initial

.circleci/config.yml

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+version: 2
+jobs:
+  build:
+    working_directory: ~/circleci
+    docker:
+      - image: circleci/python:3.7.1
+      - image: circleci/postgres:10
+        environment:
+          POSTGRES_USER: circleci
+          POSTGRES_DB: circleci
+    steps:
+      - checkout
+      - restore_cache:
+          key: deps1-{{ .Branch }}-{{ checksum "pyproject.toml" }}
+      - run:
+          name: Wait for db
+          command: dockerize -wait tcp://localhost:5432 -timeout 1m
+      - run: sudo apt-get install -y postgresql-client
+      - run:
+          name: create postgres user
+          command: psql postgresql://@localhost/circleci -c 'create role postgres'
+      - run:
+          name: Install poetry
+          command: |
+            sudo pip3 install poetry
+            poetry config settings.virtualenvs.create false
+      - run:
+          command: |
+            python3 -m venv ~/.venv
+            . ~/.venv/bin/activate
+
+            poetry install
+      - save_cache:
+          key: deps1-{{ .Branch }}-{{ checksum "pyproject.toml" }}
+          paths:
+            - "~/.venv"
+      - run:
+          name: Check formatting
+          command: |
+            . ~/.venv/bin/activate
+            make lint
+      - run:
+          command: |
+            . ~/.venv/bin/activate
+            make test
+      - store_artifacts:
+          path: test-reports/
+          destination: tr1
+
+  publish:
+    working_directory: ~/circleci
+    docker:
+      - image: circleci/python:3.7.1
+    steps:
+      - setup_remote_docker
+      - checkout
+      - restore_cache:
+          key: deps1-{{ .Branch }}-{{ checksum "pyproject.toml" }}
+      - run:
+          name: Install poetry, deps
+          command: |
+            sudo pip3 install poetry
+            poetry config settings.virtualenvs.create false
+            python3 -m venv ~/.venv
+            . ~/.venv/bin/activate
+            poetry install
+      - run:
+          name: Bump version, build, install
+          command: |
+            . ~/.venv/bin/activate
+            python deploy/vbump.py
+            poetry build
+            poetry publish --username $PYPI_USERNAME --password $PYPI_PASSWORD
+
+
+workflows:
+  version: 2
+  build-then-publish:
+    jobs:
+      - build
+      - publish:
+          requires:
+            - build
+          filters:
+            branches:
+              only: master

.flake8

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+[flake8]
+ignore = E501,W503

.gitignore

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+*.py[cod]
+
+# C extensions
+*.so
+
+# Packages
+*.egg
+*.egg-info
+dist
+build
+eggs
+parts
+bin
+var
+sdist
+develop-eggs
+.installed.cfg
+lib
+lib64
+__pycache__
+wheelhouse
+
+# Installer logs
+pip-log.txt
+
+# Unit test / coverage reports
+.coverage
+.tox
+nosetests.xml
+.pytest_cache
+
+# Translations
+*.mo
+
+# Mr Developer
+.mr.developer.cfg
+.project
+.pydevproject
+
+.cache
+
+scratch
+poetry.lock

Makefile

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+targs = --cov-report term-missing --cov results
+
+check: clean fmt test lint
+
+test:
+	pytest $(targs)
+
+lint:
+	flake8 .
+
+fmt:
+	isort -rc .
+	black .
+
+gitclean:
+	git clean -fXd
+
+clean:
+	find . -name \*.pyc -delete
+	rm -rf .cache

README.md

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+# Don't get mad, get `results`
+
+Tabular data and SQL for people who don't have time to faff about.
+
+Move between xlsx, xls, csv, python, postgres and back with ease.
+
+Features:
+
+- Zero-boilerplate database creating, connecting and querying.
+- Loading/tidying/transforming csv and excel data.
+- Autodetect column types, load your data with little or no manual specification.
+- Powerful multi-column, multi-order keyset paging of database results.
+- Schema syncing.
+
+Limitations
+
+- Python 3.6+, PostgreSQL 10+ only. Many features will work with other databases, but many won't. Just use Postgres!
+
+# Installation
+
+[`results` is on PyPI](https://pypi.org/project/results). Install it with `pip` or any of the (many) Python package managers.
+
+## Scenario
+
+Somebody gives you a messy csv or excel file. You need to load it, clean it up, put it into a database, query it, make a pivot table from it, then send the pivot table to somebody as a csv.
+
+`results` is here to get this sort of thing done quickly and with minimum possible fuss.
+
+Let's see.
+
+First, load and clean:
+
+```python
+import results
+
+# load a csv (in this example, some airport data)
+sheet = results.from_file("airports.csv")
+
+# do general cleanup
+sheet.standardize_spaces()
+sheet.set_blanks_to_none()
+
+# give the keys lowercase-with-underscore names to keep the database happy
+cleaned = sheet.with_standardized_keys()
+```
+
+Then, create a database:
+
+```python
+# create a database
+DB = "postgresql:///example"
+
+db = results.db(DB)
+
+# create it if it doesn't exist
+db.create_database()
+```
+
+Then create a table for the data, automatically guessing the columns and creating a table to match.
+
+```python
+# guess the column types
+guessed = cleaned.guessed_sql_column_types()
+
+# create a table for the data
+create_table_statement = results.create_table_statement("data", guessed)
+
+# create or auto-update the table structure in the database
+# syncing requires a copy of postgres running locally with your current user set up as superuser
+db.sync_db_structure_to_definition(create_table_statement, confirm=False)
+```
+
+Then insert the data and freely query it.
+
+```python
+# insert the data. you can also do upserts with upsert_on!
+db.insert("data", cleaned)
+
+# show recent airfreight numbers from the top 5 airports
+# ss means "single statement"
+query_result = db.ss(
+    """
+with top5 as (
+    select
+        foreignport, sum(freight_in_tonnes)
+    from
+        data
+    where year >= 2010
+    group by
+        foreignport
+    order by 2 desc
+    limit 5
+)
+
+select
+    year, foreignport, sum(freight_in_tonnes)
+from
+    data
+where
+    year >= 2010
+    and foreignport in (select foreignport from top5)
+group by 1, 2
+order by 1, 2
+
+"""
+)
+```
+
+Create a pivot table, then print it as markdown or save it as csv.
+
+```python
+# create a pivot table
+pivot = query_result.pivoted()
+
+# print the pivot table in markdown format
+print(pivot.md)
+```
+
+Output:
+```
+|   year |   Auckland |    Dubai |   Hong Kong |   Kuala Lumpur |   Singapore |
+|-------:|-----------:|---------:|------------:|---------------:|------------:|
+|   2010 |     288997 | 145527   |      404735 |       226787   |      529407 |
+|   2011 |     304628 | 169868   |      428990 |       244053   |      583921 |
+|   2012 |     312828 | 259444   |      400596 |       272093   |      614155 |
+|   2013 |     306783 | 257263   |      353895 |       272804   |      592886 |
+|   2014 |     309318 | 244776   |      330521 |       261438   |      620419 |
+|   2015 |     286202 | 263378   |      290292 |       252906   |      633862 |
+|   2016 |     285973 | 236419   |      309556 |       175858   |      614172 |
+|   2017 |     314405 | 226048   |      340216 |       199868   |      662505 |
+|   2018 |     126712 |  91611.2 |      134540 |        74667.5 |      250653 |
+```
+
+Save the table as a csv:
+
+```python
+pivot.save_csv("2010s_freight_sources_top5.csv")
+```
+
+## Design philosophy
+
+- Avoid boilerplate at all costs. Make it as simple as possible but no simpler.
+
+- Don't reinvent the wheel: `results` uses sqlalchemy for database connections, existing excel parsing libraries for excel parsing, etc etc. `results` brings it all together, sprinkles some sugar on top, and puts it at your fingertips.
+
+- Eat your own dogfood: We use this ourselves every day.
+
+## Documentation
+
+This README.md is currently all there is :( But we'll add more soon, we promise!
+
+## Credits
+
+- [Rob](https://github.com/djrobstep)
+- [Jason](https://github.com/jasongi)
+- [Nick](https://github.com/nmcl23)
+
+## Contributions
+
+Yes please!

deploy/vbump.py

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+from pathlib import Path
+from time import time
+
+from toml import TomlPreserveInlineDictEncoder as tpide
+from toml import dumps, loads
+
+PYPROJECT = "pyproject.toml"
+
+p = Path(PYPROJECT)
+pyproject = loads(p.read_text())
+
+v = pyproject["tool"]["poetry"]["version"]
+
+parts = v.split(".")[:2]
+unix = str(int(time()))
+
+parts.append(unix)
+
+v_with_timestamp = ".".join(parts)
+pyproject["tool"]["poetry"]["version"] = v_with_timestamp
+p.write_text(dumps(pyproject, tpide()))