11/25/2023 0 Comments Json to sqlite python![]() As a result, it may be less up-to-date compared to other components in your stack. It's important to be aware that Optimus is currently under active development, and its last official release was in 2020. Moreover, Optimus includes processors designed to handle common real-world data types such as email addresses and URLs. These accessors make various tasks much easier to perform.įor example, you can sort a DataFrame, filter it based on column values, change data using specific criteria, or narrow down operations based on certain conditions. The data manipulation API in Optimus is like Pandas, but it offers more. This is a great practice, if, like me, you’re just starting out with Perl or SQLite, and need a small project to help you feel your way around. You can load from and save back to Arrow, Parquet, Excel, various common database sources, or flat-file formats like CSV and JSON. In this brief post, I’ll show how you can use Perl and SQLite to convert raw JSON data into an SQL Database with multiple tables. Optimus can use Pandas, Dask, CUDF (and Dask + CUDF), Vaex, or Spark as its underlying data engine. Optimus is an all-in-one toolset designed to load, explore, cleanse, and write data back to various data sources. insert_all (, pk = "id" )Ĭheck out the full library documentation for everything else you can do with the Python library.Cleaning and preparing data for DataFrame-centric projects can be one of the less enviable tasks. Database ( "demo_database.db" ) # This line creates a "dogs" table if one does not already exist: db. You can also import sqlite_utils and use it as a Python library like this: import sqlite_utils db = sqlite_utils. See the full CLI documentation for comprehensive coverage of many more commands. Sqlite-utils memory lets you import CSV or JSON data into an in-memory database and run SQL queries against it in a single command: $ cat dogs.csv | sqlite-utils memory - "select name, age from stdin" Or for data in a CSV file: $ sqlite-utils insert dogs.db dogs dogs.csv -csv | sqlite-utils insert releases.db releases -pk id You can import JSON data into a new database table like this: $ curl \ $ sqlite-utils dogs.db "select * from dogs" -table $ sqlite-utils dogs.db "select * from dogs" -csv $ sqlite-utils dogs.db "select id, name from dogs" $ sqlite-utils insert dogs.db dogs dogs.csv -csv Now you can do things with the CLI utility like this: $ sqlite-utils memory dogs.csv "select * from t" Or if you use Homebrew for macOS: brew install sqlite-utils Convert Raw JSON Data into an SQL Database using SQLite and Perl In this brief post, I’ll show how you can use Perl and SQLite to convert raw JSON data into an SQL Database with multiple tables. Read more on my blog, in this series of posts on New features in sqlite-utils and other entries tagged sqliteutils. Extract columns into separate tables to better normalize your existing data.Run transformations against your tables to make schema changes that SQLite ALTER TABLE does not directly support, such as changing the type of a column.Configure SQLite full-text search against your database tables and run search queries against them, ordered by relevance.Run in-memory SQL queries, including joins, directly against data in CSV, TSV or JSON files and view the results.Pipe JSON (or CSV or TSV) directly into a new SQLite database file, automatically creating a table with the appropriate schema. ![]() Python CLI utility and library for manipulating SQLite databases. ![]()
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