals = [cls.read_cell(cell) for cell in row.childNodes if is_real_cell(cell)]
```
So `row_vals` will contain `None` for cells that were empty strings.
Wait, tablib `Dataset` might convert `None` to something else or keep it.
If I use `None` in the original dataset, does it work?
The problem statement says: "If the empty string is replaced with `None` the problem does not occur."
Let's test that.
`Rows: [(None,)]`. It should be `[('',)]` or `[(None,)]` depending on how tablib handles empty strings. But wait, the original was `[""]`.
In `read_cell`:
```python
if not cell.childNodes:
value = getattr(cell, 'data', None)
if value is None:
try:
value = cell.getAttribute('value')
except ValueError:
value = None
if value is None:
return ''
```
If `value` is `None`, it returns `''`.
Wait, let's look at the recursive part:
```python
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
if value:
return value
```
If `value` is `''`, then `if value:` is False!
So if a cell contains an empty string, the recursive call returns `''`, and the loop continues.
If there are no other subnodes, the function reaches the end and returns `None` implicitly.
And if `read_cell` returns `None`, `import_sheet` does:
```python
row_vals = [cls.read_cell(cell) for cell in row.childNodes if is_real_cell(cell)]
```
So `row_vals` will contain `None` for cells that were empty strings.
Wait, tablib `Dataset` might convert `None` to something else or keep it.
If I use `None` in the original dataset, does it work?
The problem statement says: "If the empty string is replaced with `None` the problem does not occur."
Let's test that.
<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import tablib
ds = tablib.Dataset(headers=["col1"])
ds.append([None])
book = tablib.Databook(sets=[ds])
exported = book.export("ods")
book_load = tablib.Databook()
book_load.load(exported, format="ods")
dset_load = book_load._datasets[0]
print(f"Headers: {dset_load.headers}")
print(f"Rows: {list(dset_load)}")
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 219 tokens · stopped: STOP
Interesting! When I put `None`, I get `''` back. When I put `''`, I get `None` back (or rather, `(None,)` in the rows).
Wait, tablib's `Dataset` representation of rows can be a bit confusing.
Let's see what `Tablib` does.
If I have `ds.append([""])`, then `list(ds)` should be `[('',)]`.
If I have `ds.append([None])`, then `list(ds)` should be `[(None,)]`.
Wait, let me check.
Interesting! When I put `None`, I get `''` back. When I put `''`, I get `None` back (or rather, `(None,)` in the rows).
Wait, tablib's `Dataset` representation of rows can be a bit confusing.
Let's see what `Tablib` does.
If I have `ds.append([""])`, then `list(ds)` should be `[('',)]`.
If I have `ds.append([None])`, then `list(ds)` should be `[(None,)]`.
Wait, let me check.
<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import tablib
ds1 = tablib.Dataset()
ds1.append([""])
print(f"ds1: {list(ds1)}")
ds2 = tablib.Dataset()
ds2.append([None])
print(f"ds2: {list(ds2)}")
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 608 tokens · stopped: STOP
Okay, so `ds1` has `''` and `ds2` has `None`.
Now let's see what happens after round-trip for each.
Case 1: `""`
Round-trip: `""` -> ODS -> `None`
Case 2: `None`
Round-trip: `None` -> ODS -> `""`
Wait, this means `read_cell` is returning `None` when it should be returning `""`.
Look at the code again:
```python
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
if value:
return value
```
If `value` is `''`, it's falsy, so it's ignored!
It should be `if value is not None:`.
Let's test this hypothesis.
Wait, if I change `if value:` to `if value is not None:`, let's see what happens.
But there's another thing. In `read_cell`, when `not cell.childNodes`:
```python
if not cell.childNodes:
value = getattr(cell, 'data', None)
if value is None:
try:
value = cell.getAttribute('value')
except ValueError:
value = None
if value is None:
return ''
```
It returns `''` if no value is found.
So if `subnode` (e.g. `text:P`) has no child nodes and no data, it returns `''`.
Then back in the loop:
```python
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
if value:
return value
```
`value` is `''`, so `if value:` is False. The loop continues. If no other subnode has a truthy value, the function returns `None` (implicitly).
So changing `if value:` to `if value is not None:` should fix it.
Let's verify this. I'll apply both the `try-except` on `getAttribute` AND the `is not None` check.
Wait, the `try-except` on `getAttribute` was a fix for the crash. Now let's fix the logic.
Okay, so `ds1` has `''` and `ds2` has `None`.
Now let's see what happens after round-trip for each.
Case 1: `""`
Round-trip: `""` -> ODS -> `None`
Case 2: `None`
Round-trip: `None` -> ODS -> `""`
Wait, this means `read_cell` is returning `None` when it should be returning `""`.
Look at the code again:
```python
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
if value:
return value
```
If `value` is `''`, it's falsy, so it's ignored!
It should be `if value is not None:`.
Let's test this hypothesis.
Wait, if I change `if value:` to `if value is not None:`, let's see what happens.
But there's another thing. In `read_cell`, when `not cell.childNodes`:
```python
if not cell.childNodes:
value = getattr(cell, 'data', None)
if value is None:
try:
value = cell.getAttribute('value')
except ValueError:
value = None
if value is None:
return ''
```
It returns `''` if no value is found.
So if `subnode` (e.g. `text:P`) has no child nodes and no data, it returns `''`.
Then back in the loop:
```python
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
if value:
return value
```
`value` is `''`, so `if value:` is False. The loop continues. If no other subnode has a truthy value, the function returns `None` (implicitly).
So changing `if value:` to `if value is not None:` should fix it.
Let's verify this. I'll apply both the `try-except` on `getAttribute` AND the `is not None` check.
Wait, the `try-except` on `getAttribute` was a fix for the crash. Now let's fix the logic.
<channel|><|tool_call>call edit_file{filepath:<|"|>src/tablib/formats/_ods.py<|"|>,new_string:<|"|> value = cls.read_cell(subnode, value_type)
if value is not None:
return value<|"|>,old_string:<|"|> value = cls.read_cell(subnode, value_type)
if value:
return value<|"|>}<tool_call|><|tool_response>
Generated tokens 95 tokens · stopped: STOP
<|channel>thought
<channel|><|tool_call>call:edit_file{filepath:<|"|>src/tablib/formats/_ods.py<|"|>,new_string:<|"|> value = cls.read_cell(subnode, value_type)
if value is not None:
return value<|"|>,old_string:<|"|> value = cls.read_cell(subnode, value_type)
if value:
return value<|"|>}<tool_call|><|tool_response>
Generated tokens 540 tokens · stopped: STOP
The previous `edit_file` changed `if value:` to `if value is not None:`.
Now let's verify if the empty string is correctly preserved.
Reproduction case 1: `tablib.Dataset(("",))`
In ODS export:
`elif col is None: cell = table.TableCell(valuetype="void")`
`else: cell = table.TableCell(valuetype="string"); cell.addElement(text.P(text=str(col), ...))`
So `""` becomes a cell with `valuetype="string"` and a child node `text.P(text="")`.
In ODS import `read_cell`:
1. `value_type = cell.getAttribute('valuetype')` (which is 'string')
2. `if not cell.childNodes:` is False because there is a `text.P` child node.
3. `for subnode in cell.childNodes:` loop starts.
4. `value = cls.read_cell(subnode, 'string')`
5. Inside the recursive call for `subnode` (`text.P`):
`value_type` is 'string'.
`if not subnode.childNodes:` depends on whether `text.P` has children (usually it has text content).
Actually, `odfpy` nodes for text usually store text in `.data`.
`value = getattr(subnode, 'data', None)` will likely be `""`.
`if value is None:` will be False.
The function will return `value` (which is `""`).
6. Back in the caller loop:
`if value is not None:` is True for `value=""`.
It returns `""`.
This looks correct now. Let's test.The previous `edit_file` changed `if value:` to `if value is not None:`.
Now let's verify if the empty string is correctly preserved.
Reproduction case 1: `tablib.Dataset(("",))`
In ODS export:
`elif col is None: cell = table.TableCell(valuetype="void")`
`else: cell = table.TableCell(valuetype="string"); cell.addElement(text.P(text=str(col), ...))`
So `""` becomes a cell with `valuetype="string"` and a child node `text.P(text="")`.
In ODS import `read_cell`:
1. `value_type = cell.getAttribute('valuetype')` (which is 'string')
2. `if not cell.childNodes:` is False because there is a `text.P` child node.
3. `for subnode in cell.childNodes:` loop starts.
4. `value = cls.read_cell(subnode, 'string')`
5. Inside the recursive call for `subnode` (`text.P`):
`value_type` is 'string'.
`if not subnode.childNodes:` depends on whether `text.P` has children (usually it has text content).
Actually, `odfpy` nodes for text usually store text in `.data`.
`value = getattr(subnode, 'data', None)` will likely be `""`.
`if value is None:` will be False.
The function will return `value` (which is `""`).
6. Back in the caller loop:
`if value is not None:` is True for `value=""`.
It returns `""`.
This looks correct now. Let's test.<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import tablib
ds = tablib.Dataset(headers=["col1"])
ds.append([""])
book = tablib.Databook(sets=[ds])
exported = book.export("ods")
book_load = tablib.Databook()
book_load.load(exported, format="ods")
dset_load = book_load._datasets[0]
print(f"Headers: {dset_load.headers}")
print(f"Rows: {list(dset_load)}")
assert list(dset_load) == [('',)]
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 444 tokens · stopped: STOP
Now let's check the case with `None`.
In ODS export: `col is None` -> `table.TableCell(valuetype="void")`.
In ODS import `read_cell`:
1. `value_type` is 'void'.
2. `cell.childNodes` is empty for `valuetype="void"`.
3. `if not cell.childNodes:` is True.
4. `value = getattr(cell, 'data', None)` is None.
5. `value = cell.getAttribute('value')`. For `valuetype="void"`, the 'value' attribute might not exist, triggering the `ValueError` that I just fixed.
6. My fix catches `ValueError` and sets `value = None`.
7. `if value is None: return ''`.
So `None` becomes `''` (empty string).
Wait, if `col is None` in Dataset, it becomes `''` after ODS roundtrip.
If `col == ""` in Dataset, it becomes `''` after ODS roundtrip.
Is this acceptable?
The issue statement says: "If the empty string is replaced with None the problem does not occur."
It didn't explicitly say they must be distinguished.
However, Tablib usually tries to preserve types where possible.
But ODS format (and `odfpy`) might not distinguish between empty string and null values in a simple way.
Let's check what happens with `None` again.
Now let's check the case with `None`.
In ODS export: `col is None` -> `table.TableCell(valuetype="void")`.
In ODS import `read_cell`:
1. `value_type` is 'void'.
2. `cell.childNodes` is empty for `valuetype="void"`.
3. `if not cell.childNodes:` is True.
4. `value = getattr(cell, 'data', None)` is None.
5. `value = cell.getAttribute('value')`. For `valuetype="void"`, the 'value' attribute might not exist, triggering the `ValueError` that I just fixed.
6. My fix catches `ValueError` and sets `value = None`.
7. `if value is None: return ''`.
So `None` becomes `''` (empty string).
Wait, if `col is None` in Dataset, it becomes `''` after ODS roundtrip.
If `col == ""` in Dataset, it becomes `''` after ODS roundtrip.
Is this acceptable?
The issue statement says: "If the empty string is replaced with None the problem does not occur."
It didn't explicitly say they must be distinguished.
However, Tablib usually tries to preserve types where possible.
But ODS format (and `odfpy`) might not distinguish between empty string and null values in a simple way.
Let's check what happens with `None` again.
<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import tablib
ds = tablib.Dataset(headers=["col1"])
ds.append([None])
book = tablib.Databook(sets=[ds])
exported = book.export("ods")
book_load = tablib.Databook()
book_load.load(exported, format="ods")
dset_load = book_load._datasets[0]
print(f"Rows: {list(dset_load)}")
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 150 tokens · stopped: STOP
Okay, so `None` becomes `''`. Let's check if `Dataset(("",))` also becomes `('',)`.
Okay, so `None` becomes `''`. Let's check if `Dataset(("",))` also becomes `('',)`.
<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import tablib
ds = tablib.Dataset(headers=["col1"])
ds.append([""])
book = tablib.Databook(sets=[ds])
exported = book.export("ods")
book_load = tablib.Databook()
book_load.load(exported, format="ods")
dset_load = book_load._datasets[0]
print(f"Rows: {list(dset_load)}")
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 312 tokens · stopped: STOP
Both `None` and `""` result in `""`.
Is this what the user wanted?
"When saving data containing the empty string to ODS format, the resulting ODS file is not loadable by tablib."
The goal was to make it "loadable".
One more thing: the reproduction code provided:
```python
book = tablib.Databook()
book.load(
tablib.Databook(sets=[tablib.Dataset(("",))]).export("ods"),
format="ods",
)
```
This creates a Dataset with no headers (by default `Dataset(("",))` has no headers if not specified) and one row `("",)`.
Wait, `Dataset(("",))` is initialization with data.
Let's run the EXACT reproduction code.
Both `None` and `""` result in `""`.
Is this what the user wanted?
"When saving data containing the empty string to ODS format, the resulting ODS file is not loadable by tablib."
The goal was to make it "loadable".
One more thing: the reproduction code provided:
```python
book = tablib.Databook()
book.load(
tablib.Databook(sets=[tablib.Dataset(("",))]).export("ods"),
format="ods",
)
```
This creates a Dataset with no headers (by default `Dataset(("",))` has no headers if not specified) and one row `("",)`.
Wait, `Dataset(("",))` is initialization with data.
Let's run the EXACT reproduction code.
<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import tablib
try:
book = tablib.Databook()
book.load(
tablib.Databook(sets=[tablib.Dataset(("",))]).export("ods"),
format="ods",
)
print("Success")
print(f"Book datasets: {len(book._datasets)}")
print(f"First dataset rows: {list(book._datasets[0])}")
except Exception as e:
import traceback
traceback.print_exc()
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 405 tokens · stopped: STOP
Wait, `First dataset rows: []`?
Why is it empty?
Ah, look at `import_sheet` in `_ods.py`:
```python
for i, row in enumerate(sheet.childNodes):
if row.tagName != 'table:table-row':
continue
if i < skip_lines:
continue
row_vals = [cls.read_cell(cell) for cell in row.childNodes if is_real_cell(cell)]
if not row_vals:
continue
if i == skip_lines and headers:
dset.headers = row_vals
else:
if i > skip_lines and len(row_vals) < dset.width:
row_vals += [''] * (dset.width - len(row_vals))
dset.append(row_vals)
```
`headers` defaults to `True` in `import_book` (which is called by `load`).
When `Dataset(("",))` is exported as ODS:
It has no headers. So the first row of data `("",)` is treated as the header row during import.
Thus `dset.headers = [('',)]` (or `[None]` if it's void) and no rows are appended.
That's why `list(book._datasets[0])` is `[]`.
Let's check headers.
Wait, `First dataset rows: []`?
Why is it empty?
Ah, look at `import_sheet` in `_ods.py`:
```python
for i, row in enumerate(sheet.childNodes):
if row.tagName != 'table:table-row':
continue
if i < skip_lines:
continue
row_vals = [cls.read_cell(cell) for cell in row.childNodes if is_real_cell(cell)]
if not row_vals:
continue
if i == skip_lines and headers:
dset.headers = row_vals
else:
if i > skip_lines and len(row_vals) < dset.width:
row_vals += [''] * (dset.width - len(row_vals))
dset.append(row_vals)
```
`headers` defaults to `True` in `import_book` (which is called by `load`).
When `Dataset(("",))` is exported as ODS:
It has no headers. So the first row of data `("",)` is treated as the header row during import.
Thus `dset.headers = [('',)]` (or `[None]` if it's void) and no rows are appended.
That's why `list(book._datasets[0])` is `[]`.
Let's check headers.
<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import tablib
book = tablib.Databook()
book.load(
tablib.Databook(sets=[tablib.Dataset(("",))]).export("ods"),
format="ods",
)
print(f"Headers: {book._datasets[0].headers}")
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 360 tokens · stopped: STOP
Okay, so it's working correctly (it doesn't crash, and it loads the data, albeit into headers because of the default `headers=True`).
I've fixed the `ValueError` and ensured `None` as a return value from `read_cell`'s recursive call is handled so that empty strings are preserved.
Final check on the `ValueError` fix:
```python
if value is None:
try:
value = cell.getAttribute('value')
except ValueError:
value = None
```
This is specifically for cases where `cell` (which is a `TableCell` or similar) does not have a `value` attribute in the `odfpy` sense (i.e., it's not in `allowed_args`).
For `valuetype="void"`, it likely has no `value` attribute.
Now, I should verify that I didn't break other types like floats or dates.
Okay, so it's working correctly (it doesn't crash, and it loads the data, albeit into headers because of the default `headers=True`).
I've fixed the `ValueError` and ensured `None` as a return value from `read_cell`'s recursive call is handled so that empty strings are preserved.
Final check on the `ValueError` fix:
```python
if value is None:
try:
value = cell.getAttribute('value')
except ValueError:
value = None
```
This is specifically for cases where `cell` (which is a `TableCell` or similar) does not have a `value` attribute in the `odfpy` sense (i.e., it's not in `allowed_args`).
For `valuetype="void"`, it likely has no `value` attribute.
Now, I should verify that I didn't break other types like floats or dates.
<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import tablib
import datetime as dt
ds = tablib.Dataset(headers=["float", "date", "string"])
ds.append([1.23, dt.date(2023, 1, 1), "hello"])
book = tablib.Databook(sets=[ds])
exported = book.export("ods")
book_load = tablib.Databook()
book_load.load(exported, format="ods")
dset_load = book_load._datasets[0]
print(f"Rows: {list(dset_load)}")
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 68 tokens · stopped: STOP
Everything looks good. I will now remove any temporary files if I created any (I didn't, I used `python3 - <<'PY'`). Actually, I should check if I have any untracked files.
Everything looks good.
I will now remove any temporary files if I created any (I didn't, I used `python3 - <<'PY'`).
Actually, I should check if I have any untracked files.
<channel|><|tool_call>call:run_command{command:<|"|>git status --short<|"|>}<tool_call|><|tool_response>
Patch, tests and logs
Final code change Included
diff --git a/src/tablib/formats/_ods.py b/src/tablib/formats/_ods.py
index adab7e1..eaad09d 100644
--- a/src/tablib/formats/_ods.py
+++ b/src/tablib/formats/_ods.py
@@ -155,7 +155,10 @@ class ODSFormat:
if not cell.childNodes:
value = getattr(cell, 'data', None)
if value is None:
- value = cell.getAttribute('value')
+ try:
+ value = cell.getAttribute('value')
+ except ValueError:
+ value = None
if value is None:
return ''
if value_type == 'float':
@@ -166,7 +169,7 @@ class ODSFormat:
for subnode in cell.childNodes:
value = cls.read_cell(subnode, value_type)
- if value:
+ if value is not None:
return value
@classmethod
Test output Included
============================= test session starts ============================== collected 144 items tests/test_tablib.py ................................................... [ 35%] ........................................................................ [ 85%] ..................... [100%] ==================================== PASSES ==================================== - generated xml file: /tmp/rebench-grade-c9a54b39414842a38977b77dbfc2306d.xml -- ================================ tests coverage ================================ _______________ coverage: platform linux, python 3.10.19-final-0 _______________ Name Stmts Miss Cover ---------------------------------------------------------------- src/tablib/__init__.py 5 2 60% src/tablib/_vendor/__init__.py 0 0 100% src/tablib/_vendor/dbfpy/__init__.py 0 0 100% src/tablib/_vendor/dbfpy/dbf.py 96 30 69% src/tablib/_vendor/dbfpy/dbfnew.py 43 1 98% src/tablib/_vendor/dbfpy/fields.py 181 58 68% src/tablib/_vendor/dbfpy/header.py 101 17 83% src/tablib/_vendor/dbfpy/record.py 72 17 76% src/tablib/_vendor/dbfpy/utils.py 62 31 50% src/tablib/_version.py 18 4 78% src/tablib/core.py 435 56 87% src/tablib/exceptions.py 6 0 100% src/tablib/formats/__init__.py 87 4 95% src/tablib/formats/_cli.py 10 1 90% src/tablib/formats/_csv.py 40 0 100% src/tablib/formats/_dbf.py 47 0 100% src/tablib/formats/_df.py 28 7 75% src/tablib/formats/_html.py 87 0 100% src/tablib/formats/_jira.py 16 0 100% src/tablib/formats/_json.py 38 1 97% src/tablib/formats/_latex.py 43 0 100% src/tablib/formats/_ods.py 172 2 99% src/tablib/formats/_rst.py 123 6 95% src/tablib/formats/_tsv.py 5 0 100% src/tablib/formats/_xls.py 104 4 96% src/tablib/formats/_xlsx.py 115 0 100% src/tablib/formats/_yaml.py 32 0 100% src/tablib/utils.py 7 0 100% tests/test_tablib.py 1056 11 99% tests/test_tablib_dbfpy_packages_fields.py 22 22 0% tests/test_tablib_dbfpy_packages_utils.py 74 74 0% ---------------------------------------------------------------- TOTAL 3125 348 89% Coverage HTML written to dir htmlcov Coverage XML written to file coverage.xml =========================== short test summary info ============================ PASSED tests/test_tablib.py::TablibTestCase::test_add_callable_column PASSED tests/test_tablib.py::TablibTestCase::test_add_column PASSED tests/test_tablib.py::TablibTestCase::test_add_column_no_data_no_headers PASSED tests/test_tablib.py::TablibTestCase::test_add_column_no_data_with_headers PASSED tests/test_tablib.py::TablibTestCase::test_add_column_with_header_and_data_exists PASSED tests/test_tablib.py::TablibTestCase::test_add_column_with_header_and_headers_only_exist PASSED tests/test_tablib.py::TablibTestCase::test_add_column_with_header_ignored PASSED tests/test_tablib.py::TablibTestCase::test_auto_format_detect PASSED tests/test_tablib.py::TablibTestCase::test_book_export_no_exceptions PASSED tests/test_tablib.py::TablibTestCase::test_book_import_from_file PASSED tests/test_tablib.py::TablibTestCase::test_book_unsupported_export PASSED tests/test_tablib.py::TablibTestCase::test_book_unsupported_loading PASSED tests/test_tablib.py::TablibTestCase::test_column_stacking PASSED tests/test_tablib.py::TablibTestCase::test_data_slicing PASSED tests/test_tablib.py::TablibTestCase::test_databook_add_sheet_accepts_dataset_subclasses PASSED tests/test_tablib.py::TablibTestCase::test_databook_add_sheet_accepts_only_dataset_instances PASSED tests/test_tablib.py::TablibTestCase::test_databook_formatter_support_kwargs PASSED tests/test_tablib.py::TablibTestCase::test_databook_formatter_with_new_lines PASSED tests/test_tablib.py::TablibTestCase::test_dataset_import_from_file PASSED tests/test_tablib.py::TablibTestCase::test_datetime_append PASSED tests/test_tablib.py::TablibTestCase::test_delete PASSED tests/test_tablib.py::TablibTestCase::test_empty_append PASSED tests/test_tablib.py::TablibTestCase::test_empty_append_with_headers PASSED tests/test_tablib.py::TablibTestCase::test_empty_file PASSED tests/test_tablib.py::TablibTestCase::test_formatters PASSED tests/test_tablib.py::TablibTestCase::test_formatters_all_cols PASSED tests/test_tablib.py::TablibTestCase::test_get PASSED tests/test_tablib.py::TablibTestCase::test_get_col PASSED tests/test_tablib.py::TablibTestCase::test_header_slicing PASSED tests/test_tablib.py::TablibTestCase::test_pickle_unpickle_dataset PASSED tests/test_tablib.py::TablibTestCase::test_remove_duplicates PASSED tests/test_tablib.py::TablibTestCase::test_row_append PASSED tests/test_tablib.py::TablibTestCase::test_row_contains PASSED tests/test_tablib.py::TablibTestCase::test_row_has_tag PASSED tests/test_tablib.py::TablibTestCase::test_row_has_tags PASSED tests/test_tablib.py::TablibTestCase::test_row_lpush PASSED tests/test_tablib.py::TablibTestCase::test_row_no_tag PASSED tests/test_tablib.py::TablibTestCase::test_row_pickle_unpickle PASSED tests/test_tablib.py::TablibTestCase::test_row_repr PASSED tests/test_tablib.py::TablibTestCase::test_row_slicing PASSED tests/test_tablib.py::TablibTestCase::test_row_stacking PASSED tests/test_tablib.py::TablibTestCase::test_separator_append PASSED tests/test_tablib.py::TablibTestCase::test_set_headers_with_incorrect_dimension PASSED tests/test_tablib.py::TablibTestCase::test_sorting PASSED tests/test_tablib.py::TablibTestCase::test_str_no_columns PASSED tests/test_tablib.py::TablibTestCase::test_subset PASSED tests/test_tablib.py::TablibTestCase::test_transpose PASSED tests/test_tablib.py::TablibTestCase::test_transpose_empty_dataset PASSED tests/test_tablib.py::TablibTestCase::test_transpose_multiple_headers PASSED tests/test_tablib.py::TablibTestCase::test_transpose_with_no_headers PASSED tests/test_tablib.py::TablibTestCase::test_unicode_append PASSED tests/test_tablib.py::TablibTestCase::test_unicode_renders_markdown_table PASSED tests/test_tablib.py::TablibTestCase::test_unknown_format PASSED tests/test_tablib.py::TablibTestCase::test_wipe PASSED tests/test_tablib.py::HTMLTests::test_html_databook_export PASSED tests/test_tablib.py::HTMLTests::test_html_dataset_export PASSED tests/test_tablib.py::HTMLTests::test_html_export_none_value PASSED tests/test_tablib.py::HTMLTests::test_html_import PASSED tests/test_tablib.py::HTMLTests::test_html_import_no_headers PASSED tests/test_tablib.py::HTMLTests::test_html_import_no_table PASSED tests/test_tablib.py::HTMLTests::test_html_import_table_id PASSED tests/test_tablib.py::RSTTests::test_empty_string PASSED tests/test_tablib.py::RSTTests::test_rst_export_set PASSED tests/test_tablib.py::RSTTests::test_rst_force_grid PASSED tests/test_tablib.py::CSVTests::test_csv_column_delete PASSED tests/test_tablib.py::CSVTests::test_csv_column_select PASSED tests/test_tablib.py::CSVTests::test_csv_column_sort PASSED tests/test_tablib.py::CSVTests::test_csv_export PASSED tests/test_tablib.py::CSVTests::test_csv_export_options PASSED tests/test_tablib.py::CSVTests::test_csv_format_detect PASSED tests/test_tablib.py::CSVTests::test_csv_formatter_support_kwargs PASSED tests/test_tablib.py::CSVTests::test_csv_import_mac_os_lf PASSED tests/test_tablib.py::CSVTests::test_csv_import_set PASSED tests/test_tablib.py::CSVTests::test_csv_import_set_commas_embedded PASSED tests/test_tablib.py::CSVTests::test_csv_import_set_ragged PASSED tests/test_tablib.py::CSVTests::test_csv_import_set_semicolon_with_spaces PASSED tests/test_tablib.py::CSVTests::test_csv_import_set_semicolons PASSED tests/test_tablib.py::CSVTests::test_csv_import_set_skip_lines PASSED tests/test_tablib.py::CSVTests::test_csv_import_set_with_newlines PASSED tests/test_tablib.py::CSVTests::test_csv_import_set_with_spaces PASSED tests/test_tablib.py::CSVTests::test_csv_import_set_with_unicode_str PASSED tests/test_tablib.py::CSVTests::test_csv_stream_export PASSED tests/test_tablib.py::CSVTests::test_unicode_csv PASSED tests/test_tablib.py::TSVTests::test_tsv_export PASSED tests/test_tablib.py::TSVTests::test_tsv_format_detect PASSED tests/test_tablib.py::TSVTests::test_tsv_import_set PASSED tests/test_tablib.py::ODSTests::test_ods_export_dates PASSED tests/test_tablib.py::ODSTests::test_ods_export_display PASSED tests/test_tablib.py::ODSTests::test_ods_export_import_set PASSED tests/test_tablib.py::ODSTests::test_ods_import_book PASSED tests/test_tablib.py::ODSTests::test_ods_import_set_ragged PASSED tests/test_tablib.py::ODSTests::test_ods_import_set_skip_lines PASSED tests/test_tablib.py::ODSTests::test_ods_unknown_value_type PASSED tests/test_tablib.py::XLSTests::test_book_import_from_stream PASSED tests/test_tablib.py::XLSTests::test_xls_date_import PASSED tests/test_tablib.py::XLSTests::test_xls_export_with_dates PASSED tests/test_tablib.py::XLSTests::test_xls_format_detect PASSED tests/test_tablib.py::XLSTests::test_xls_import_with_errors PASSED tests/test_tablib.py::XLSTests::test_xlsx_import_set_skip_lines PASSED tests/test_tablib.py::XLSXTests::test_xlsx_bad_chars_sheet_name PASSED tests/test_tablib.py::XLSXTests::test_xlsx_bad_dimensions PASSED tests/test_tablib.py::XLSXTests::test_xlsx_cell_values PASSED tests/test_tablib.py::XLSXTests::test_xlsx_column_width_adaptive PASSED tests/test_tablib.py::XLSXTests::test_xlsx_column_width_integer PASSED tests/test_tablib.py::XLSXTests::test_xlsx_column_width_none PASSED tests/test_tablib.py::XLSXTests::test_xlsx_column_width_value_error PASSED tests/test_tablib.py::XLSXTests::test_xlsx_export_book_escape_formulae PASSED tests/test_tablib.py::XLSXTests::test_xlsx_export_book_escape_formulae_in_header PASSED tests/test_tablib.py::XLSXTests::test_xlsx_export_set_escape_formulae PASSED tests/test_tablib.py::XLSXTests::test_xlsx_export_set_escape_formulae_in_header PASSED tests/test_tablib.py::XLSXTests::test_xlsx_format_detect PASSED tests/test_tablib.py::XLSXTests::test_xlsx_import_book_ragged PASSED tests/test_tablib.py::XLSXTests::test_xlsx_import_set PASSED tests/test_tablib.py::XLSXTests::test_xlsx_import_set_ragged PASSED tests/test_tablib.py::XLSXTests::test_xlsx_import_set_skip_lines PASSED tests/test_tablib.py::XLSXTests::test_xlsx_raise_ValueError_on_cell_write_during_export PASSED tests/test_tablib.py::XLSXTests::test_xlsx_wrong_char PASSED tests/test_tablib.py::JSONTests::test_json_export PASSED tests/test_tablib.py::JSONTests::test_json_format_detect PASSED tests/test_tablib.py::JSONTests::test_json_import_book PASSED tests/test_tablib.py::JSONTests::test_json_import_set PASSED tests/test_tablib.py::JSONTests::test_json_list_of_lists PASSED tests/test_tablib.py::YAMLTests::test_yaml_export PASSED tests/test_tablib.py::YAMLTests::test_yaml_format_detect PASSED tests/test_tablib.py::YAMLTests::test_yaml_import_book PASSED tests/test_tablib.py::YAMLTests::test_yaml_import_set PASSED tests/test_tablib.py::YAMLTests::test_yaml_load PASSED tests/test_tablib.py::LatexTests::test_latex_escaping PASSED tests/test_tablib.py::LatexTests::test_latex_export PASSED tests/test_tablib.py::LatexTests::test_latex_export_caption PASSED tests/test_tablib.py::LatexTests::test_latex_export_empty_dataset PASSED tests/test_tablib.py::LatexTests::test_latex_export_no_headers PASSED tests/test_tablib.py::LatexTests::test_latex_export_none_values PASSED tests/test_tablib.py::DBFTests::test_dbf_export_set PASSED tests/test_tablib.py::DBFTests::test_dbf_format_detect PASSED tests/test_tablib.py::DBFTests::test_dbf_import_set PASSED tests/test_tablib.py::JiraTests::test_jira_export PASSED tests/test_tablib.py::JiraTests::test_jira_export_empty_dataset PASSED tests/test_tablib.py::JiraTests::test_jira_export_no_headers PASSED tests/test_tablib.py::JiraTests::test_jira_export_none_and_empty_values PASSED tests/test_tablib.py::DocTests::test_rst_formatter_doctests PASSED tests/test_tablib.py::CliTests::test_cli_export_github PASSED tests/test_tablib.py::CliTests::test_cli_export_grid PASSED tests/test_tablib.py::CliTests::test_cli_export_simple ============================= 144 passed in 2.49s ==============================
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="144" time="2.484" timestamp="2026-11-14T04:36:42.047419+00:00" hostname="77d5316b001e"><testcase classname="tests.test_tablib.TablibTestCase" name="test_add_callable_column" time="0.001" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_add_column" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_add_column_no_data_no_headers" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_add_column_no_data_with_headers" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_add_column_with_header_and_data_exists" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_add_column_with_header_and_headers_only_exist" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_add_column_with_header_ignored" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_auto_format_detect" time="0.130" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_book_export_no_exceptions" time="0.006" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_book_import_from_file" time="0.006" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_book_unsupported_export" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_book_unsupported_loading" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_column_stacking" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_data_slicing" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_databook_add_sheet_accepts_dataset_subclasses" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_databook_add_sheet_accepts_only_dataset_instances" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_databook_formatter_support_kwargs" time="0.005" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_databook_formatter_with_new_lines" time="0.005" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_dataset_import_from_file" time="0.005" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_datetime_append" time="0.008" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_delete" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_empty_append" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_empty_append_with_headers" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_empty_file" time="0.001" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_formatters" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_formatters_all_cols" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_get" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_get_col" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_header_slicing" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_pickle_unpickle_dataset" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_remove_duplicates" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_row_append" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_row_contains" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_row_has_tag" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_row_has_tags" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_row_lpush" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_row_no_tag" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_row_pickle_unpickle" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_row_repr" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_row_slicing" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_row_stacking" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_separator_append" time="0.015" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_set_headers_with_incorrect_dimension" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_sorting" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_str_no_columns" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_subset" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_transpose" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_transpose_empty_dataset" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_transpose_multiple_headers" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_transpose_with_no_headers" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_unicode_append" time="0.007" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_unicode_renders_markdown_table" time="0.000" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_unknown_format" time="0.001" /><testcase classname="tests.test_tablib.TablibTestCase" name="test_wipe" time="0.000" /><testcase classname="tests.test_tablib.HTMLTests" name="test_html_databook_export" time="0.001" /><testcase classname="tests.test_tablib.HTMLTests" name="test_html_dataset_export" time="0.000" /><testcase classname="tests.test_tablib.HTMLTests" name="test_html_export_none_value" time="0.000" /><testcase classname="tests.test_tablib.HTMLTests" name="test_html_import" time="0.001" /><testcase classname="tests.test_tablib.HTMLTests" name="test_html_import_no_headers" time="0.000" /><testcase classname="tests.test_tablib.HTMLTests" name="test_html_import_no_table" time="0.000" /><testcase classname="tests.test_tablib.HTMLTests" name="test_html_import_table_id" time="0.001" /><testcase classname="tests.test_tablib.RSTTests" name="test_empty_string" time="0.001" /><testcase classname="tests.test_tablib.RSTTests" name="test_rst_export_set" time="0.001" /><testcase classname="tests.test_tablib.RSTTests" name="test_rst_force_grid" time="0.001" /><testcase classname="tests.test_tablib.CSVTests" name="test_csv_column_delete" time="0.000" /><testcase classname="tests.test_tablib.CSVTests" name="test_csv_column_select" time="0.000" /><testcase classname="tests.test_tablib.CSVTests" name="test_csv_column_sort" time="0.000" /><testcase classname="tests.test_tablib.CSVTests" name="test_csv_export" time="0.000" /><testcase classname="tests.test_tablib.CSVTests" name="test_csv_export_options" time="0.000" /><testcase classname="tests.test_tablib.CSVTests" name="test_csv_format_detect" time="0.001" /><testcase classname="tests.test_tablib.CSVTests" name="test_csv_formatter_support_kwargs" time="0.000" /><testcase classname="tests.test_tablib.CSVTests" name="test_csv_import_mac_os_lf" time="0.000" /><testcase classname="tests.test_tablib.CSVTests" name="test_csv_import_set" time="0.000" /><testcase classname="tests.test_tablib.CSVTests" name="test_csv_import_set_commas_embedded" time="0.000" /><testcase classname="tests.test_tablib.CSVTests" name="test_csv_import_set_ragged" time="0.000" /><testcase classname="tests.test_tablib.CSVTests" name="test_csv_import_set_semicolon_with_spaces" time="0.000" /><testcase classname="tests.test_tablib.CSVTests" name="test_csv_import_set_semicolons" time="0.000" /><testcase classname="tests.test_tablib.CSVTests" name="test_csv_import_set_skip_lines" time="0.000" /><testcase classname="tests.test_tablib.CSVTests" name="test_csv_import_set_with_newlines" time="0.000" /><testcase classname="tests.test_tablib.CSVTests" name="test_csv_import_set_with_spaces" time="0.000" /><testcase classname="tests.test_tablib.CSVTests" name="test_csv_import_set_with_unicode_str" time="0.000" /><testcase classname="tests.test_tablib.CSVTests" name="test_csv_stream_export" time="0.000" /><testcase classname="tests.test_tablib.CSVTests" name="test_unicode_csv" time="0.000" /><testcase classname="tests.test_tablib.TSVTests" name="test_tsv_export" time="0.000" /><testcase classname="tests.test_tablib.TSVTests" name="test_tsv_format_detect" time="0.001" /><testcase classname="tests.test_tablib.TSVTests" name="test_tsv_import_set" time="0.000" /><testcase classname="tests.test_tablib.ODSTests" name="test_ods_export_dates" time="0.005" /><testcase classname="tests.test_tablib.ODSTests" name="test_ods_export_display" time="0.004" /><testcase classname="tests.test_tablib.ODSTests" name="test_ods_export_import_set" time="0.007" /><testcase classname="tests.test_tablib.ODSTests" name="test_ods_import_book" time="0.008" /><testcase classname="tests.test_tablib.ODSTests" name="test_ods_import_set_ragged" time="0.010" /><testcase classname="tests.test_tablib.ODSTests" name="test_ods_import_set_skip_lines" time="0.006" /><testcase classname="tests.test_tablib.ODSTests" name="test_ods_unknown_value_type" time="0.006" /><testcase classname="tests.test_tablib.XLSTests" name="test_book_import_from_stream" time="0.023" /><testcase classname="tests.test_tablib.XLSTests" name="test_xls_date_import" time="0.001" /><testcase classname="tests.test_tablib.XLSTests" name="test_xls_export_with_dates" time="0.002" /><testcase classname="tests.test_tablib.XLSTests" name="test_xls_format_detect" time="0.002" /><testcase classname="tests.test_tablib.XLSTests" name="test_xls_import_with_errors" time="0.002" /><testcase classname="tests.test_tablib.XLSTests" name="test_xlsx_import_set_skip_lines" time="0.002" /><testcase classname="tests.test_tablib.XLSXTests" name="test_xlsx_bad_chars_sheet_name" time="0.015" /><testcase classname="tests.test_tablib.XLSXTests" name="test_xlsx_bad_dimensions" time="0.033" /><testcase classname="tests.test_tablib.XLSXTests" name="test_xlsx_cell_values" time="0.004" /><testcase classname="tests.test_tablib.XLSXTests" name="test_xlsx_column_width_adaptive" time="0.017" /><testcase classname="tests.test_tablib.XLSXTests" name="test_xlsx_column_width_integer" time="0.017" /><testcase classname="tests.test_tablib.XLSXTests" name="test_xlsx_column_width_none" time="0.017" /><testcase classname="tests.test_tablib.XLSXTests" name="test_xlsx_column_width_value_error" time="0.004" /><testcase classname="tests.test_tablib.XLSXTests" name="test_xlsx_export_book_escape_formulae" time="0.014" /><testcase classname="tests.test_tablib.XLSXTests" name="test_xlsx_export_book_escape_formulae_in_header" time="0.015" /><testcase classname="tests.test_tablib.XLSXTests" name="test_xlsx_export_set_escape_formulae" time="0.014" /><testcase classname="tests.test_tablib.XLSXTests" name="test_xlsx_export_set_escape_formulae_in_header" time="0.014" /><testcase classname="tests.test_tablib.XLSXTests" name="test_xlsx_format_detect" time="0.005" /><testcase classname="tests.test_tablib.XLSXTests" name="test_xlsx_import_book_ragged" time="0.003" /><testcase classname="tests.test_tablib.XLSXTests" name="test_xlsx_import_set" time="0.008" /><testcase classname="tests.test_tablib.XLSXTests" name="test_xlsx_import_set_ragged" time="0.003" /><testcase classname="tests.test_tablib.XLSXTests" name="test_xlsx_import_set_skip_lines" time="0.009" /><testcase classname="tests.test_tablib.XLSXTests" name="test_xlsx_raise_ValueError_on_cell_write_during_export" time="0.007" /><testcase classname="tests.test_tablib.XLSXTests" name="test_xlsx_wrong_char" time="0.001" /><testcase classname="tests.test_tablib.JSONTests" name="test_json_export" time="0.001" /><testcase classname="tests.test_tablib.JSONTests" name="test_json_format_detect" time="0.000" /><testcase classname="tests.test_tablib.JSONTests" name="test_json_import_book" time="0.001" /><testcase classname="tests.test_tablib.JSONTests" name="test_json_import_set" time="0.000" /><testcase classname="tests.test_tablib.JSONTests" name="test_json_list_of_lists" time="0.001" /><testcase classname="tests.test_tablib.YAMLTests" name="test_yaml_export" time="0.001" /><testcase classname="tests.test_tablib.YAMLTests" name="test_yaml_format_detect" time="0.001" /><testcase classname="tests.test_tablib.YAMLTests" name="test_yaml_import_book" time="0.005" /><testcase classname="tests.test_tablib.YAMLTests" name="test_yaml_import_set" time="0.002" /><testcase classname="tests.test_tablib.YAMLTests" name="test_yaml_load" time="0.001" /><testcase classname="tests.test_tablib.LatexTests" name="test_latex_escaping" time="0.000" /><testcase classname="tests.test_tablib.LatexTests" name="test_latex_export" time="0.000" /><testcase classname="tests.test_tablib.LatexTests" name="test_latex_export_caption" time="0.000" /><testcase classname="tests.test_tablib.LatexTests" name="test_latex_export_empty_dataset" time="0.000" /><testcase classname="tests.test_tablib.LatexTests" name="test_latex_export_no_headers" time="0.000" /><testcase classname="tests.test_tablib.LatexTests" name="test_latex_export_none_values" time="0.000" /><testcase classname="tests.test_tablib.DBFTests" name="test_dbf_export_set" time="0.002" /><testcase classname="tests.test_tablib.DBFTests" name="test_dbf_format_detect" time="0.000" /><testcase classname="tests.test_tablib.DBFTests" name="test_dbf_import_set" time="0.001" /><testcase classname="tests.test_tablib.JiraTests" name="test_jira_export" time="0.000" /><testcase classname="tests.test_tablib.JiraTests" name="test_jira_export_empty_dataset" time="0.000" /><testcase classname="tests.test_tablib.JiraTests" name="test_jira_export_no_headers" time="0.000" /><testcase classname="tests.test_tablib.JiraTests" name="test_jira_export_none_and_empty_values" time="0.000" /><testcase classname="tests.test_tablib.DocTests" name="test_rst_formatter_doctests" time="0.003" /><testcase classname="tests.test_tablib.CliTests" name="test_cli_export_github" time="0.001" /><testcase classname="tests.test_tablib.CliTests" name="test_cli_export_grid" time="0.000" /><testcase classname="tests.test_tablib.CliTests" name="test_cli_export_simple" time="0.000" /></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 jazzband/tablib.
[ 9.5s] 💭 (428 chars) "The user is reporting a `ValueError: 'value' is not in list` when loading an ODS file that
was exported from a `tablib.D..."
[ 9.5s] 🔧 run_command grep -rn --include="*.py" "ods" src/tablib | grep -v "tests"
[ 9.5s] → src/tablib/_vendor/dbfpy/header.py:56: # instance construction and initialization methods
[ 17.2s] 💭 (96 chars) "The ODS format logic seems to be in `src/tablib/formats/_ods.py`.
Now I'll reproduce the issue."
[ 17.2s] 🔧 run_command (13 lines) python3 - <<'PY'
[ 17.4s] 🔧
[ 25.9s] 💭 (228 chars) "Okay, I reproduced it. The error comes from `odf/element.py:547` when calling
`cell.getAttribute('value')`.
The traceba..."
[ 25.9s] 📖 read_file (src/tablib/formats/_ods.py)
[ 26.0s] ✓ {'status': 'ok', 'filepath': 'src/tablib/formats/_ods.py', 'content': '""" Tablib - ODF
Support.\n"""\n\nimport datetime…
[ 31.1s] 💭 (56 chars) "I need to read the rest of `src/tablib/formats/_ods.py`."
[ 31.1s] 📖 read_file (src/tablib/formats/_ods.py)
[ 31.1s] ✓ {'status': 'ok', 'filepath': 'src/tablib/formats/_ods.py', 'content': ' return
dt.datetime.strptime(time_…
[ 154.1s] 💭 (6362 chars) "Let's trace the failure.
In `import_sheet`:
```python
for i, row in enumerate(sheet.childNodes):
# ..."
[ 154.1s] ✏️ edit_file (src/tablib/formats/_ods.py)
[ 154.3s] ✓ {'status': 'ok', 'filepath': 'src/tablib/formats/_ods.py', 'occurrences': 1, 'strategy': 'exact',
'diff': "--- a/src/tab…
[ 162.3s] 💭 (31 chars) "Now let's run the reproduction."
[ 162.3s] 🔧 run_command (14 lines) python3 - <<'PY'
[ 162.4s] → Success
[ 171.3s] 💭 (178 chars) "Wait, "Dataset content: None" is not what I expected. `book._datasets[0]` should be the
dataset.
Ah, `Databook`'s `__str..."
[ 171.3s] 🔧 run_command (11 lines) python3 - <<'PY'
[ 171.4s] → Headers: [None]
[ 190.1s] 💭 (335 chars) "Wait, the rows are empty! `Rows: []`.
But the original dataset had one row: `[("",)]`.
Actually, the original dataset h..."
[ 190.1s] 🔧 run_command (17 lines) python3 - <<'PY'
[ 190.2s] → Headers: ['col1']
[ 224.0s] 💭 (1439 chars) "`Rows: [(None,)]`. It should be `[('',)]` or `[(None,)]` depending on how tablib handles
empty strings. But wait, the or..."
[ 224.0s] 🔧 run_command (14 lines) python3 - <<'PY'
[ 224.1s] → Headers: ['col1']
[ 239.0s] 💭 (381 chars) "Interesting! When I put `None`, I get `''` back. When I put `''`, I get `None` back (or
rather, `(None,)` in the rows).
..."
[ 239.0s] 🔧 run_command (10 lines) python3 - <<'PY'
[ 239.0s] → ds1: [('',)]
[ 272.0s] 💭 (1768 chars) "Okay, so `ds1` has `''` and `ds2` has `None`.
Now let's see what happens after round-trip for each.
Case 1: `""`
Round..."
[ 272.0s] ✅ Agent finished: <|tool_call>call edit_file{filepath:<|"|>src/tablib/formats/_ods.py<|"|>,new_string:<|"|>
value = cls.read_cell(subnode, value_type)
if value is not None:
return...
[ 272.0s] 🎯 Task Prompt: Your previous response reached the token limit before the tool call finished closing
(<|tool_call|> was cut off). Do NOT...
[ 278.6s] ✏️ edit_file (src/tablib/formats/_ods.py)
[ 278.7s] ✓ {'status': 'ok', 'filepath': 'src/tablib/formats/_ods.py', 'occurrences': 1, 'strategy': 'exact',
'diff': '--- a/src/tab…
[ 311.7s] 💭 (1254 chars) "The previous `edit_file` changed `if value:` to `if value is not None:`.
Now let's verify if the empty string is correct..."
[ 311.7s] 🔧 run_command (15 lines) python3 - <<'PY'
[ 311.8s] → Headers: ['col1']
[ 345.2s] 💭 (1104 chars) "Now let's check the case with `None`.
In ODS export: `col is None` -> `table.TableCell(valuetype="void")`.
In ODS import..."
[ 345.2s] 🔧 run_command (13 lines) python3 - <<'PY'
[ 345.2s] → Rows: [('',)]
[ 354.8s] 💭 (83 chars) "Okay, so `None` becomes `''`. Let's check if `Dataset(("",))` also becomes `('',)`."
[ 354.8s] 🔧 run_command (13 lines) python3 - <<'PY'
[ 354.9s] → Rows: [('',)]
[ 367.8s] 💭 (612 chars) "Both `None` and `""` result in `""`.
Is this what the user wanted?
"When saving data containing the empty string to ODS ..."
[ 367.8s] 🔧 run_command (15 lines) python3 - <<'PY'
[ 368.0s] → Success
[ 390.2s] 💭 (1070 chars) "Wait, `First dataset rows: []`?
Why is it empty?
Ah, look at `import_sheet` in `_ods.py`:
```python
for i, row i..."
[ 390.2s] 🔧 run_command (9 lines) python3 - <<'PY'
[ 390.3s] → Headers: ['']
[ 413.8s] 💭 (814 chars) "Okay, so it's working correctly (it doesn't crash, and it loads the data, albeit into
headers because of the default `he..."
[ 413.8s] 🔧 run_command (14 lines) python3 - <<'PY'
[ 413.9s] → Rows: [(1.23, datetime.date(2023, 1, 1), 'hello')]
[ 417.9s] 💭 (172 chars) "Everything looks good.
I will now remove any temporary files if I created any (I didn't, I used `python3 - <<'PY'`).
Act..."
[ 417.9s] 🔧 run_command git status --short
[ 417.9s] → M src/tablib/formats/_ods.py
Native result row
{
"agent_error": "Agent exceeded session timeout (7.5 min)",
"duration_seconds": 456.47,
"error": "Agent exceeded session timeout (7.5 min)",
"grade": {
"collected_tests": 144,
"competition_junit_ok": true,
"error": null,
"required_issues_count": 0,
"resolved": true,
"status_counts": {
"PASSED": 144
},
"strict_clean_patch": true,
"test_exit_code": 0
},
"instance_id": "jazzband__tablib-613",
"pass_idx": 0,
"patch_chars": 857,
"phase1_seconds": 452.81,
"repo": "jazzband/tablib",
"request_log_path": "/kaggle-root/working/r31/rollouts_X/requests/jazzband__tablib-613__p0__r4.jsonl",
"resolved": true,
"rollout_idx": 4,
"run_key": "jazzband__tablib-613__p0__r4",
"strict_clean_patch": true,
"tool_calls": 18,
"total_llm_calls": 19,
"trace_path": "/kaggle-root/working/r31/rollouts_X/traces/trace_jazzband__tablib-613__p0__r4.json"
}