Migration from local files to database made simple!
Project description
files-2-db
Uploading data from files to database made easy!
Background
Importing a file from your local machine into a database which is in a remote server is painful process. The exact same process can be done through a command now.
Current implementation
- File formats supported -
.csv
- Database engines supported -
mysql
Usage
The tool can be used in two ways.
-
Through command line, where you do not even need a python script to be created.
usage: file2db [-h] --host HOST [--port PORT] --user USER --password PASSWORD --database DATABASE --table TABLE [--seperator SEPERATOR] [--ignore_errors IGNORE_ERRORS] [--n_rows N_ROWS] Source-file Target-database file2db - Transfer of data from your local file to Database, made simple. positional arguments: Source-file Absolute path of the file to be uploaded, with suffix Target-database Target database where the file has to be uploaded options: -h, --help show this help message and exit --host HOST URL or IP address representation of database host --port PORT Port number to connect to the database --user USER Username for database authentication --password PASSWORD Password for database authentication --database DATABASE Target database --table TABLE Target table to insert the data --seperator SEPERATOR Column seperator in the file --ignore_errors IGNORE_ERRORS Try to keep reading lines if some lines yield errors. default value -> False --n_rows N_ROWS Number of rows from the file to be inserted to database. Default -> all
-
Otherwise, you can access the
ingest_data_from_file
API of the module. It takes the same set of parameters to the API in the below format,def ingest_data_from_file( file_path: str, target_database: str, db_host: str, db_port: int, db_user: str, db_password: str, data_db: str, data_table: str, file_seperator: str, ignore_file_errors: bool, n_rows_to_insert: int, ) -> None: ...
Roadmap
In upcoming versions, files2db
will support commonly used file formats like, .json
, .parquet
, .tsv
, .xlsx
, .arrow
and the databases, not limited to, postgresql
, sqlite
, MSSQL
and what not.
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