├── tests ├── __init__.py ├── conftest.py ├── test_deltabase_workflow.py ├── test_magic.ipynb └── test_deltabase.py ├── .python-version ├── docs ├── assets │ ├── css │ │ └── extra.css │ ├── logo.png │ ├── favicon.png │ └── banner.svg ├── errors.md ├── checkout.md ├── configure.md ├── delete.md ├── commit.md ├── sql_context.md ├── index.md ├── upsert.md ├── register.md └── connect.md ├── .devcontainer ├── dockerfile └── devcontainer.json ├── .gitignore ├── pyproject.toml ├── mkdocs.yml ├── deltabase ├── magic.py └── __init__.py ├── README.md ├── requirements.txt ├── examples └── magic.ipynb └── LICENSE /tests/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /.python-version: -------------------------------------------------------------------------------- 1 | 3.11.6 2 | -------------------------------------------------------------------------------- /docs/assets/css/extra.css: -------------------------------------------------------------------------------- 1 | :root { 2 | --md-code-font: "Verdana"; 3 | } -------------------------------------------------------------------------------- /docs/assets/logo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/uname-n/deltabase/HEAD/docs/assets/logo.png -------------------------------------------------------------------------------- /docs/assets/favicon.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/uname-n/deltabase/HEAD/docs/assets/favicon.png -------------------------------------------------------------------------------- /.devcontainer/dockerfile: -------------------------------------------------------------------------------- 1 | ARG VARIANT="3.10-bullseye" 2 | FROM mcr.microsoft.com/vscode/devcontainers/python:0-${VARIANT} 3 | 4 | -------------------------------------------------------------------------------- /tests/conftest.py: -------------------------------------------------------------------------------- 1 | from shutil import rmtree 2 | from os.path import exists 3 | 4 | def pytest_sessionfinish(session, exitstatus): 5 | if exists("test.delta"): rmtree("test.delta") -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | .venv/ 2 | *.delta/ 3 | dist 4 | __pycache__ 5 | .pytest_cache 6 | _playground.* 7 | *.db 8 | .DS_Store 9 | docs/build/ 10 | site/ 11 | .env 12 | *.txt 13 | examples/delta -------------------------------------------------------------------------------- /docs/errors.md: -------------------------------------------------------------------------------- 1 | If any errors occur during operations, they are returned by the methods as exceptions. Handle these exceptions to debug or manage issues in your workflows. 2 | 3 | ```python 4 | try: 5 | db.commit(database="mydatabase", table="mytable") 6 | except Exception as e: 7 | print(f"Error: {e}") 8 | ``` 9 | 10 | --- -------------------------------------------------------------------------------- /docs/checkout.md: -------------------------------------------------------------------------------- 1 | To revert to a previous version of a table, use the `checkout` method. This allows you to load historical data or restore a previous state. 2 | 3 | ```python 4 | db.checkout(database="mydatabase", table="mytable", version=1) 5 | db.checkout(database="mydatabase", table="mytable", version="2024-01-01") 6 | db.checkout(database="mydatabase", table="mytable", version=datetime(2024, 1, 1)) 7 | ``` 8 | 9 | --- 10 | -------------------------------------------------------------------------------- /docs/configure.md: -------------------------------------------------------------------------------- 1 | You can configure the Delta instance to output different data formats by setting the `dtype` attribute of the configuration object. The default format is `json`, but you can change it to `polars` for better performance or other formats as needed. 2 | 3 | ```python 4 | from deltabase import delta 5 | 6 | db:delta = delta.connect(path="local_path/mydelta") 7 | db.config.dtype = "polars" 8 | ``` 9 | 10 | --- 11 | -------------------------------------------------------------------------------- /docs/delete.md: -------------------------------------------------------------------------------- 1 | To delete records from a table or remove a table from the SQL context, use the `delete` method. You can delete specific records based on a condition or remove all records. 2 | 3 | ```python 4 | # delete records with sql condition 5 | db.delete(table="mytable", filter="name='bob'") 6 | 7 | # delete records using a lambda function 8 | db.delete(table="mytable", filter=lambda row: row["name"] == "sam") 9 | 10 | # delete table from sql context 11 | db.delete(table="mytable") 12 | ``` 13 | 14 | --- 15 | -------------------------------------------------------------------------------- /docs/commit.md: -------------------------------------------------------------------------------- 1 | To persist changes made in the SQL context back to the delta source, use the `commit` method. You can enforce schema changes or partition your data during the commit process. 2 | 3 | ```python 4 | db.commit(database="mydatabase", table="mytable") 5 | ``` 6 | 7 | --- 8 | 9 | > `#!python db.commit(..., force=True)` 10 | 11 | Force schema changes when committing data to the delta source. 12 | 13 | --- 14 | 15 | > `#!python db.commit(..., partition_by=["job"])` 16 | 17 | Partition the table by one or more columns when committing data. 18 | 19 | --- 20 | -------------------------------------------------------------------------------- /docs/sql_context.md: -------------------------------------------------------------------------------- 1 | You can run SQL queries against your registered tables using the `sql` method. This allows you to interact with your data using standard SQL syntax. 2 | 3 | ```python 4 | db.sql("select * from mytable") 5 | ``` 6 | 7 | --- 8 | 9 | > `#!python db.sql("select * from mytable", dtype="polars")` 10 | 11 | You can specify the output format of the query using the `dtype` parameter, such as `polars` for fast data processing. 12 | 13 | --- 14 | 15 | > `#!python db.sql("select * from mytable", lazy=True)` 16 | 17 | If you prefer to defer execution, you can return a LazyFrame by setting the `lazy` parameter to `True`. 18 | 19 | --- 20 | -------------------------------------------------------------------------------- /.devcontainer/devcontainer.json: -------------------------------------------------------------------------------- 1 | { 2 | "name": "deltabase", 3 | "build":{ 4 | "dockerfile": "dockerfile", 5 | "context": ".", 6 | "args": { 7 | "VARIANT": "3.11-bullseye" 8 | } 9 | }, 10 | 11 | "features": { 12 | "github-cli": "latest" 13 | }, 14 | 15 | "postCreateCommand": "bash ./.devcontainer/post-install.sh", 16 | 17 | "customizations": { 18 | "vscode": { 19 | "extensions": [ 20 | "ms-vscode.cpptools-themes", 21 | "ms-toolsai.jupyter", 22 | "ms-python.python" 23 | ], 24 | "settings": { 25 | "workbench.colorTheme": "Visual Studio 2017 Dark - C++" 26 | } 27 | } 28 | }, 29 | 30 | "remoteUser": "vscode" 31 | } 32 | -------------------------------------------------------------------------------- /docs/index.md: -------------------------------------------------------------------------------- 1 | # Getting Started 2 | 3 | ## Install 4 | To install **DeltaBase**, run the following command: 5 | ```bash 6 | pip install deltabase 7 | ``` 8 | 9 | ## Quick Start 10 | ```python 11 | from deltabase import delta 12 | 13 | # connect to a delta source 14 | db:delta = delta.connect(path="mydelta") 15 | 16 | # upsert records into a table 17 | db.upsert(table="mytable", primary_key="id", data=[ 18 | {"id": 1, "name": "alice"} 19 | ]) 20 | 21 | # commit table to delta source 22 | db.commit(table="mytable") 23 | 24 | # read records from sql context 25 | result = db.sql("select * from mytable") 26 | print(result) # output: [{"id": 1, "name": "alice"}] 27 | ``` -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [tool.poetry] 2 | name = "deltabase" 3 | version = "1.1.0" 4 | description = "" 5 | authors = ["uname-n "] 6 | readme = "README.md" 7 | packages = [{include = "deltabase"}] 8 | 9 | [tool.poetry.dependencies] 10 | python = "^3.11" 11 | polars = "^1.6.0" 12 | deltalake = "^0.19.0" 13 | ipython = {version="^8.26.0", optional=true} 14 | openai = {version="^1.43.0", optional=true} 15 | 16 | [tool.poetry.group.dev.dependencies] 17 | pytest = "^8.3.2" 18 | mkdocs = "^1.6.0" 19 | mkdocs-material = "^9.5.31" 20 | ipykernel = "^6.29.5" 21 | pandas = "^2.2.2" 22 | 23 | [tool.poetry.extras] 24 | magic = ["ipython"] 25 | ai = ["ipython", "openai"] 26 | 27 | [build-system] 28 | requires = ["poetry-core"] 29 | build-backend = "poetry.core.masonry.api" 30 | -------------------------------------------------------------------------------- /docs/upsert.md: -------------------------------------------------------------------------------- 1 | To insert new records or update existing records in a table, use the `upsert` method. This method allows you to keep your data synchronized while managing schema changes automatically. 2 | 3 | --- 4 | 5 | Insert or update a single record: 6 | 7 | ```python 8 | db.upsert(database="mydatabase", table="mytable", primary_key="id", data={ 9 | "id": 1, 10 | "name": "alice" 11 | }) 12 | ``` 13 | 14 | --- 15 | 16 | Insert or update multiple records at once: 17 | 18 | ```python 19 | db.upsert(database="mydatabase", table="mytable", primary_key="id", data=[ 20 | {"id": 1, "name": "ali"}, 21 | {"id": 2, "name": "bob", "job": "chef"}, 22 | {"id": 3, "name": "sam"}, 23 | ]) 24 | ``` 25 | 26 | --- 27 | 28 | > `#!python db.upsert(..., data=DataFrame([{"id": 1, "name": "ali"}]))` 29 | 30 | You can upsert data directly from a DataFrame. 31 | 32 | --- 33 | 34 | > `#!python db.upsert(..., data=LazyFrame([{"id": 1, "name": "ali"}]))` 35 | 36 | Or, upsert data using a LazyFrame for more efficient operations. 37 | 38 | --- 39 | -------------------------------------------------------------------------------- /docs/register.md: -------------------------------------------------------------------------------- 1 | To load or register a table in the SQL context from a delta source, use the `register` method. You can register tables from the delta source, load a specific version, or register a DataFrame or LazyFrame directly. 2 | 3 | --- 4 | 5 | Register a table from a specific database in the delta source: 6 | 7 | ```python 8 | db.register(database="mydatabase", table="mytable") 9 | ``` 10 | 11 | --- 12 | 13 | > `#!python db.register(..., alias="table")` 14 | 15 | You can assign an alias to the registered table within the SQL context for easier reference. 16 | 17 | --- 18 | 19 | > `#!python db.register(..., version=1)` 20 | 21 | Load a specific version of the table by specifying the version number. 22 | 23 | --- 24 | 25 | > `#!python db.register(..., data=...)` 26 | 27 | Register a DataFrame or LazyFrame directly instead of loading it from the Delta source. 28 | 29 | --- 30 | 31 | > `#!python db.register(..., pyarrow_options={"partitions": [("year", "=", "2021")]})` 32 | 33 | Use `pyarrow_options` to specify partition filters or other advanced options when loading the table. 34 | 35 | --- 36 | -------------------------------------------------------------------------------- /docs/connect.md: -------------------------------------------------------------------------------- 1 | To connect to a delta source instance, use the `connect` method provided by the `delta` class. This method allows you to connect to either a local file path or a remote cloud storage service (such as AWS S3, Azure Data Lake, or Google Cloud Storage). The method returns an instance of the `delta` class, which you can use to manage your Delta tables. 2 | 3 | ```python 4 | from deltabase import delta 5 | 6 | db:delta = delta.connect(path="local_path/mydelta") 7 | ``` 8 | 9 | --- 10 | 11 | > on connect, delta will attempt to load tables if path is local. 12 | 13 | --- 14 | 15 | > `#!python db:delta = delta.connect(path="s3://")` 16 | 17 | You can also connect to a delta source stored in an AWS S3 bucket. Replace `` with the actual bucket name and path. 18 | 19 | --- 20 | 21 | > `#!python db:delta = delta.connect(path="://")` 22 | 23 | For Azure, you can connect to an Azure Data Lake Storage (ADLS) or Azure Blob Storage using the appropriate URI scheme (`az://`, `adl://`, or `abfs[s]://`). 24 | 25 | --- 26 | 27 | > `#!python db:delta = delta.connect(path="gs://")` 28 | 29 | For Google Cloud Storage, use the `gs://` prefix followed by the bucket name and path. 30 | 31 | --- 32 | -------------------------------------------------------------------------------- /mkdocs.yml: -------------------------------------------------------------------------------- 1 | site_name: DeltaBase 2 | 3 | nav: 4 | - Getting Started: index.md 5 | - Connect: connect.md 6 | - Configure: configure.md 7 | - Register: register.md 8 | - Upsert: upsert.md 9 | - SQL Context: sql_context.md 10 | - Delete: delete.md 11 | - Commit: commit.md 12 | - Checkout: checkout.md 13 | - Errors: errors.md 14 | 15 | theme: 16 | name: material 17 | logo: assets/logo.png 18 | favicon: assets/favicon.png 19 | features: 20 | - navigation.sections 21 | - toc.integrate 22 | - navigation.top 23 | - search.suggest 24 | - search.highlight 25 | - content.code.annotate 26 | - content.code.copy 27 | language: en 28 | palette: 29 | # Palette toggle for automatic mode 30 | - media: "(prefers-color-scheme)" 31 | toggle: 32 | icon: material/brightness-auto 33 | name: Switch to light mode 34 | 35 | # Palette toggle for light mode 36 | - media: "(prefers-color-scheme: light)" 37 | scheme: default 38 | toggle: 39 | icon: material/brightness-7 40 | name: Switch to dark mode 41 | primary: blue grey 42 | accent: light blue 43 | 44 | # Palette toggle for dark mode 45 | - media: "(prefers-color-scheme: dark)" 46 | scheme: slate 47 | toggle: 48 | icon: material/brightness-4 49 | name: Switch to system preference 50 | primary: blue grey 51 | accent: light blue 52 | 53 | markdown_extensions: 54 | - pymdownx.highlight: 55 | anchor_linenums: true 56 | line_spans: __span 57 | pygments_lang_class: true 58 | - pymdownx.inlinehilite 59 | - pymdownx.snippets 60 | - pymdownx.superfences 61 | - pymdownx.snippets 62 | - pymdownx.details 63 | - pymdownx.mark 64 | - pymdownx.betterem 65 | -------------------------------------------------------------------------------- /tests/test_deltabase_workflow.py: -------------------------------------------------------------------------------- 1 | import pytest 2 | 3 | from deltabase import delta 4 | 5 | from polars import DataFrame 6 | from os.path import exists 7 | from os import listdir 8 | from time import time 9 | 10 | TIMEOUT = 20 11 | W = 1_000 12 | H = 1_000 13 | 14 | data = lambda w, h: [{"name":f"name_{_}", **{f"field_{n}":n+_ for n in range(w)}} for _ in range(h)] 15 | testing_data = data(W, H) 16 | 17 | @pytest.fixture 18 | def db(): 19 | return delta.connect(path="test.delta") 20 | 21 | def test_connect(db): 22 | assert isinstance(db, delta) 23 | assert db.tables == [] 24 | 25 | def test_add_data(db): 26 | s = time() 27 | err = db.upsert(table="test_table", primary_key="name", data=testing_data) 28 | assert not err, err 29 | e = time() 30 | result = db.sql("select * from test_table", dtype="polars") 31 | 32 | assert isinstance(result, DataFrame) 33 | assert result.shape == (W, H+1) 34 | assert (e-s) < TIMEOUT 35 | 36 | def test_first_commit(db): 37 | err = db.commit("test_table") 38 | assert not err, err 39 | 40 | assert exists("test.delta/default/test_table") 41 | assert len(listdir("test.delta/default/test_table")) == 2 42 | assert len(listdir("test.delta/default/test_table/_delta_log")) == 1 43 | 44 | def test_delete_records(db): 45 | err = db.delete("test_table", filter="field_6 % 2 == 0") 46 | assert not err, err 47 | 48 | result = db.sql("select * from test_table", dtype="polars") 49 | assert 0 < result.shape[0] < W 50 | assert result.shape[1] == H+1 51 | 52 | def test_second_commit(db): 53 | err = db.commit("test_table") 54 | assert not err, err 55 | 56 | assert len(listdir("test.delta/default/test_table")) == 3 57 | assert len(listdir("test.delta/default/test_table/_delta_log")) == 2 58 | 59 | def test_checkout_original_commit(db): 60 | err = db.checkout("test_table", version=1) 61 | assert not err, err 62 | 63 | result = db.sql("select * from test_table", dtype="polars") 64 | 65 | assert isinstance(result, DataFrame) 66 | assert result.shape == (W, H+1) -------------------------------------------------------------------------------- /deltabase/magic.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | # -*- coding: utf-8 -*- 3 | 4 | # Copyright 2024 darryl mcculley 5 | 6 | # This program is free software: you can redistribute it and/or modify 7 | # it under the terms of the GNU General Public License as published by 8 | # the Free Software Foundation, either version 3 of the License, or 9 | # any later version. 10 | 11 | # This program is distributed in the hope that it will be useful, 12 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 13 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 14 | # GNU General Public License for more details. 15 | 16 | # You should have received a copy of the GNU General Public License 17 | # along with this program. If not, see . 18 | 19 | try: 20 | from IPython.core.magic import Magics, magics_class, cell_magic, line_magic 21 | from IPython.display import Markdown, display 22 | from IPython import get_ipython 23 | except ImportError: 24 | raise ImportError("`deltabase[magic]` package required for magic.") 25 | 26 | from . import delta 27 | 28 | from json import dumps 29 | 30 | @magics_class 31 | class magic (Magics): 32 | def __init__(self, shell, delta:delta): 33 | super(magic, self).__init__(shell) 34 | self.__openai_chat_history = [] 35 | self.delta = delta 36 | 37 | @cell_magic 38 | def sql(self, line, cell): 39 | data = self.delta.sql(query=cell, dtype="polars") 40 | 41 | args = line.split(" ") 42 | if "--table" in line and "--key" in line: 43 | table = args[args.index("--table")+1] 44 | key = args[args.index("--key")+1] 45 | if "--database" in line: database = args[args.index("--upsert")+1] 46 | else: database = "default" 47 | self.delta.upsert(database=database, table=table, primary_key=key, data=data) 48 | 49 | return data 50 | 51 | @cell_magic 52 | def ai(self, line, cell): 53 | try: from openai import OpenAI 54 | except: raise ImportError("`deltabase[ai]` package required for `ai` magic.") 55 | client = OpenAI() 56 | 57 | context = "" 58 | for table in self.delta.tables: 59 | schema = self.delta.schema(table=table) 60 | if schema: context += f"- {table}: {schema}\n" 61 | 62 | messages = [ 63 | {"role": "system", "content": ( 64 | "answer the user's question. " 65 | "below is the data they have access to." 66 | "data can be accessed via sql.\n" 67 | )}, 68 | {"role": "system", "content": f"here is the data available to the user.\n" + context} 69 | ] 70 | 71 | for question, answer in self.__openai_chat_history: 72 | messages.append({"role": "user", "content":question}) 73 | messages.append({"role": "assistant", "content":answer}) 74 | messages.append({"role": "user", "content":cell}) 75 | 76 | if "--debug" in line: return display(Markdown(f"```json\n{dumps(messages, indent=4)}\n```")) 77 | 78 | completion = client.chat.completions.create( 79 | model=self.delta.config.ai_model, 80 | messages=messages 81 | ) 82 | 83 | response = completion.choices[0].message.content 84 | self.__openai_chat_history.append((cell, response)) 85 | return display(Markdown(response)) 86 | 87 | @line_magic 88 | def ai_chat(self, line): 89 | match line: 90 | case "clear": self.__openai_chat_history = [] 91 | case "undo": self.__openai_chat_history.pop() 92 | 93 | def enable(delta:delta): 94 | ipython = get_ipython() 95 | if ipython: ipython.register_magics(magic(ipython, delta)) -------------------------------------------------------------------------------- /tests/test_magic.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "from deltabase import delta\n", 10 | "\n", 11 | "db:delta = delta.connect(\"path\")" 12 | ] 13 | }, 14 | { 15 | "cell_type": "code", 16 | "execution_count": 2, 17 | "metadata": {}, 18 | "outputs": [], 19 | "source": [ 20 | "db.upsert(\"mytable\", \"id\", {\"id\":1, \"name\":\"jim\"})" 21 | ] 22 | }, 23 | { 24 | "cell_type": "code", 25 | "execution_count": 3, 26 | "metadata": { 27 | "vscode": { 28 | "languageId": "sql" 29 | } 30 | }, 31 | "outputs": [ 32 | { 33 | "data": { 34 | "text/html": [ 35 | "
\n", 42 | "shape: (1, 2)
idname
i64str
1"jim"
" 43 | ], 44 | "text/plain": [ 45 | "shape: (1, 2)\n", 46 | "┌─────┬──────┐\n", 47 | "│ id ┆ name │\n", 48 | "│ --- ┆ --- │\n", 49 | "│ i64 ┆ str │\n", 50 | "╞═════╪══════╡\n", 51 | "│ 1 ┆ jim │\n", 52 | "└─────┴──────┘" 53 | ] 54 | }, 55 | "execution_count": 3, 56 | "metadata": {}, 57 | "output_type": "execute_result" 58 | } 59 | ], 60 | "source": [ 61 | "%%sql --table newtable --key id\n", 62 | "select * from mytable" 63 | ] 64 | }, 65 | { 66 | "cell_type": "code", 67 | "execution_count": 4, 68 | "metadata": {}, 69 | "outputs": [ 70 | { 71 | "data": { 72 | "text/plain": [ 73 | "['mytable', 'newtable']" 74 | ] 75 | }, 76 | "execution_count": 4, 77 | "metadata": {}, 78 | "output_type": "execute_result" 79 | } 80 | ], 81 | "source": [ 82 | "db.tables" 83 | ] 84 | }, 85 | { 86 | "cell_type": "code", 87 | "execution_count": 5, 88 | "metadata": {}, 89 | "outputs": [], 90 | "source": [ 91 | "db.upsert(\"mytable\", \"id\", {\"id\":1, \"name\":\"jimbob\"})\n", 92 | "db.upsert(\"mytabl1\", \"id\", {\"id\":1, \"name\":\"jimbob\"})\n", 93 | "db.upsert(\"mytabl2\", \"id\", {\"id\":1, \"name\":\"jimbob\"})\n", 94 | "db.upsert(\"mytabl3\", \"id\", {\"id\":1, \"name\":\"jimbob\"})\n", 95 | "db.upsert(\"mytabl4\", \"id\", {\"id\":1, \"name\":\"jimbob\"})" 96 | ] 97 | }, 98 | { 99 | "cell_type": "code", 100 | "execution_count": 6, 101 | "metadata": {}, 102 | "outputs": [ 103 | { 104 | "data": { 105 | "text/markdown": [ 106 | "```json\n", 107 | "[\n", 108 | " {\n", 109 | " \"role\": \"system\",\n", 110 | " \"content\": \"answer the user's question. below is the data they have access to.data can be accessed via sql.\\n\"\n", 111 | " },\n", 112 | " {\n", 113 | " \"role\": \"system\",\n", 114 | " \"content\": \"here is the data available to the user.\\n- mytabl1: {'id': , 'name': }\\n- mytabl2: {'id': , 'name': }\\n- mytabl3: {'id': , 'name': }\\n- mytabl4: {'id': , 'name': }\\n- mytable: {'id': , 'name': }\\n- newtable: {'id': , 'name': }\\n\"\n", 115 | " },\n", 116 | " {\n", 117 | " \"role\": \"user\",\n", 118 | " \"content\": \"describe the data available to me.\\n\"\n", 119 | " }\n", 120 | "]\n", 121 | "```" 122 | ], 123 | "text/plain": [ 124 | "" 125 | ] 126 | }, 127 | "metadata": {}, 128 | "output_type": "display_data" 129 | } 130 | ], 131 | "source": [ 132 | "%%ai --debug\n", 133 | "describe the data available to me." 134 | ] 135 | } 136 | ], 137 | "metadata": { 138 | "kernelspec": { 139 | "display_name": ".venv", 140 | "language": "python", 141 | "name": "python3" 142 | }, 143 | "language_info": { 144 | "codemirror_mode": { 145 | "name": "ipython", 146 | "version": 3 147 | }, 148 | "file_extension": ".py", 149 | "mimetype": "text/x-python", 150 | "name": "python", 151 | "nbconvert_exporter": "python", 152 | "pygments_lexer": "ipython3", 153 | "version": "3.12.2" 154 | } 155 | }, 156 | "nbformat": 4, 157 | "nbformat_minor": 2 158 | } 159 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 |

2 | banner 3 |

4 | 5 |

6 | documentation (wip) 7 |

8 | 9 | **DeltaBase** is a lightweight, comprehensive solution for managing Delta Tables in both local and cloud environments. Built on the high-performance frameworks [**polars**](https://github.com/pola-rs/polars) and [**deltalake**](https://github.com/delta-io/delta-rs), DeltaBase streamlines data operations with features like upsert, delete, commit, and version control. Designed for data engineers, analysts, and developers, it ensures data consistency, efficient versioning, and seamless integration into your workflows. 10 | 11 | ## Installation 12 | To install **DeltaBase**, run the following command: 13 | ```bash 14 | pip install deltabase 15 | ``` 16 | 17 | ## Quick Start 18 | ```python 19 | from deltabase import delta 20 | 21 | # connect to a delta source 22 | db:delta = delta.connect(path="mydelta") 23 | 24 | # upsert records into a table 25 | db.upsert(table="mytable", primary_key="id", data=[ 26 | {"id": 1, "name": "alice"} 27 | ]) 28 | 29 | # commit table to delta source 30 | db.commit(table="mytable") 31 | 32 | # read records from sql context 33 | result = db.sql("select * from mytable") 34 | print(result) # output: [{"id": 1, "name": "alice"}] 35 | ``` 36 | 37 | See a full example of **DeltaBase** in action [here](https://github.com/uname-n/deltabase/blob/master/examples/magic.ipynb). 38 | 39 | ## Usage 40 | 41 | ### Connecting to a Delta Source 42 | Establish a connection to your Delta source, whether it's a local directory or remote cloud storage. 43 | 44 | ```python 45 | from deltabase import delta 46 | 47 | db = delta.connect(path="local_path/mydelta") 48 | db = delta.connect(path="s3://your-bucket/path") 49 | db = delta.connect(path="az://your-container/path") 50 | db = delta.connect(path="abfs[s]://your-container/path") 51 | ``` 52 | 53 | ### Register Tables 54 | Load tables into the SQL context from the Delta source using the `register` method. You can also register data directly from a DataFrame or specify options like version and alias. 55 | 56 | ```python 57 | # load existing table from delta 58 | db.register(table="mytable") 59 | 60 | # load under an alias 61 | db.register(table="mytable", alias="table_alias") 62 | 63 | # load a specific version 64 | db.register(table="mytable", version=1) 65 | 66 | # load data directly 67 | data = DataFrame([{"id": 1, "name": "Alice"}]) 68 | db.register(table="mytable", data=data) 69 | 70 | # load with pyarrow options 71 | db.register( 72 | table="mytable", 73 | pyarrow_options={"partitions": [("year", "=", "2021")]} 74 | ) 75 | ``` 76 | 77 | ### Running SQL Queries 78 | Execute SQL queries against your registered tables using the `sql` method. 79 | 80 | ```python 81 | # run a query and get the result in json format 82 | result = db.sql("select * from mytable") 83 | 84 | # get the result as a polars dataframe 85 | result = db.sql("select * from mytable", dtype="polars") 86 | 87 | # return a LazyFrame for deferred execution 88 | result = db.sql("select * from mytable", lazy=True) 89 | ``` 90 | 91 | ### Upserting Data 92 | Insert new records or update existing ones using the `upsert` method. It automatically handles schema changes and efficiently synchronizes data. 93 | 94 | ```python 95 | # upsert a single record 96 | db.upsert( 97 | table="mytable", 98 | primary_key="id", 99 | data={"id": 1, "name": "Alice"} 100 | ) 101 | 102 | # upsert multiple records 103 | db.upsert( 104 | table="mytable", 105 | primary_key="id", 106 | data=[ 107 | {"id": 2, "name": "Bob", "job": "Chef"}, 108 | {"id": 3, "name": "Sam"}, 109 | ] 110 | ) 111 | 112 | # upsert dataframes 113 | data = DataFrame([{"id": 4, "name": "Dave"}]) 114 | db.upsert(table="mytable", primary_key="id", data=data) 115 | 116 | # upsert lazyframes 117 | data = LazyFrame([{"id": 5, "name": "Eve"}]) 118 | db.upsert(table="mytable", primary_key="id", data=data) 119 | ``` 120 | 121 | ### Committing Changes 122 | Persist changes made in the SQL context back to the Delta source using the `commit` method. You can enforce schema changes or partition your data during this process. 123 | 124 | 125 | ```python 126 | db.commit(table="mytable") 127 | db.commit(table="mytable", force=True) 128 | db.commit(table="mytable", partition_by=["job"]) 129 | ``` 130 | 131 | ### Deleting Data 132 | Remove records from a table or delete the table from the SQL context using the delete method. 133 | 134 | ```python 135 | # delete records using a sql condition 136 | db.delete(table="mytable", filter="name='Bob'") 137 | 138 | # delete records using a lambda function 139 | db.delete(table="mytable", filter=lambda row: row["name"] == "Sam") 140 | 141 | # delete table from sql context 142 | db.delete(table="mytable") 143 | ``` 144 | 145 | ### Checking Out Previous Versions 146 | Revert to a previous version of a table using the `checkout` method. This is useful for loading historical data or restoring a previous state. 147 | 148 | ```python 149 | # get a specific version by number 150 | db.checkout(table="mytable", version=1) 151 | 152 | # get out a version by date string 153 | db.checkout(table="mytable", version="2024-01-01") 154 | 155 | # get out a version by datetime object 156 | db.checkout(table="mytable", version=datetime(2024, 1, 1)) 157 | ``` 158 | 159 | ### Configuring Output Data Types 160 | Set the output data format by adjusting the `dtype` attribute in the configuration object. The default format is `json`. 161 | 162 | ```python 163 | # set output data type to polars dataframe 164 | db.config.dtype = "polars" 165 | 166 | # run a sql query and get results as polars dataframe 167 | result = db.sql("SELECT * FROM mytable") 168 | ``` 169 | 170 | ### Jupyter Notebook Magic 171 | **DeltaBase** provides magic commands for use in Jupyter notebooks, enhancing your interactive data exploration experience. Magic commands are automatically enabled when you connect to delta source within a notebook. 172 | 173 | #### Using SQL Magic 174 | ```sql 175 | %%sql 176 | select * from mytable 177 | ``` 178 | 179 | #### Using AI Magic 180 | ```sql 181 | %%ai 182 | what data is available to me? 183 | ``` -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | deltalake==0.19.0 ; python_version >= "3.12" and python_version < "4.0" \ 2 | --hash=sha256:0783ce640ee97842280953bd6923200262d29d980b53530f4d796a6e4919d9ee \ 3 | --hash=sha256:12fc8ef76294515324de2bc7b44c92f0491a35d33de362e9352f3a2512102ca4 \ 4 | --hash=sha256:21789d9a2c3979f12acb2deac11a47fb28e140af4be137f4dffee99eefb70239 5 | numpy==2.0.1 ; python_version >= "3.12" and python_version < "4.0" \ 6 | --hash=sha256:08458fbf403bff5e2b45f08eda195d4b0c9b35682311da5a5a0a0925b11b9bd8 \ 7 | --hash=sha256:0fbb536eac80e27a2793ffd787895242b7f18ef792563d742c2d673bfcb75134 \ 8 | --hash=sha256:12f5d865d60fb9734e60a60f1d5afa6d962d8d4467c120a1c0cda6eb2964437d \ 9 | --hash=sha256:15eb4eca47d36ec3f78cde0a3a2ee24cf05ca7396ef808dda2c0ddad7c2bde67 \ 10 | --hash=sha256:173a00b9995f73b79eb0191129f2455f1e34c203f559dd118636858cc452a1bf \ 11 | --hash=sha256:1b902ce0e0a5bb7704556a217c4f63a7974f8f43e090aff03fcf262e0b135e02 \ 12 | --hash=sha256:1f682ea61a88479d9498bf2091fdcd722b090724b08b31d63e022adc063bad59 \ 13 | --hash=sha256:1f87fec1f9bc1efd23f4227becff04bd0e979e23ca50cc92ec88b38489db3b55 \ 14 | --hash=sha256:24a0e1befbfa14615b49ba9659d3d8818a0f4d8a1c5822af8696706fbda7310c \ 15 | --hash=sha256:2c3a346ae20cfd80b6cfd3e60dc179963ef2ea58da5ec074fd3d9e7a1e7ba97f \ 16 | --hash=sha256:36d3a9405fd7c511804dc56fc32974fa5533bdeb3cd1604d6b8ff1d292b819c4 \ 17 | --hash=sha256:3fdabe3e2a52bc4eff8dc7a5044342f8bd9f11ef0934fcd3289a788c0eb10018 \ 18 | --hash=sha256:4127d4303b9ac9f94ca0441138acead39928938660ca58329fe156f84b9f3015 \ 19 | --hash=sha256:4658c398d65d1b25e1760de3157011a80375da861709abd7cef3bad65d6543f9 \ 20 | --hash=sha256:485b87235796410c3519a699cfe1faab097e509e90ebb05dcd098db2ae87e7b3 \ 21 | --hash=sha256:529af13c5f4b7a932fb0e1911d3a75da204eff023ee5e0e79c1751564221a5c8 \ 22 | --hash=sha256:5a3d94942c331dd4e0e1147f7a8699a4aa47dffc11bf8a1523c12af8b2e91bbe \ 23 | --hash=sha256:5daab361be6ddeb299a918a7c0864fa8618af66019138263247af405018b04e1 \ 24 | --hash=sha256:61728fba1e464f789b11deb78a57805c70b2ed02343560456190d0501ba37b0f \ 25 | --hash=sha256:6790654cb13eab303d8402354fabd47472b24635700f631f041bd0b65e37298a \ 26 | --hash=sha256:69ff563d43c69b1baba77af455dd0a839df8d25e8590e79c90fcbe1499ebde42 \ 27 | --hash=sha256:6bf4e6f4a2a2e26655717a1983ef6324f2664d7011f6ef7482e8c0b3d51e82ac \ 28 | --hash=sha256:6e4eeb6eb2fced786e32e6d8df9e755ce5be920d17f7ce00bc38fcde8ccdbf9e \ 29 | --hash=sha256:72dc22e9ec8f6eaa206deb1b1355eb2e253899d7347f5e2fae5f0af613741d06 \ 30 | --hash=sha256:75b4e316c5902d8163ef9d423b1c3f2f6252226d1aa5cd8a0a03a7d01ffc6268 \ 31 | --hash=sha256:7b9853803278db3bdcc6cd5beca37815b133e9e77ff3d4733c247414e78eb8d1 \ 32 | --hash=sha256:7d6fddc5fe258d3328cd8e3d7d3e02234c5d70e01ebe377a6ab92adb14039cb4 \ 33 | --hash=sha256:81b0893a39bc5b865b8bf89e9ad7807e16717f19868e9d234bdaf9b1f1393868 \ 34 | --hash=sha256:8efc84f01c1cd7e34b3fb310183e72fcdf55293ee736d679b6d35b35d80bba26 \ 35 | --hash=sha256:8fae4ebbf95a179c1156fab0b142b74e4ba4204c87bde8d3d8b6f9c34c5825ef \ 36 | --hash=sha256:99d0d92a5e3613c33a5f01db206a33f8fdf3d71f2912b0de1739894668b7a93b \ 37 | --hash=sha256:9adbd9bb520c866e1bfd7e10e1880a1f7749f1f6e5017686a5fbb9b72cf69f82 \ 38 | --hash=sha256:a1e01dcaab205fbece13c1410253a9eea1b1c9b61d237b6fa59bcc46e8e89343 \ 39 | --hash=sha256:a8fc2de81ad835d999113ddf87d1ea2b0f4704cbd947c948d2f5513deafe5a7b \ 40 | --hash=sha256:b83e16a5511d1b1f8a88cbabb1a6f6a499f82c062a4251892d9ad5d609863fb7 \ 41 | --hash=sha256:bb2124fdc6e62baae159ebcfa368708867eb56806804d005860b6007388df171 \ 42 | --hash=sha256:bfc085b28d62ff4009364e7ca34b80a9a080cbd97c2c0630bb5f7f770dae9414 \ 43 | --hash=sha256:cbab9fc9c391700e3e1287666dfd82d8666d10e69a6c4a09ab97574c0b7ee0a7 \ 44 | --hash=sha256:e5eeca8067ad04bc8a2a8731183d51d7cbaac66d86085d5f4766ee6bf19c7f87 \ 45 | --hash=sha256:e9e81fa9017eaa416c056e5d9e71be93d05e2c3c2ab308d23307a8bc4443c368 \ 46 | --hash=sha256:ea2326a4dca88e4a274ba3a4405eb6c6467d3ffbd8c7d38632502eaae3820587 \ 47 | --hash=sha256:eacf3291e263d5a67d8c1a581a8ebbcfd6447204ef58828caf69a5e3e8c75990 \ 48 | --hash=sha256:ec87f5f8aca726117a1c9b7083e7656a9d0d606eec7299cc067bb83d26f16e0c \ 49 | --hash=sha256:f1659887361a7151f89e79b276ed8dff3d75877df906328f14d8bb40bb4f5101 \ 50 | --hash=sha256:f9cf5ea551aec449206954b075db819f52adc1638d46a6738253a712d553c7b4 51 | polars==1.6.0 ; python_version >= "3.12" and python_version < "4.0" \ 52 | --hash=sha256:1c811b772c9476f7f0bb4445a8387d2ab6d86f5e79140b1bfba914a32788d261 \ 53 | --hash=sha256:6d1665c23e3574ebd47a26a5d7b619e6e73e53718c3b0bfd7d08b6a0a4ae7daa \ 54 | --hash=sha256:a166adb429f8ee099c9d803e7470a80c76368437a8b272c67cef9eef6d5e9da1 \ 55 | --hash=sha256:d7e8d5e577883a9755bc3be92ecbf6f20bced68267bdb8bdb440120e905cc19c \ 56 | --hash=sha256:d7f3abf085adf034720b358119c4c8e144bcc2d96010b7e7d0afa11b80da383c \ 57 | --hash=sha256:ffae15ffa80fda5cc3af44a340b565bcf7f2ab6d7854d3f967baf505710c78e2 58 | pyarrow==17.0.0 ; python_version >= "3.12" and python_version < "4.0" \ 59 | --hash=sha256:0071ce35788c6f9077ff9ecba4858108eebe2ea5a3f7cf2cf55ebc1dbc6ee24a \ 60 | --hash=sha256:02dae06ce212d8b3244dd3e7d12d9c4d3046945a5933d28026598e9dbbda1fca \ 61 | --hash=sha256:0b72e87fe3e1db343995562f7fff8aee354b55ee83d13afba65400c178ab2597 \ 62 | --hash=sha256:0cdb0e627c86c373205a2f94a510ac4376fdc523f8bb36beab2e7f204416163c \ 63 | --hash=sha256:13d7a460b412f31e4c0efa1148e1d29bdf18ad1411eb6757d38f8fbdcc8645fb \ 64 | --hash=sha256:1c8856e2ef09eb87ecf937104aacfa0708f22dfeb039c363ec99735190ffb977 \ 65 | --hash=sha256:2e19f569567efcbbd42084e87f948778eb371d308e137a0f97afe19bb860ccb3 \ 66 | --hash=sha256:32503827abbc5aadedfa235f5ece8c4f8f8b0a3cf01066bc8d29de7539532687 \ 67 | --hash=sha256:392bc9feabc647338e6c89267635e111d71edad5fcffba204425a7c8d13610d7 \ 68 | --hash=sha256:42bf93249a083aca230ba7e2786c5f673507fa97bbd9725a1e2754715151a204 \ 69 | --hash=sha256:4beca9521ed2c0921c1023e68d097d0299b62c362639ea315572a58f3f50fd28 \ 70 | --hash=sha256:5984f416552eea15fd9cee03da53542bf4cddaef5afecefb9aa8d1010c335087 \ 71 | --hash=sha256:6b244dc8e08a23b3e352899a006a26ae7b4d0da7bb636872fa8f5884e70acf15 \ 72 | --hash=sha256:757074882f844411fcca735e39aae74248a1531367a7c80799b4266390ae51cc \ 73 | --hash=sha256:75c06d4624c0ad6674364bb46ef38c3132768139ddec1c56582dbac54f2663e2 \ 74 | --hash=sha256:7c7916bff914ac5d4a8fe25b7a25e432ff921e72f6f2b7547d1e325c1ad9d155 \ 75 | --hash=sha256:9b564a51fbccfab5a04a80453e5ac6c9954a9c5ef2890d1bcf63741909c3f8df \ 76 | --hash=sha256:9b8a823cea605221e61f34859dcc03207e52e409ccf6354634143e23af7c8d22 \ 77 | --hash=sha256:9ba11c4f16976e89146781a83833df7f82077cdab7dc6232c897789343f7891a \ 78 | --hash=sha256:a155acc7f154b9ffcc85497509bcd0d43efb80d6f733b0dc3bb14e281f131c8b \ 79 | --hash=sha256:a27532c38f3de9eb3e90ecab63dfda948a8ca859a66e3a47f5f42d1e403c4d03 \ 80 | --hash=sha256:a48ddf5c3c6a6c505904545c25a4ae13646ae1f8ba703c4df4a1bfe4f4006bda \ 81 | --hash=sha256:a5c8b238d47e48812ee577ee20c9a2779e6a5904f1708ae240f53ecbee7c9f07 \ 82 | --hash=sha256:af5ff82a04b2171415f1410cff7ebb79861afc5dae50be73ce06d6e870615204 \ 83 | --hash=sha256:b0c6ac301093b42d34410b187bba560b17c0330f64907bfa4f7f7f2444b0cf9b \ 84 | --hash=sha256:d7d192305d9d8bc9082d10f361fc70a73590a4c65cf31c3e6926cd72b76bc35c \ 85 | --hash=sha256:da1e060b3876faa11cee287839f9cc7cdc00649f475714b8680a05fd9071d545 \ 86 | --hash=sha256:db023dc4c6cae1015de9e198d41250688383c3f9af8f565370ab2b4cb5f62655 \ 87 | --hash=sha256:dc5c31c37409dfbc5d014047817cb4ccd8c1ea25d19576acf1a001fe07f5b420 \ 88 | --hash=sha256:dec8d129254d0188a49f8a1fc99e0560dc1b85f60af729f47de4046015f9b0a5 \ 89 | --hash=sha256:e3343cb1e88bc2ea605986d4b94948716edc7a8d14afd4e2c097232f729758b4 \ 90 | --hash=sha256:edca18eaca89cd6382dfbcff3dd2d87633433043650c07375d095cd3517561d8 \ 91 | --hash=sha256:f1e70de6cb5790a50b01d2b686d54aaf73da01266850b05e3af2a1bc89e16053 \ 92 | --hash=sha256:f553ca691b9e94b202ff741bdd40f6ccb70cdd5fbf65c187af132f1317de6145 \ 93 | --hash=sha256:f7ae2de664e0b158d1607699a16a488de3d008ba99b3a7aa5de1cbc13574d047 \ 94 | --hash=sha256:fa3c246cc58cb5a4a5cb407a18f193354ea47dd0648194e6265bd24177982fe8 95 | -------------------------------------------------------------------------------- /tests/test_deltabase.py: -------------------------------------------------------------------------------- 1 | import pytest 2 | 3 | from deltabase import delta 4 | from polars import DataFrame, LazyFrame 5 | from pandas import DataFrame as PandasDataFrame 6 | 7 | from os.path import exists 8 | from shutil import rmtree 9 | 10 | @pytest.fixture 11 | def db(): 12 | _ = delta.connect(path="test.delta") 13 | yield _ 14 | for table in _.tables: 15 | _._delta__delta_sql_context.unregister(table) 16 | if exists("test.delta"): rmtree("test.delta") 17 | 18 | def test_connect(db): 19 | assert isinstance(db, delta) 20 | assert db.tables == [] 21 | 22 | def test_add_record_dict(db): 23 | err = db.upsert(table="test_table", primary_key="id", data=dict(id=1, name="a")) 24 | assert not err, err 25 | 26 | err = db.upsert(table="test_table", primary_key="id", data=[ 27 | dict(id=2, name="b"), 28 | dict(id=3, name="c"), 29 | ]) 30 | assert not err, err 31 | result = db.sql("select * from test_table", dtype="polars") 32 | 33 | assert isinstance(result, DataFrame) 34 | assert result.shape == (3, 2) 35 | assert set(result["id"].to_list()) == set([1,2,3]) 36 | assert set(result["name"].to_list()) == set(["a","b","c"]) 37 | 38 | def test_add_record_dataframe(db): 39 | err = db.upsert(table="test_table", primary_key="id", data=DataFrame([ 40 | dict(id=2, name="b"), 41 | dict(id=3, name="c"), 42 | ])) 43 | assert not err, err 44 | result = db.sql("select * from test_table", dtype="polars") 45 | 46 | assert isinstance(result, DataFrame) 47 | assert result.shape == (2, 2) 48 | assert set(result["id"].to_list()) == set([2,3]) 49 | assert set(result["name"].to_list()) == set(["b","c"]) 50 | 51 | def test_add_record_lazyframe(db): 52 | err = db.upsert(table="test_table", primary_key="id", data=DataFrame([ 53 | dict(id=2, name="b"), 54 | dict(id=3, name="c"), 55 | ]).lazy()) 56 | assert not err, err 57 | result = db.sql("select * from test_table", dtype="polars") 58 | 59 | assert isinstance(result, DataFrame) 60 | assert result.shape == (2, 2) 61 | assert set(result["id"].to_list()) == set([2,3]) 62 | assert set(result["name"].to_list()) == set(["b","c"]) 63 | 64 | def test_add_mismatch_schema(db): 65 | err = db.upsert(table="test_table", primary_key="id", data=[ 66 | dict(id=2, name="b", job="j"), 67 | dict(id=3, name="c"), 68 | ]) 69 | assert not err, err 70 | result = db.sql("select * from test_table", dtype="polars") 71 | 72 | assert isinstance(result, DataFrame) 73 | assert result.shape == (2, 3) 74 | assert set(result["id"].to_list()) == set([2,3]) 75 | assert set(result["name"].to_list()) == set(["b","c"]) 76 | assert set(result["job"].to_list()) == set(["j", None]) 77 | 78 | def test_update_record(db): 79 | db.upsert(table="test_table", primary_key="id", data=dict(id=2, name="a")) 80 | db.upsert(table="test_table", primary_key="id", data=dict(id=2, name="b")) 81 | result = db.sql("select * from test_table", dtype="polars") 82 | 83 | assert isinstance(result, DataFrame) 84 | assert result.shape == (1, 2) 85 | assert set(result["id"].to_list()) == set([2]) 86 | assert set(result["name"].to_list()) == set(["b"]) 87 | 88 | def test_update_mismatch_schema_record(db): 89 | db.upsert(table="test_table", primary_key="id", data=dict(id=2, name="a")) 90 | db.upsert(table="test_table", primary_key="id", data=[dict(id=2, name="b"), dict(id=3, name="c", job="j")]) 91 | result = db.sql("select * from test_table", dtype="polars") 92 | 93 | assert isinstance(result, DataFrame) 94 | assert result.shape == (2, 3) 95 | assert set(result["id"].to_list()) == set([2, 3]) 96 | assert set(result["name"].to_list()) == set(["b", "c"]) 97 | assert set(result["job"].to_list()) == set([None, "j"]) 98 | 99 | def test_delete_record_sql(db): 100 | db.upsert(table="test_table", primary_key="id", data=dict(id=5, name="a")) 101 | db.upsert(table="test_table", primary_key="id", data=dict(id=6, name="b")) 102 | 103 | err = db.delete(table="test_table", filter="name='a'") 104 | assert not err, err 105 | 106 | result = db.sql("select * from test_table", dtype="polars") 107 | 108 | assert isinstance(result, DataFrame) 109 | assert result.shape == (1, 2) 110 | assert set(result["name"].to_list()) == set(["b"]) 111 | 112 | def test_delete_record_lambda(db): 113 | db.upsert(table="test_table", primary_key="id", data=dict(id=5, name="a")) 114 | db.upsert(table="test_table", primary_key="id", data=dict(id=6, name="b")) 115 | 116 | err = db.delete(table="test_table", filter=lambda row: row["name"] == "a") 117 | assert not err, err 118 | 119 | result = db.sql("select * from test_table", dtype="polars") 120 | 121 | assert isinstance(result, DataFrame) 122 | assert result.shape == (1, 2) 123 | assert set(result["name"].to_list()) == set(["b"]) 124 | 125 | def test_delete_record_wrong_type(db): 126 | db.upsert(table="test_table", primary_key="id", data=dict(id=5, name="a")) 127 | db.upsert(table="test_table", primary_key="id", data=dict(id=6, name="b")) 128 | 129 | err = db.delete(table="test_table", filter=["wrong"]) 130 | assert isinstance(err, Exception) 131 | 132 | def test_schema_override(db): 133 | db.upsert(table="test_table", primary_key="id", data=dict(id=5, name="edward")) 134 | db.commit("test_table") 135 | db.upsert(table="test_table", primary_key="id", data=dict(id=6, name="james", job="chef")) 136 | db.commit("test_table", force=True) 137 | 138 | result = db.sql("select * from test_table", dtype="polars") 139 | assert result.shape == (2, 3) 140 | 141 | def test_commit_and_versioning(db): 142 | err = db.upsert(table="test_table", primary_key="id", data=dict(id=2, name="b")) 143 | assert not err, err 144 | 145 | err = db.commit("test_table") 146 | assert not err, err 147 | 148 | err = db.upsert(table="test_table", primary_key="id", data=dict(id=3, name="c")) 149 | assert not err, err 150 | 151 | result = db.sql("select * from test_table", dtype="polars") 152 | 153 | assert isinstance(result, DataFrame) 154 | assert result.shape == (2, 2) 155 | assert set(result["id"].to_list()) == set([2,3]) 156 | assert set(result["name"].to_list()) == set(["b","c"]) 157 | 158 | err = db.checkout(table="test_table", version=0) 159 | assert not err, err 160 | 161 | result = db.sql("select * from test_table", dtype="polars") 162 | 163 | assert isinstance(result, DataFrame) 164 | assert result.shape == (1, 2) 165 | assert set(result["id"].to_list()) == set([2]) 166 | assert set(result["name"].to_list()) == set(["b"]) 167 | 168 | def test_commit_with_partitions(db): 169 | db.upsert(table="test_table", primary_key="id", data=LazyFrame([dict(id=1, name="alice", job="teacher")])) 170 | db.upsert(table="test_table", primary_key="id", data=LazyFrame([dict(id=2, name="john", job="chef")])) 171 | db.commit("test_table", partition_by=["job"]) 172 | 173 | db.register(table="test_table", pyarrow_options={"partitions": [("job", "=", "chef")]}) 174 | 175 | result = db.sql("select * from test_table", dtype="polars") 176 | 177 | assert isinstance(result, DataFrame) 178 | assert result.shape == (1, 3) 179 | assert result["id"].to_list() == [2] 180 | assert result["name"].to_list() == ["john"] 181 | 182 | def test_register_with_alias(db): 183 | db.upsert(table="test_table", primary_key="id", data=LazyFrame([dict(id=1, name="alice", job="teacher")])) 184 | db.upsert(table="test_table", primary_key="id", data=LazyFrame([dict(id=2, name="john", job="chef")])) 185 | db.commit("test_table") 186 | 187 | db.register(table="test_table", alias="other_table") 188 | 189 | result = db.sql("select * from other_table", dtype="polars") 190 | 191 | assert isinstance(result, DataFrame) 192 | assert result.shape == (2, 3) 193 | assert set(result["id"].to_list()) == set([1,2]) 194 | assert set(result["name"].to_list()) == set(["alice","john"]) 195 | 196 | def test_json_output(db): 197 | db.upsert(table="test_table", primary_key="id", data=dict(id=5, name="a")) 198 | result = db.sql("select * from test_table", dtype="json") 199 | assert isinstance(result, list) 200 | assert isinstance(result[0], dict) 201 | assert result[0] == dict(id=5, name="a") 202 | 203 | def test_override_dtype(db): 204 | db.config.dtype = "polars" 205 | db.upsert(table="test_table", primary_key="id", data=dict(id=5, name="a")) 206 | result = db.sql("select * from test_table") 207 | assert isinstance(result, DataFrame) 208 | 209 | def test_collect_schema(db): 210 | db.config.dtype = "polars" 211 | db.upsert(table="test_table", primary_key="id", data=dict(id=5, name="a")) 212 | schema = db.schema(table="test_table") 213 | assert schema == {'id': int, 'name': str} 214 | -------------------------------------------------------------------------------- /docs/assets/banner.svg: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | -------------------------------------------------------------------------------- /deltabase/__init__.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | # -*- coding: utf-8 -*- 3 | 4 | # Copyright 2024 darryl mcculley 5 | 6 | # This program is free software: you can redistribute it and/or modify 7 | # it under the terms of the GNU General Public License as published by 8 | # the Free Software Foundation, either version 3 of the License, or 9 | # any later version. 10 | 11 | # This program is distributed in the hope that it will be useful, 12 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 13 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 14 | # GNU General Public License for more details. 15 | 16 | # You should have received a copy of the GNU General Public License 17 | # along with this program. If not, see . 18 | 19 | from types import LambdaType 20 | from typing import Any, TypeVar, Type 21 | 22 | from polars import SQLContext, DataFrame, LazyFrame, Schema, sql_expr, scan_delta, struct, coalesce, from_dicts, from_dict, from_pandas 23 | from polars.exceptions import SchemaError 24 | 25 | from deltalake import WriterProperties 26 | from datetime import datetime 27 | from os.path import exists, isdir, join 28 | from os import listdir 29 | 30 | from deltalake.exceptions import TableNotFoundError 31 | 32 | from logging import getLogger 33 | 34 | debugger = getLogger("deltabase") 35 | 36 | T = TypeVar("T", bound="delta") 37 | 38 | class delta_config: 39 | dtype:str="json" 40 | writer_properties:WriterProperties = WriterProperties() 41 | ai_model:str="gpt-4o-mini" 42 | 43 | class delta: 44 | __delta_source:str 45 | __delta_sql_context:SQLContext=SQLContext(frames=[]) 46 | __delta_sql_context_schema:dict[str, Schema]={} 47 | config:delta_config 48 | 49 | @property 50 | def tables(self): 51 | """ list all tables within the sql context. 52 | 53 | returns a list of table names available in the sql context. 54 | 55 | >>> db.tables # output: ["table_1", "table_2"] 56 | """ 57 | return self.__delta_sql_context.tables() 58 | 59 | @classmethod 60 | def connect(cls: Type[T], path:str, config:delta_config=delta_config(), scan_local_dir:bool=True) -> T: 61 | """ connects to a remote source if provided, or local path, sets config, and automatically scans for tables. 62 | 63 | **args**: 64 | - **path**: the file path or uri to connect to, can be a local directory or remote storage. 65 | - **config**: `optional` configuration settings for the delta instance. default is an instance of `delta_config`. 66 | - **scan_local_dir**: `optional` automatically scan for tables when a local directory is provided. default is `true` 67 | 68 | >>> db = delta.connect(path="local_path/mydelta") 69 | >>> db = delta.connect(path="az:///") 70 | >>> db = delta.connect(path="s3:///") 71 | >>> db = delta.connect(path="gs:///") 72 | """ 73 | delta_cls = cls() 74 | delta_cls.__delta_source = path 75 | delta_cls.config = config 76 | 77 | try: from .magic import enable; enable(delta_cls) 78 | except ImportError as e: pass 79 | 80 | if not exists(path) or "://" in path or not scan_local_dir: return delta_cls 81 | 82 | for database in listdir(delta_cls.__delta_source): 83 | path = join(delta_cls.__delta_source, database) 84 | if isdir(path): 85 | for table in listdir(join(delta_cls.__delta_source, database)): 86 | if not table.startswith("."): 87 | table_path = join(delta_cls.__delta_source, database, table) 88 | if exists(table_path): 89 | try: delta_cls.register(database=database, table=table) 90 | except Exception as e: raise e 91 | 92 | return delta_cls 93 | 94 | def register(self, 95 | table:str, 96 | pyarrow_options:dict=None, 97 | alias:str=None, 98 | database:str="default", 99 | version:int|str|datetime=None, 100 | data:DataFrame|LazyFrame=None, 101 | ) -> Exception: 102 | """ registers the provided data, or loads the table from the delta source if no data is provided. 103 | 104 | **args**: 105 | - **table**: the name of the table to register. 106 | - **pyarrow_options**: `optional` options for loading the table using pyarrow. 107 | - **alias**: `optional` an alias to use for the table within the sql context. 108 | - **database**: `optional` the name of the database where the table is located. default is `'default'`. 109 | - **version**: `optional` the version of the table to load, can be an integer, string, or datetime. 110 | - **data**: `optional` a `DataFrame` or `LazyFrame` to register instead of loading from the delta source. 111 | 112 | >>> db.register(database="mydatabase", table="mytable", data=...) 113 | >>> db.register(database="mydatabase", table="mytable", version=1) 114 | >>> db.register(database="mydatabase", table="mytable", alias="mydatabase_mytable") 115 | >>> db.register(database="mydatabase", table="mytable", pyarrow_options={ 116 | >>> "partitions": [("year", "=", "2021")] 117 | >>> }) 118 | """ 119 | table_path = join(self.__delta_source, database, table) 120 | 121 | options = dict() 122 | if pyarrow_options: 123 | options["use_pyarrow"]=True 124 | options["pyarrow_options"] = pyarrow_options 125 | if isinstance(version, int|str|datetime): options["version"] = version 126 | table_name = alias if alias else table 127 | 128 | try: 129 | if data is None: data = scan_delta(table_path, **options) 130 | elif not isinstance(data, (DataFrame, LazyFrame)): 131 | raise TypeError(f"deltabase.register:: provided {type(data)} is not {DataFrame} or {LazyFrame}") 132 | self.__delta_sql_context.register(table_name, data) 133 | self.__delta_sql_context_schema[table_name] = data.collect_schema() 134 | except (TableNotFoundError, FileNotFoundError) as e: return e 135 | 136 | def __sync_data(self, primary_key:str, target_data:LazyFrame, source_data:LazyFrame) -> LazyFrame: 137 | """ performs a full outer join on the primary key and coalesces data to ensure consistency. 138 | 139 | **args**: 140 | - **primary_key**: the primary key on which the join will be performed. 141 | - **target_data**: the target `LazyFrame` containing the data to be updated. 142 | - **source_data**: the source `LazyFrame` containing the data to synchronize with. 143 | 144 | returns a lazyframe containing the synchronized data. 145 | """ 146 | update_data = source_data.join( 147 | target_data, 148 | on=primary_key, 149 | how="full", 150 | suffix="_delta_target", 151 | coalesce=True 152 | ) 153 | 154 | update_data_columns = update_data.collect_schema().names() 155 | 156 | coalesce_columns = [col for col in update_data_columns if "_delta_target" in col] 157 | coalesce_columns_strip = [col.replace("_delta_target", "") for col in coalesce_columns] 158 | 159 | update_data = update_data.with_columns([ 160 | coalesce([f"{col}_delta_target", col]).alias(col) 161 | if f"{col}_delta_target" in update_data_columns else update_data[col] 162 | for col in coalesce_columns_strip 163 | ]).drop(coalesce_columns) 164 | 165 | return update_data 166 | 167 | def upsert(self, 168 | table:str, 169 | primary_key:str, 170 | data:list[dict] | dict | DataFrame | LazyFrame, 171 | database:str="default", 172 | ) -> Exception: 173 | """ updates or inserts records in the specified table, with schema changes handled automatically. changes are reflected in the sql context, but a commit is required to persist them. 174 | 175 | **args**: 176 | - **table**: the name of the table to upsert data into. 177 | - **primary_key**: the primary key used to match records for updates. 178 | - **data**: the data to be upserted, can be a list of dictionaries, a dictionary, `DataFrame`, or `LazyFrame`. 179 | - **database**: `optional` the name of the database where the table is located. default is `'default'`. 180 | 181 | >>> db.upsert(database="mydatabase", table="mytable", primary_key="id", data=...) 182 | """ 183 | if isinstance(data, list) and len(data) > 0 and isinstance(data[0], dict): data = from_dicts(data).lazy() 184 | elif isinstance(data, dict): data = from_dict(data).lazy() 185 | elif isinstance(data, DataFrame): data = data.lazy() 186 | elif isinstance(data, LazyFrame): pass 187 | else: return ValueError(f"'data' was provided as '{type(data)}', type must be 'list[dict]' | 'dict' | 'DataFrame' | 'LazyFrame'") 188 | 189 | if table not in self.tables: 190 | return self.register(database=database, table=table, data=data) 191 | 192 | table_path = join(self.__delta_source, database, table) 193 | 194 | try: 195 | source_data = scan_delta(table_path) 196 | staged_data = self.sql(f"select * from {table}", lazy=True) 197 | source_data = self.__sync_data(primary_key, staged_data, source_data) 198 | except (TableNotFoundError, FileNotFoundError) as e: 199 | source_data = self.sql(f"select * from {table}", lazy=True) 200 | 201 | update_data = self.__sync_data(primary_key, data, source_data) 202 | 203 | return self.register(database=database, table=table, data=update_data) 204 | 205 | def delete(self, table:str, filter:str|LambdaType="*", database:str="default") -> Exception: 206 | """ removes records using a specified sql condition or lambda function. this only affects the sql context and does not delete data from disk or cloud storage. 207 | 208 | **args**: 209 | - **table**: the name of the table from which records will be deleted. 210 | - **filter**: `optional` a sql condition string or lambda function to filter the records to delete. default is `'*'`, which deletes all records. 211 | - **database**: `optional` the name of the database where the table is located. default is `'default'`. 212 | 213 | >>> db.delete(database="mydatabase", table="mytable") 214 | >>> db.delete(database="mydatabase", table="mytable", filter="name='bob'") 215 | >>> db.delete(database="mydatabase", table="mytable", filter=lambda row: row["name"] == "bob") 216 | """ 217 | table_path = join(self.__delta_source, database, table) 218 | if filter == "*": 219 | self.__delta_sql_context.unregister(table_path) 220 | return None 221 | elif isinstance(filter, str): 222 | source_data = self.sql(f"select * from {table}", lazy=True) 223 | filter_data = source_data.filter(~sql_expr(filter)) 224 | elif type(filter) == LambdaType: 225 | source_data = self.sql(f"select * from {table}", lazy=True) 226 | filter_data = source_data.filter( 227 | ~struct(source_data.collect_schema().names()).map_elements(filter, return_dtype=bool) 228 | ) 229 | else: 230 | return ValueError(f"'filter' was provided as '{type(filter)}', type must be 'callable' or 'str'") 231 | 232 | return self.register(database=database, table=table, data=filter_data) 233 | 234 | def sql(self, query:str, lazy:bool=False, dtype:str=None) -> DataFrame | LazyFrame: 235 | """ executes the provided sql query and returns the result as a dataframe or lazyframe. the result type can be specified via the dtype argument. 236 | 237 | **args**: 238 | - **query**: the sql query to execute. 239 | - **lazy**: `optional` returns a lazyframe if set to true. default is `false`. 240 | - **dtype**: `optional` sets the output data type. default is `'json'`. 241 | 242 | >>> db.sql("select * from mytable") 243 | """ 244 | dtype = dtype if dtype else self.config.dtype 245 | if lazy: return self.__delta_sql_context.execute(query) 246 | try: data:DataFrame = self.__delta_sql_context.execute(query).collect() 247 | except SchemaError as e: data:DataFrame = DataFrame( 248 | schema=self.__delta_sql_context.execute(query).collect_schema() 249 | ) 250 | match dtype: 251 | case "polars": return data 252 | case "json": return data.to_dicts() 253 | case _: raise ValueError(f"'dtype' was provided as '{dtype}', type must be one of the following ['polars', 'json']") 254 | 255 | def commit(self, 256 | table:str, 257 | force:bool=False, 258 | partition_by:list[str]=None, 259 | database:str="default", 260 | ) -> Exception: 261 | """ persists the current state of a table in the sql context to the delta source, with optional schema or partitioning options. 262 | 263 | **args**: 264 | - **table**: the name of the table to commit. 265 | - **force**: `optional` force schema changes during the commit. 266 | - **partition_by**: `optional` list of fields to partition by. 267 | - **database**: `optional` name of the database. default is `'default'`. 268 | 269 | >>> db.commit(database="mydatabase", table="mytable") 270 | >>> db.commit(database="mydatabase", table="mytable", force=True) 271 | >>> db.commit(database="mydatabase", table="mytable", partition_by=["job"]) 272 | """ 273 | table_path = join(self.__delta_source, database, table) 274 | data = self.sql(f"select * from {table}", dtype="polars") 275 | 276 | options = {"mode":"overwrite"} 277 | options.setdefault("delta_write_options", {}) 278 | options["delta_write_options"]["writer_properties"] = self.config.writer_properties 279 | 280 | if partition_by: options["delta_write_options"]["partition_by"] = partition_by 281 | if force: options["delta_write_options"]["schema_mode"] = "overwrite" 282 | 283 | try: data.write_delta(table_path, **options) 284 | except Exception as e: return e 285 | 286 | def checkout(self, table:str, version:int|str|datetime, database:str="default") -> Exception: 287 | """ reloads a previous version of a table from the delta source into the sql context. 288 | 289 | **args**: 290 | - **table**: the name of the table to revert. 291 | - **version**: the version to checkout, which can be an integer, string, or datetime. 292 | - **database**: `optional` name of the database. default is `'default'`. 293 | 294 | >>> db.checkout(database="mydatabase", table="mytable", version=1) 295 | """ 296 | return self.register(database=database, table=table, version=version) 297 | 298 | def schema(self, table:str) -> Schema|None: 299 | """ reloads a previous version of a table from the delta source into the sql context. 300 | 301 | **args**: 302 | - **table**: the name of the table. 303 | - **database**: `optional` name of the database. default is `'default'`. 304 | 305 | >>> db.schema(table="mytable") 306 | """ 307 | schema = self.__delta_sql_context_schema.get(table) 308 | if schema: return schema.to_python() 309 | return None 310 | -------------------------------------------------------------------------------- /examples/magic.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": null, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "%pip install --upgrade 'deltabase' 'deltabase[magic]' 'deltabase[ai]' requests" 10 | ] 11 | }, 12 | { 13 | "cell_type": "code", 14 | "execution_count": 2, 15 | "metadata": {}, 16 | "outputs": [], 17 | "source": [ 18 | "from deltabase import delta\n", 19 | "\n", 20 | "from polars import DataFrame\n", 21 | "from requests import get" 22 | ] 23 | }, 24 | { 25 | "cell_type": "code", 26 | "execution_count": 3, 27 | "metadata": {}, 28 | "outputs": [], 29 | "source": [ 30 | "db:delta = delta.connect(\"delta\")\n", 31 | "db.config.dtype = \"polars\"" 32 | ] 33 | }, 34 | { 35 | "cell_type": "code", 36 | "execution_count": null, 37 | "metadata": {}, 38 | "outputs": [], 39 | "source": [ 40 | "bulk_data = get(\"https://api.scryfall.com/bulk-data\").json()\n", 41 | "download_uri = next((item['download_uri'] for item in bulk_data['data'] if item['type'] == 'all_cards'), None)\n", 42 | "\n", 43 | "data = get(download_uri).json()\n", 44 | "data = DataFrame(data)" 45 | ] 46 | }, 47 | { 48 | "cell_type": "code", 49 | "execution_count": 5, 50 | "metadata": {}, 51 | "outputs": [], 52 | "source": [ 53 | "err = db.upsert(table=\"colors\", primary_key=\"id\", data=data[[\n", 54 | " \"id\", \"lang\", \"set_name\", \"rarity\", \"colors\"\n", 55 | "]].explode(\"colors\").fill_null(strategy=\"zero\"))\n", 56 | "assert not err, err\n", 57 | "err = db.commit(table=\"colors\", partition_by=[\"lang\", \"set_name\", \"rarity\"])\n", 58 | "assert not err, err\n", 59 | "\n", 60 | "err = db.upsert(table=\"images\", primary_key=\"id\", data=data[[\n", 61 | " \"id\", \"lang\", \"set_name\", \"rarity\", \"image_uris\"\n", 62 | "]].unnest(\"image_uris\").fill_null(strategy=\"zero\"))\n", 63 | "assert not err, err\n", 64 | "err = db.commit(table=\"images\", partition_by=[\"lang\", \"set_name\", \"rarity\"])\n", 65 | "assert not err, err\n", 66 | "\n", 67 | "err = db.upsert(table=\"keywords\", primary_key=\"id\", data=data[[\n", 68 | " \"id\", \"lang\", \"set_name\", \"rarity\", \"keywords\"\n", 69 | "]].explode(\"keywords\").fill_null(strategy=\"zero\"))\n", 70 | "assert not err, err\n", 71 | "err = db.commit(table=\"keywords\", partition_by=[\"lang\", \"set_name\", \"rarity\"])\n", 72 | "assert not err, err\n", 73 | "\n", 74 | "err = db.upsert(table=\"legalities\", primary_key=\"id\", data=data[[\n", 75 | " \"id\", \"lang\", \"set_name\", \"rarity\", \"legalities\"\n", 76 | "]].unnest(\"legalities\").fill_null(strategy=\"zero\"))\n", 77 | "assert not err, err\n", 78 | "err = db.commit(table=\"legalities\", partition_by=[\"lang\", \"set_name\", \"rarity\"])\n", 79 | "assert not err, err\n", 80 | "\n", 81 | "err = db.upsert(table=\"prices\", primary_key=\"id\", data=data[[\n", 82 | " \"id\", \"lang\", \"set_name\", \"rarity\", \"prices\"\n", 83 | "]].unnest(\"prices\").drop(\"usd_etched\").fill_null(strategy=\"zero\"))\n", 84 | "assert not err, err\n", 85 | "err = db.commit(table=\"prices\", partition_by=[\"lang\", \"set_name\", \"rarity\"])\n", 86 | "assert not err, err\n", 87 | "\n", 88 | "err = db.upsert(table=\"produced_mana\", primary_key=\"id\", data=data[[\n", 89 | " \"id\", \"lang\", \"set_name\", \"rarity\", \"produced_mana\"\n", 90 | "]].explode(\"produced_mana\").fill_null(\"zero\"))\n", 91 | "assert not err, err\n", 92 | "err = db.commit(table=\"produced_mana\", partition_by=[\"lang\", \"set_name\", \"rarity\"])\n", 93 | "assert not err, err" 94 | ] 95 | }, 96 | { 97 | "cell_type": "code", 98 | "execution_count": 6, 99 | "metadata": {}, 100 | "outputs": [], 101 | "source": [ 102 | "data = data.drop([\n", 103 | " \"all_parts\",\n", 104 | " \"arena_id\",\n", 105 | " \"artist_ids\",\n", 106 | " \"card_faces\",\n", 107 | " \"cardmarket_id\",\n", 108 | " \"color_identity\",\n", 109 | " \"colors\",\n", 110 | " \"finishes\",\n", 111 | " \"frame_effects\",\n", 112 | " \"games\",\n", 113 | " \"highres_image\",\n", 114 | " \"image_status\",\n", 115 | " \"image_uris\",\n", 116 | " \"keywords\",\n", 117 | " \"layout\",\n", 118 | " \"legalities\",\n", 119 | " \"mtgo_foil_id\",\n", 120 | " \"mtgo_id\",\n", 121 | " \"multiverse_ids\",\n", 122 | " \"object\",\n", 123 | " \"oracle_id\",\n", 124 | " \"oracle_text\",\n", 125 | " \"preview\",\n", 126 | " \"prices\",\n", 127 | " \"printed_name\",\n", 128 | " \"printed_text\",\n", 129 | " \"printed_type_line\",\n", 130 | " \"prints_search_uri\",\n", 131 | " \"produced_mana\",\n", 132 | " \"promo_types\",\n", 133 | " \"purchase_uris\",\n", 134 | " \"related_uris\",\n", 135 | " \"rulings_uri\",\n", 136 | " \"scryfall_set_uri\",\n", 137 | " \"scryfall_uri\",\n", 138 | " \"security_stamp\",\n", 139 | " \"set_search_uri\",\n", 140 | " \"set_uri\",\n", 141 | " \"uri\",\n", 142 | "])\n", 143 | "\n", 144 | "err = db.upsert(table=\"cards\", primary_key=\"id\", data=data.fill_null(\"zero\"))\n", 145 | "assert not err, err\n", 146 | "err = db.commit(table=\"cards\", partition_by=[\"lang\", \"set_name\", \"rarity\"])\n", 147 | "assert not err, err" 148 | ] 149 | }, 150 | { 151 | "cell_type": "code", 152 | "execution_count": 7, 153 | "metadata": {}, 154 | "outputs": [], 155 | "source": [ 156 | "data = db.sql(\"\"\"\n", 157 | "select\n", 158 | " p.id, \n", 159 | " c.name,\n", 160 | " c.set_name,\n", 161 | " c.released_at as release_date,\n", 162 | " cast(p.usd as float) as usd,\n", 163 | "from prices as p\n", 164 | "inner join cards as c on c.id = p.id\n", 165 | "where p.usd != '' and c.lang = 'en'\n", 166 | "order by usd desc\n", 167 | "\"\"\")\n", 168 | "err = db.upsert(table=\"card_value\", primary_key=\"id\", data=data)\n", 169 | "assert not err, err\n", 170 | "err = db.commit(table=\"card_value\", partition_by=[\"set_name\"])\n", 171 | "assert not err, err" 172 | ] 173 | }, 174 | { 175 | "cell_type": "code", 176 | "execution_count": 8, 177 | "metadata": {}, 178 | "outputs": [], 179 | "source": [ 180 | "data = db.sql(\"\"\"\n", 181 | "select\n", 182 | " set_name,\n", 183 | " min(cast(release_date as date)) as release_date,\n", 184 | " sum(usd) as usd,\n", 185 | " count(id) as n_cards,\n", 186 | "from card_value\n", 187 | "group by set_name\n", 188 | "order by usd desc\n", 189 | "\"\"\")\n", 190 | "err = db.upsert(table=\"set_value\", primary_key=\"set_name\", data=data)\n", 191 | "assert not err, err\n", 192 | "err = db.commit(table=\"set_value\")\n", 193 | "assert not err, err" 194 | ] 195 | }, 196 | { 197 | "cell_type": "markdown", 198 | "metadata": {}, 199 | "source": [ 200 | "---" 201 | ] 202 | }, 203 | { 204 | "cell_type": "code", 205 | "execution_count": 9, 206 | "metadata": {}, 207 | "outputs": [ 208 | { 209 | "data": { 210 | "text/markdown": [ 211 | "You have access to the following sets of data related to card games:\n", 212 | "\n", 213 | "1. **Card Values (`card_value`)**: Contains information about individual card values, including identifiers, names, set names, release dates, and their USD prices.\n", 214 | "\n", 215 | "2. **Cards (`cards`)**: Provides detailed attributes of each card, including ID, TCGPlayer ID, name, language, release date, mana cost, converted mana cost (cmc), type, rarity, various boolean flags (e.g., reserved, foil, promo), and attributes like power and toughness.\n", 216 | "\n", 217 | "3. **Colors (`colors`)**: Lists information on card colors, including identifiers, language, rarity, and color specifications.\n", 218 | "\n", 219 | "4. **Images (`images`)**: Contains image URLs for cards, which include different sizes (small, normal, large) and specific formats (PNG, art crop, border crop) alongside their associated metadata like rarity.\n", 220 | "\n", 221 | "5. **Keywords (`keywords`)**: Features keywords associated with cards, giving insight into specific abilities or traits based on language and rarity.\n", 222 | "\n", 223 | "6. **Legalities (`legalities`)**: Specifies the legality of cards in various formats (e.g., standard, modern, commander) based on identifiers, language, rarity, and specific formats.\n", 224 | "\n", 225 | "7. **Prices (`prices`)**: Presents pricing information, including USD prices for normal and foil cards, as well as EURO prices and ticket values.\n", 226 | "\n", 227 | "8. **Produced Mana (`produced_mana`)**: Lists details on mana production for cards, including identifiers, languages, set names, rarity, and the type of mana produced.\n", 228 | "\n", 229 | "9. **Set Values (`set_value`)**: Summarizes data for card sets, detailing the set name, release date, total USD value of the set, and the number of cards in that set.\n", 230 | "\n", 231 | "This data collectively allows you to gain insights into individual cards, their values, legalities, and related multimedia, among other aspects of the card game ecosystem." 232 | ], 233 | "text/plain": [ 234 | "" 235 | ] 236 | }, 237 | "metadata": {}, 238 | "output_type": "display_data" 239 | } 240 | ], 241 | "source": [ 242 | "%%ai\n", 243 | "summarize the data available to me." 244 | ] 245 | }, 246 | { 247 | "cell_type": "code", 248 | "execution_count": 10, 249 | "metadata": {}, 250 | "outputs": [], 251 | "source": [ 252 | "db.register(table=\"card_value\", version=0, alias=\"temp_card_value\")" 253 | ] 254 | }, 255 | { 256 | "cell_type": "code", 257 | "execution_count": 11, 258 | "metadata": {}, 259 | "outputs": [ 260 | { 261 | "data": { 262 | "text/plain": [ 263 | "['card_value',\n", 264 | " 'cards',\n", 265 | " 'colors',\n", 266 | " 'images',\n", 267 | " 'keywords',\n", 268 | " 'legalities',\n", 269 | " 'prices',\n", 270 | " 'produced_mana',\n", 271 | " 'set_value',\n", 272 | " 'temp_card_value']" 273 | ] 274 | }, 275 | "execution_count": 11, 276 | "metadata": {}, 277 | "output_type": "execute_result" 278 | } 279 | ], 280 | "source": [ 281 | "db.tables" 282 | ] 283 | }, 284 | { 285 | "cell_type": "code", 286 | "execution_count": 12, 287 | "metadata": { 288 | "vscode": { 289 | "languageId": "sql" 290 | } 291 | }, 292 | "outputs": [ 293 | { 294 | "data": { 295 | "text/html": [ 296 | "
\n", 303 | "shape: (71_519, 6)
idnameset_namepreviouscurrentdiff
strstrstrf64f64f64
"093e3fc5-b2e0-4376-b8ad-4470e0…"Gratuitous Violence""Conspiracy: Take the Crown"2.142.140.0
"43ab3ff8-91b0-437c-9c4b-e9c103…"Omenspeaker""Conspiracy: Take the Crown"0.060.060.0
"9de3eeae-22a5-4d9c-afd6-1cc441…"Coordinated Assault""Conspiracy: Take the Crown"0.080.080.0
"f9083583-6fa9-4b8a-86bb-59e51a…"Exotic Orchard""Conspiracy: Take the Crown"0.330.330.0
"160d39b0-76c5-4218-97e5-5903f7…"Opaline Unicorn""Conspiracy: Take the Crown"0.090.090.0
………………
"c2c6e29e-261a-4953-bdbe-cce879…"Tamiyo, Field Researcher Emble…"Eldritch Moon Tokens"0.710.710.0
"dbd994fc-f3f0-4c81-86bd-14ca63…"Human""Eldritch Moon Tokens"0.290.290.0
"e44aa879-b63b-497c-9c1b-233395…"Zombie""Eldritch Moon Tokens"0.250.250.0
"11d25bde-a303-4b06-a3e1-4ad642…"Eldrazi Horror""Eldritch Moon Tokens"0.10.10.0
"b8710a30-8314-49ef-b995-bd0545…"Zombie""Eldritch Moon Tokens"0.130.130.0
" 304 | ], 305 | "text/plain": [ 306 | "shape: (71_519, 6)\n", 307 | "┌───────────────────────┬───────────────────────┬──────────────────────┬──────────┬─────────┬──────┐\n", 308 | "│ id ┆ name ┆ set_name ┆ previous ┆ current ┆ diff │\n", 309 | "│ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n", 310 | "│ str ┆ str ┆ str ┆ f64 ┆ f64 ┆ f64 │\n", 311 | "╞═══════════════════════╪═══════════════════════╪══════════════════════╪══════════╪═════════╪══════╡\n", 312 | "│ 093e3fc5-b2e0-4376-b8 ┆ Gratuitous Violence ┆ Conspiracy: Take the ┆ 2.14 ┆ 2.14 ┆ 0.0 │\n", 313 | "│ ad-4470e0… ┆ ┆ Crown ┆ ┆ ┆ │\n", 314 | "│ 43ab3ff8-91b0-437c-9c ┆ Omenspeaker ┆ Conspiracy: Take the ┆ 0.06 ┆ 0.06 ┆ 0.0 │\n", 315 | "│ 4b-e9c103… ┆ ┆ Crown ┆ ┆ ┆ │\n", 316 | "│ 9de3eeae-22a5-4d9c-af ┆ Coordinated Assault ┆ Conspiracy: Take the ┆ 0.08 ┆ 0.08 ┆ 0.0 │\n", 317 | "│ d6-1cc441… ┆ ┆ Crown ┆ ┆ ┆ │\n", 318 | "│ f9083583-6fa9-4b8a-86 ┆ Exotic Orchard ┆ Conspiracy: Take the ┆ 0.33 ┆ 0.33 ┆ 0.0 │\n", 319 | "│ bb-59e51a… ┆ ┆ Crown ┆ ┆ ┆ │\n", 320 | "│ 160d39b0-76c5-4218-97 ┆ Opaline Unicorn ┆ Conspiracy: Take the ┆ 0.09 ┆ 0.09 ┆ 0.0 │\n", 321 | "│ e5-5903f7… ┆ ┆ Crown ┆ ┆ ┆ │\n", 322 | "│ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", 323 | "│ c2c6e29e-261a-4953-bd ┆ Tamiyo, Field ┆ Eldritch Moon Tokens ┆ 0.71 ┆ 0.71 ┆ 0.0 │\n", 324 | "│ be-cce879… ┆ Researcher Emble… ┆ ┆ ┆ ┆ │\n", 325 | "│ dbd994fc-f3f0-4c81-86 ┆ Human ┆ Eldritch Moon Tokens ┆ 0.29 ┆ 0.29 ┆ 0.0 │\n", 326 | "│ bd-14ca63… ┆ ┆ ┆ ┆ ┆ │\n", 327 | "│ e44aa879-b63b-497c-9c ┆ Zombie ┆ Eldritch Moon Tokens ┆ 0.25 ┆ 0.25 ┆ 0.0 │\n", 328 | "│ 1b-233395… ┆ ┆ ┆ ┆ ┆ │\n", 329 | "│ 11d25bde-a303-4b06-a3 ┆ Eldrazi Horror ┆ Eldritch Moon Tokens ┆ 0.1 ┆ 0.1 ┆ 0.0 │\n", 330 | "│ e1-4ad642… ┆ ┆ ┆ ┆ ┆ │\n", 331 | "│ b8710a30-8314-49ef-b9 ┆ Zombie ┆ Eldritch Moon Tokens ┆ 0.13 ┆ 0.13 ┆ 0.0 │\n", 332 | "│ 95-bd0545… ┆ ┆ ┆ ┆ ┆ │\n", 333 | "└───────────────────────┴───────────────────────┴──────────────────────┴──────────┴─────────┴──────┘" 334 | ] 335 | }, 336 | "execution_count": 12, 337 | "metadata": {}, 338 | "output_type": "execute_result" 339 | } 340 | ], 341 | "source": [ 342 | "%%sql\n", 343 | "select \n", 344 | " c.id, \n", 345 | " c.name, \n", 346 | " c.set_name,\n", 347 | " t.usd as previous,\n", 348 | " c.usd as current,\n", 349 | " (c.usd - t.usd) as diff\n", 350 | "from card_value as c\n", 351 | "inner join temp_card_value as t on c.id = t.id\n", 352 | "order by diff desc;" 353 | ] 354 | }, 355 | { 356 | "cell_type": "code", 357 | "execution_count": 13, 358 | "metadata": { 359 | "vscode": { 360 | "languageId": "sql" 361 | } 362 | }, 363 | "outputs": [], 364 | "source": [ 365 | "db.register(table=\"set_value\", version=0, alias=\"temp_set_value\")" 366 | ] 367 | }, 368 | { 369 | "cell_type": "code", 370 | "execution_count": 14, 371 | "metadata": { 372 | "vscode": { 373 | "languageId": "sql" 374 | } 375 | }, 376 | "outputs": [ 377 | { 378 | "data": { 379 | "text/html": [ 380 | "
\n", 387 | "shape: (537, 4)
set_namepreviouscurrentdiff
strf64f64f64
"Unlimited Edition"26503.526503.50.0
"Limited Edition Beta"22377.6922377.690.0
"Limited Edition Alpha"19426.0719426.070.0
"Arabian Nights"13772.2213772.220.0
"Secret Lair Drop"13739.513739.50.0
…………
"Duel Decks: Sorin vs. Tibalt T…0.120.120.0
"Streets of New Capenna Tokens"0.110.110.0
"Duel Decks: Jace vs. Chandra T…0.10.10.0
"Dominaria United Commander Tok…0.070.070.0
"Assassin's Creed Tokens"0.060.060.0
" 388 | ], 389 | "text/plain": [ 390 | "shape: (537, 4)\n", 391 | "┌─────────────────────────────────┬──────────┬──────────┬──────┐\n", 392 | "│ set_name ┆ previous ┆ current ┆ diff │\n", 393 | "│ --- ┆ --- ┆ --- ┆ --- │\n", 394 | "│ str ┆ f64 ┆ f64 ┆ f64 │\n", 395 | "╞═════════════════════════════════╪══════════╪══════════╪══════╡\n", 396 | "│ Unlimited Edition ┆ 26503.5 ┆ 26503.5 ┆ 0.0 │\n", 397 | "│ Limited Edition Beta ┆ 22377.69 ┆ 22377.69 ┆ 0.0 │\n", 398 | "│ Limited Edition Alpha ┆ 19426.07 ┆ 19426.07 ┆ 0.0 │\n", 399 | "│ Arabian Nights ┆ 13772.22 ┆ 13772.22 ┆ 0.0 │\n", 400 | "│ Secret Lair Drop ┆ 13739.5 ┆ 13739.5 ┆ 0.0 │\n", 401 | "│ … ┆ … ┆ … ┆ … │\n", 402 | "│ Duel Decks: Sorin vs. Tibalt T… ┆ 0.12 ┆ 0.12 ┆ 0.0 │\n", 403 | "│ Streets of New Capenna Tokens ┆ 0.11 ┆ 0.11 ┆ 0.0 │\n", 404 | "│ Duel Decks: Jace vs. Chandra T… ┆ 0.1 ┆ 0.1 ┆ 0.0 │\n", 405 | "│ Dominaria United Commander Tok… ┆ 0.07 ┆ 0.07 ┆ 0.0 │\n", 406 | "│ Assassin's Creed Tokens ┆ 0.06 ┆ 0.06 ┆ 0.0 │\n", 407 | "└─────────────────────────────────┴──────────┴──────────┴──────┘" 408 | ] 409 | }, 410 | "execution_count": 14, 411 | "metadata": {}, 412 | "output_type": "execute_result" 413 | } 414 | ], 415 | "source": [ 416 | "%%sql\n", 417 | "select\n", 418 | " c.set_name,\n", 419 | " t.usd as previous,\n", 420 | " c.usd as current,\n", 421 | " (c.usd - t.usd) as diff\n", 422 | "from set_value as c\n", 423 | "inner join temp_set_value as t on c.set_name = t.set_name\n", 424 | "order by diff desc;" 425 | ] 426 | } 427 | ], 428 | "metadata": { 429 | "kernelspec": { 430 | "display_name": ".venv", 431 | "language": "python", 432 | "name": "python3" 433 | }, 434 | "language_info": { 435 | "codemirror_mode": { 436 | "name": "ipython", 437 | "version": 3 438 | }, 439 | "file_extension": ".py", 440 | "mimetype": "text/x-python", 441 | "name": "python", 442 | "nbconvert_exporter": "python", 443 | "pygments_lexer": "ipython3", 444 | "version": "3.12.2" 445 | } 446 | }, 447 | "nbformat": 4, 448 | "nbformat_minor": 2 449 | } 450 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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No Surrender of Others' Freedom. 541 | 542 | If conditions are imposed on you (whether by court order, agreement or 543 | otherwise) that contradict the conditions of this License, they do not 544 | excuse you from the conditions of this License. If you cannot convey a 545 | covered work so as to satisfy simultaneously your obligations under this 546 | License and any other pertinent obligations, then as a consequence you may 547 | not convey it at all. For example, if you agree to terms that obligate you 548 | to collect a royalty for further conveying from those to whom you convey 549 | the Program, the only way you could satisfy both those terms and this 550 | License would be to refrain entirely from conveying the Program. 551 | 552 | 13. Use with the GNU Affero General Public License. 553 | 554 | Notwithstanding any other provision of this License, you have 555 | permission to link or combine any covered work with a work licensed 556 | under version 3 of the GNU Affero General Public License into a single 557 | combined work, and to convey the resulting work. The terms of this 558 | License will continue to apply to the part which is the covered work, 559 | but the special requirements of the GNU Affero General Public License, 560 | section 13, concerning interaction through a network will apply to the 561 | combination as such. 562 | 563 | 14. Revised Versions of this License. 564 | 565 | The Free Software Foundation may publish revised and/or new versions of 566 | the GNU General Public License from time to time. Such new versions will 567 | be similar in spirit to the present version, but may differ in detail to 568 | address new problems or concerns. 569 | 570 | Each version is given a distinguishing version number. If the 571 | Program specifies that a certain numbered version of the GNU General 572 | Public License "or any later version" applies to it, you have the 573 | option of following the terms and conditions either of that numbered 574 | version or of any later version published by the Free Software 575 | Foundation. If the Program does not specify a version number of the 576 | GNU General Public License, you may choose any version ever published 577 | by the Free Software Foundation. 578 | 579 | If the Program specifies that a proxy can decide which future 580 | versions of the GNU General Public License can be used, that proxy's 581 | public statement of acceptance of a version permanently authorizes you 582 | to choose that version for the Program. 583 | 584 | Later license versions may give you additional or different 585 | permissions. However, no additional obligations are imposed on any 586 | author or copyright holder as a result of your choosing to follow a 587 | later version. 588 | 589 | 15. Disclaimer of Warranty. 590 | 591 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY 592 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT 593 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY 594 | OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, 595 | THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR 596 | PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM 597 | IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF 598 | ALL NECESSARY SERVICING, REPAIR OR CORRECTION. 599 | 600 | 16. Limitation of Liability. 601 | 602 | IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING 603 | WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS 604 | THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY 605 | GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE 606 | USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF 607 | DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD 608 | PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), 609 | EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF 610 | SUCH DAMAGES. 611 | 612 | 17. Interpretation of Sections 15 and 16. 613 | 614 | If the disclaimer of warranty and limitation of liability provided 615 | above cannot be given local legal effect according to their terms, 616 | reviewing courts shall apply local law that most closely approximates 617 | an absolute waiver of all civil liability in connection with the 618 | Program, unless a warranty or assumption of liability accompanies a 619 | copy of the Program in return for a fee. 620 | 621 | END OF TERMS AND CONDITIONS 622 | 623 | How to Apply These Terms to Your New Programs 624 | 625 | If you develop a new program, and you want it to be of the greatest 626 | possible use to the public, the best way to achieve this is to make it 627 | free software which everyone can redistribute and change under these terms. 628 | 629 | To do so, attach the following notices to the program. It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . --------------------------------------------------------------------------------