A pyparsing-based library for parsing SOQL statements

Overview

CONTRIBUTORS WANTED!!

Installation

pip install python-soql-parser

or, with poetry

poetry add python-soql-parser

Usage

from python_soql_parser import parse


parse_result = parse("SELECT Id FROM Account")

where parse_result is a ParseResults object from pyparsing.

Notable caveats

Unsupported features

  • Subqueries (e.g., SELECT Name, (SELECT LastName FROM Contacts) FROM Account)
  • Aggregate queries
  • SOQL specific WHERE-clause tokens (e.g., LAST_N_DAYS: )

Partially supported

These are either partially supported or weakly supported

  • Related attributes (e.g., SELECT Id, Account.Name FROM Contact). The object name is not yet parsed out on its own. This will simply parse out "Account.Name"

Contributing

A lot of work remains to be done. Practically no SOQL-specific features are supported as of yet. If you want to contribute, just open a PR! (and add a test for your new feature)

Setting up locally

First install poetry. Afterwards, to install the dependencies, run

poetry install

Running the tests

Simply execute

pytest

House cleaning

Please sort imports with isort and format the code with black (in that order).

Owner
Kicksaw
Salesforce implementation, data migration, process optimization, tool integration, & data sourcing / enrichment services to boost your revenue teams.
Kicksaw
An experimentation and research platform to investigate the interaction of automated agents in an abstract simulated network environments.

CyberBattleSim April 8th, 2021: See the announcement on the Microsoft Security Blog. CyberBattleSim is an experimentation research platform to investi

Microsoft 1.5k Dec 25, 2022
MLSpace: Hassle-free machine learning & deep learning development

MLSpace: Hassle-free machine learning & deep learning development

abhishek thakur 293 Jan 03, 2023
VID-Fusion: Robust Visual-Inertial-Dynamics Odometry for Accurate External Force Estimation

VID-Fusion VID-Fusion: Robust Visual-Inertial-Dynamics Odometry for Accurate External Force Estimation Authors: Ziming Ding , Tiankai Yang, Kunyi Zhan

ZJU FAST Lab 86 Nov 18, 2022
This repository contains the map content ontology used in narrative cartography

Narrative-cartography-ontology This repository contains the map content ontology used in narrative cartography, which is associated with a submission

Weiming Huang 0 Oct 31, 2021
PyTorch implementation of NeurIPS 2021 paper: "CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration"

PyTorch implementation of NeurIPS 2021 paper: "CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration"

76 Jan 03, 2023
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty

AugMix Introduction We propose AugMix, a data processing technique that mixes augmented images and enforces consistent embeddings of the augmented ima

Google Research 876 Dec 17, 2022
Scheduling BilinearRewards

Scheduling_BilinearRewards Requirement Python 3 =3.5 Structure main.py This file includes the main function. For getting the results in Figure 1, ple

junghun.kim 0 Nov 25, 2021
fastgradio is a python library to quickly build and share gradio interfaces of your trained fastai models.

fastgradio is a python library to quickly build and share gradio interfaces of your trained fastai models.

Ali Abdalla 34 Jan 05, 2023
Forecasting directional movements of stock prices for intraday trading using LSTM and random forest

Forecasting directional movements of stock-prices for intraday trading using LSTM and random-forest https://arxiv.org/abs/2004.10178 Pushpendu Ghosh,

Pushpendu Ghosh 270 Dec 24, 2022
Architecture Patterns with Python (TDD, DDD, EDM)

architecture-traning Architecture Patterns with Python (TDD, DDD, EDM) Chapter 5. 높은 기어비와 낮은 기어비의 TDD 5.2 도메인 계층 테스트를 서비스 계층으로 옮겨야 하는가? 도메인 계층 테스트 def

minsung sim 2 Mar 04, 2022
A collection of pre-trained StyleGAN2 models trained on different datasets at different resolution.

Awesome Pretrained StyleGAN2 A collection of pre-trained StyleGAN2 models trained on different datasets at different resolution. Note the readme is a

Justin 1.1k Dec 24, 2022
[CVPR 2022] Thin-Plate Spline Motion Model for Image Animation.

[CVPR2022] Thin-Plate Spline Motion Model for Image Animation Source code of the CVPR'2022 paper "Thin-Plate Spline Motion Model for Image Animation"

yoyo-nb 1.4k Dec 30, 2022
This is an example of object detection on Micro bacterium tuberculosis using Mask-RCNN

Mask-RCNN on Mycobacterium tuberculosis This is an example of object detection on Mycobacterium Tuberculosis using Mask RCNN. Implement of Mask R-CNN

Jun-En Ding 1 Sep 16, 2021
A library for answering questions using data you cannot see

A library for computing on data you do not own and cannot see PySyft is a Python library for secure and private Deep Learning. PySyft decouples privat

OpenMined 8.5k Jan 02, 2023
DeepGNN is a framework for training machine learning models on large scale graph data.

DeepGNN Overview DeepGNN is a framework for training machine learning models on large scale graph data. DeepGNN contains all the necessary features in

Microsoft 45 Jan 01, 2023
Code for T-Few from "Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning"

T-Few This repository contains the official code for the paper: "Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learni

220 Dec 31, 2022
Tooling for GANs in TensorFlow

TensorFlow-GAN (TF-GAN) TF-GAN is a lightweight library for training and evaluating Generative Adversarial Networks (GANs). Can be installed with pip

803 Dec 24, 2022
Semi-supervised Stance Detection of Tweets Via Distant Network Supervision

SANDS This is an annonymous repository containing code and data necessary to reproduce the results published in "Semi-supervised Stance Detection of T

2 Sep 22, 2022
Tightness-aware Evaluation Protocol for Scene Text Detection

TIoU-metric Release on 27/03/2019. This repository is built on the ICDAR 2015 evaluation code. If you propose a better metric and require further eval

Yuliang Liu 206 Nov 18, 2022
Implementation of ToeplitzLDA for spatiotemporal stationary time series data.

Code for the ToeplitzLDA classifier proposed in here. The classifier conforms sklearn and can be used as a drop-in replacement for other LDA classifiers. For in-depth usage refer to the learning from

Jan Sosulski 5 Nov 07, 2022