def build_code_export(data_id, imports='import pandas as pd\n\n', query=None):
"""
Helper function for building a string representing the code that was run to get the data you are viewing to that
point.
:param data_id: integer string identifier for a D-Tale process's data
:type data_id: str
:param imports: string representing the imports at the top of the code string
:type imports: string, optional
:param query: pandas dataframe query string
:type query: str, optional
:return: python code string
"""
history = global_state.get_history(data_id) or []
settings = global_state.get_settings(data_id) or {}
ctxt_vars = global_state.get_context_variables(data_id)
startup_code = settings.get('startup_code')
startup_code = '# Data Re-shaping\n{}\n\n'.format(startup_code) if startup_code else ''
startup_str = (
"# DISCLAIMER: 'df' refers to the data you passed in when calling 'dtale.show'\n\n"
'{imports}'
'{startup}'
'if isinstance(df, (pd.DatetimeIndex, pd.MultiIndex)):\n'
'\tdf = df.to_frame(index=False)\n\n'
'# remove any pre-existing indices for ease of use in the D-Tale code, but this is not required\n'
"df = df.reset_index().drop('index', axis=1, errors='ignore')\n"
'df.columns = [str(c) for c in df.columns] # update columns to strings in case they are numbers\n'
).format(imports=imports, startup=startup_code)
final_history = [startup_str] + history
final_query = query
if final_query is None:
final_query = settings.get('query')
if final_query is not None:
if len(ctxt_vars or {}):
final_history.append((
"\n# this is injecting any context variables you may have passed into 'dtale.show'\n"
"import dtale.global_state as dtale_global_state\n"
"\n# DISCLAIMER: running this line in a different process than the one it originated will produce\n"
"# differing results\n"
"ctxt_vars = dtale_global_state.get_context_variables('{data_id}')\n\n"
'df = df.query("{query}", local_dict=ctxt_vars)\n'
).format(query=final_query, data_id=data_id))
else:
final_history.append("df = df.query('{}')\n".format(final_query))
elif 'query' in settings:
final_history.append("df = df.query('{}')\n".format(settings['query']))
if 'sort' in settings:
cols, dirs = [], []
for col, dir in settings['sort']:
cols.append(col)
dirs.append('True' if dir == 'ASC' else 'False')
final_history.append("df = df.sort_values(['{cols}'], ascending=[{dirs}])\n".format(
cols=', '.join(cols), dirs="', '".join(dirs)
))
return final_history
def build_code_export(data_id, imports="import pandas as pd\n\n", query=None):
"""
Helper function for building a string representing the code that was run to get the data you are viewing to that
point.
:param data_id: integer string identifier for a D-Tale process's data
:type data_id: str
:param imports: string representing the imports at the top of the code string
:type imports: string, optional
:param query: pandas dataframe query string
:type query: str, optional
:return: python code string
"""
history = global_state.get_history(data_id) or []
settings = global_state.get_settings(data_id) or {}
ctxt_vars = global_state.get_context_variables(data_id)
startup_code = settings.get("startup_code") or ""
if startup_code and not startup_code.endswith("\n"):
startup_code += "\n"
xarray_setup = ""
if data_id in global_state.DATASETS:
xarray_dims = global_state.get_dataset_dim(data_id)
if len(xarray_dims):
xarray_setup = (
"df = ds.sel({selectors}).to_dataframe()\n"
"df = df.reset_index().drop('index', axis=1, errors='ignore')\n"
"df = df.set_index(list(ds.dims.keys()))\n"
).format(
selectors=", ".join(
"{}='{}'".format(k, v) for k, v in xarray_dims.items()
)
)
else:
xarray_setup = (
"df = ds.to_dataframe()\n"
"df = df.reset_index().drop('index', axis=1, errors='ignore')\n"
"df = df.set_index(list(ds.dims.keys()))\n"
)
startup_str = (
"# DISCLAIMER: 'df' refers to the data you passed in when calling 'dtale.show'\n\n"
"{imports}"
"{xarray_setup}"
"{startup}"
"if isinstance(df, (pd.DatetimeIndex, pd.MultiIndex)):\n"
"\tdf = df.to_frame(index=False)\n\n"
"# remove any pre-existing indices for ease of use in the D-Tale code, but this is not required\n"
"df = df.reset_index().drop('index', axis=1, errors='ignore')\n"
"df.columns = [str(c) for c in df.columns] # update columns to strings in case they are numbers\n"
).format(imports=imports, xarray_setup=xarray_setup, startup=startup_code)
final_history = [startup_str] + history
final_query = query
if final_query is None:
final_query = settings.get("query")
if final_query is not None and final_query != "":
if len(ctxt_vars or {}):
final_history.append(
(
"\n# this is injecting any context variables you may have passed into 'dtale.show'\n"
"import dtale.global_state as dtale_global_state\n"
"\n# DISCLAIMER: running this line in a different process than the one it originated will produce\n"
"# differing results\n"
"ctxt_vars = dtale_global_state.get_context_variables('{data_id}')\n\n"
"df = df.query({query}, local_dict=ctxt_vars)\n"
).format(query=triple_quote(final_query), data_id=data_id)
)
else:
final_history.append(
"df = df.query({})\n".format(triple_quote(final_query))
)
elif settings.get("query"):
final_history.append(
"df = df.query({})\n".format(triple_quote(settings["query"]))
)
if "sort" in settings:
cols, dirs = [], []
for col, dir in settings["sort"]:
cols.append(col)
dirs.append("True" if dir == "ASC" else "False")
final_history.append(
"df = df.sort_values(['{cols}'], ascending=[{dirs}])\n".format(
cols=", ".join(cols), dirs="', '".join(dirs)
)
)
return final_history