operations Package

DataFrame-oriented wrappers for batch record operations.

Provides create, update, and delete that accept pandas.DataFrame / pandas.Series inputs and convert them to standard dicts before enqueueing on the batch. This lets data-science callers feed DataFrames directly into a batch without manual conversion.

Accessed via batch.dataframe.

Example:

   import pandas as pd

   batch = client.batch.new()
   df = pd.DataFrame([
       {"name": "Contoso", "telephone1": "555-0100"},
       {"name": "Fabrikam", "telephone1": "555-0200"},
   ])
   batch.dataframe.create("account", df)
   result = batch.execute()

Namespace for batch operations (client.batch).

Accessed via client.batch. Use new to create a BatchRequest builder.

Example:

   batch = client.batch.new()
   batch.records.create("account", {"name": "Fabrikam"})
   result = batch.execute()

Query operations on a BatchRequest.

Mirrors client.query exactly: same method names, same signatures. All methods return None; results arrive via BatchResult.

Do not instantiate directly; use batch.query.

Record operations on a BatchRequest.

Mirrors client.records: same method names, same signatures. All methods return None; results are available via BatchResult after execute.

GA methods: retrieve (single record) and list (multi-record, single page). get is deprecated — use retrieve instead.

Do not instantiate directly; use batch.records.

Builder for constructing and executing a Dataverse OData $batch request.

Obtain via new (client.batch.new()). Add operations through records, tables, query, and dataframe, optionally group writes into a changeset, then call execute.

Operations are executed sequentially in the order added. The resulting BatchResult contains one BatchItemResponse per HTTP request dispatched (some operations expand to multiple requests).

Example:

   batch = client.batch.new()
   batch.records.create("account", {"name": "Contoso"})
   batch.tables.get("account")
   with batch.changeset() as cs:
       ref = cs.records.create("contact", {"firstname": "Alice"})
       cs.records.update("account", account_id, {
           "primarycontactid@odata.bind": ref
       })
   result = batch.execute()

Table metadata operations on a BatchRequest.

Mirrors client.tables exactly: same method names, same signatures. All methods return None; results arrive via BatchResult.

Do not instantiate directly; use batch.tables.

A transactional group of single-record write operations.

All operations succeed or are rolled back together. Use as a context manager or call records to add operations directly.

Do not instantiate directly; use changeset.

Example:

   with batch.changeset() as cs:
       ref = cs.records.create("contact", {"firstname": "Alice"})
       cs.records.update("account", account_id, {
           "primarycontactid@odata.bind": ref
       })

Record write operations available inside a ChangeSet.

Mirrors client.records but restricted to single-record forms (no bulk create/update/delete). Only write operations are allowed — GET is not permitted inside a changeset.

Do not instantiate directly; use ChangeSet.records.

Namespace for pandas DataFrame CRUD operations.

Accessed via client.dataframe. Provides DataFrame-oriented wrappers around the record-level CRUD operations.

Example:

   import pandas as pd

   client = DataverseClient(base_url, credential)

   # Query records as a DataFrame
   df = client.dataframe.get("account", select=["name"], top=100)

   # Create records from a DataFrame
   new_df = pd.DataFrame([{"name": "Contoso"}, {"name": "Fabrikam"}])
   new_df["accountid"] = client.dataframe.create("account", new_df)

   # Update records
   new_df["telephone1"] = ["555-0100", "555-0200"]
   client.dataframe.update("account", new_df, id_column="accountid")

   # Delete records
   client.dataframe.delete("account", new_df["accountid"])

Namespace for file operations.

Accessed via client.files. Provides file upload operations for Dataverse file columns.

Example:

   client = DataverseClient(base_url, credential)

   client.files.upload(
       "account", account_id, "new_Document", "/path/to/file.pdf"
   )

Namespace for query operations.

Accessed via client.query. Provides query and search operations against Dataverse tables.

Example:

   from PowerPlatform.Dataverse.models.filters import col

   client = DataverseClient(base_url, credential)

   # Fluent query builder (recommended)
   for record in (client.query.builder("account")
                  .select("name", "revenue")
                  .where(col("statecode") == 0)
                  .order_by("revenue", descending=True)
                  .top(100)
                  .execute()):
       print(record["name"])

   # SQL query
   rows = client.query.sql("SELECT TOP 10 name FROM account ORDER BY name")
   for row in rows:
       print(row["name"])

Namespace for record-level CRUD operations.

Accessed via client.records. Provides create, update, delete, and get operations on individual Dataverse records.

Example:

   client = DataverseClient(base_url, credential)

   # Create a single record
   guid = client.records.create("account", {"name": "Contoso Ltd"})

   # Get a record
   record = client.records.get("account", guid, select=["name"])

   # Update a record
   client.records.update("account", guid, {"telephone1": "555-0100"})

   # Delete a record
   client.records.delete("account", guid)

Namespace for table-level metadata operations.

Accessed via client.tables. Provides operations to create, delete, inspect, and list Dataverse tables, as well as add and remove columns.

Example:

   client = DataverseClient(base_url, credential)

   # Create a table
   info = client.tables.create(
       "new_Product",
       {"new_Price": "decimal", "new_InStock": "bool"},
       solution="MySolution",
   )

   # List tables
   tables = client.tables.list()

   # Get table info
   info = client.tables.get("new_Product")

   # Add columns
   client.tables.add_columns("new_Product", {"new_Rating": "int"})

   # Remove columns
   client.tables.remove_columns("new_Product", "new_Rating")

   # Delete a table
   client.tables.delete("new_Product")