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Here is a work-around that uses an in-memory SQLite database to generate the schema:
using DataFrames, SQLite, LibPQ
# An example test dataframe:
df = DataFrame(A = 1:3, B = [2.0, -1.1, 2.8], C = ["p","q","r"])
# Get the table schema:
table_sch = Tables.schema(df)
# Create an in-memory SQLite database:
db = SQLite.DB()
# Just create the schema in the SQLite database:
SQLite.createtable!(db, "mytable", Tables.schema(df))
# Now get back the generated SQL CREATE statement:
res = DataFrame(DBInterface.execute(db, "SELECT sql FROM sqlite_master;"))
# alternative to just get a specific name:
# res = DataFrame(DBInterface.execute(db, "SELECT * FROM sqlite_master WHERE name='mytable';"))
str = res[1,:sql] # or change the first index of `1` to other indices (e.g for multiple tables)
# Now use the string to create a table in LibPQ:
conn = LibPQ.Connection("dbname=postgres") # replace postgres with your db name.
result = LibPQ.execute(conn, str)
and from here, you can use the function from this post
to load the table into the database:
load_table!(conn, df, "mytable")