langchain/libs/community/langchain_community/document_loaders/geodataframe.py

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from typing import Any, Iterator
community[major], core[patch], langchain[patch], experimental[patch]: Create langchain-community (#14463) Moved the following modules to new package langchain-community in a backwards compatible fashion: ``` mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community ``` Moved the following to core ``` mv langchain/langchain/utils/json_schema.py core/langchain_core/utils mv langchain/langchain/utils/html.py core/langchain_core/utils mv langchain/langchain/utils/strings.py core/langchain_core/utils cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py rm langchain/langchain/utils/env.py ``` See .scripts/community_split/script_integrations.sh for all changes
2023-12-11 21:53:30 +00:00
from langchain_core.documents import Document
from langchain_community.document_loaders.base import BaseLoader
class GeoDataFrameLoader(BaseLoader):
"""Load `geopandas` Dataframe."""
def __init__(self, data_frame: Any, page_content_column: str = "geometry"):
"""Initialize with geopandas Dataframe.
Args:
data_frame: geopandas DataFrame object.
page_content_column: Name of the column containing the page content.
Defaults to "geometry".
"""
try:
import geopandas as gpd
except ImportError:
raise ImportError(
"geopandas package not found, please install it with "
"`pip install geopandas`"
)
if not isinstance(data_frame, gpd.GeoDataFrame):
raise ValueError(
f"Expected data_frame to be a gpd.GeoDataFrame, got {type(data_frame)}"
)
if page_content_column not in data_frame.columns:
raise ValueError(
f"Expected data_frame to have a column named {page_content_column}"
)
if not isinstance(data_frame[page_content_column], gpd.GeoSeries):
raise ValueError(
f"Expected data_frame[{page_content_column}] to be a GeoSeries"
)
self.data_frame = data_frame
self.page_content_column = page_content_column
def lazy_load(self) -> Iterator[Document]:
"""Lazy load records from dataframe."""
# assumes all geometries in GeoSeries are same CRS and Geom Type
crs_str = self.data_frame.crs.to_string() if self.data_frame.crs else None
geometry_type = self.data_frame.geometry.geom_type.iloc[0]
for _, row in self.data_frame.iterrows():
geom = row[self.page_content_column]
xmin, ymin, xmax, ymax = geom.bounds
metadata = row.to_dict()
metadata["crs"] = crs_str
metadata["geometry_type"] = geometry_type
metadata["xmin"] = xmin
metadata["ymin"] = ymin
metadata["xmax"] = xmax
metadata["ymax"] = ymax
metadata.pop(self.page_content_column)
# using WKT instead of str() to help GIS system interoperability
yield Document(page_content=geom.wkt, metadata=metadata)