LogoLogo
SnowflakeDocumentation Home
  • Snowpark Migration Accelerator Documentation
  • General
    • Introduction
    • Getting Started
      • Download and Access
      • Installation
        • Windows Installation
        • MacOS Installation
        • Linux Installation
    • Conversion Software Terms of Use
      • Open Source Libraries
    • Release Notes
      • Old Version Release Notes
        • SC Spark Scala Release Notes
          • Known Issues
        • SC Spark Python Release Notes
          • Known Issues
    • Roadmap
  • User Guide
    • Overview
    • Before Using the SMA
      • Supported Platforms
      • Supported Filetypes
      • Code Extraction
      • Pre-Processing Considerations
    • Project Overview
      • Project Setup
      • Configuration and Settings
      • Tool Execution
    • Assessment
      • How the Assessment Works
      • Assessment Quick Start
      • Understanding the Assessment Summary
      • Readiness Scores
      • Output Reports
        • Curated Reports
        • SMA Inventories
        • Generic Inventories
        • Assessment zip file
      • Output Logs
      • Spark Reference Categories
    • Conversion
      • How the Conversion Works
      • Conversion Quick Start
      • Conversion Setup
      • Understanding the Conversion Assessment and Reporting
      • Output Code
    • Using the SMA CLI
      • Additional Parameters
  • Use Cases
    • Assessment Walkthrough
      • Walkthrough Setup
        • Notes on Code Preparation
      • Running the Tool
      • Interpreting the Assessment Output
        • Assessment Output - In Application
        • Assessment Output - Reports Folder
      • Running the SMA Again
    • Conversion Walkthrough
    • Sample Project
    • Using SMA with Docker
    • SMA CLI Walkthrough
  • Issue Analysis
    • Approach
    • Issue Code Categorization
    • Issue Codes by Source
      • General
      • Python
        • SPRKPY1000
        • SPRKPY1001
        • SPRKPY1002
        • SPRKPY1003
        • SPRKPY1004
        • SPRKPY1005
        • SPRKPY1006
        • SPRKPY1007
        • SPRKPY1008
        • SPRKPY1009
        • SPRKPY1010
        • SPRKPY1011
        • SPRKPY1012
        • SPRKPY1013
        • SPRKPY1014
        • SPRKPY1015
        • SPRKPY1016
        • SPRKPY1017
        • SPRKPY1018
        • SPRKPY1019
        • SPRKPY1020
        • SPRKPY1021
        • SPRKPY1022
        • SPRKPY1023
        • SPRKPY1024
        • SPRKPY1025
        • SPRKPY1026
        • SPRKPY1027
        • SPRKPY1028
        • SPRKPY1029
        • SPRKPY1030
        • SPRKPY1031
        • SPRKPY1032
        • SPRKPY1033
        • SPRKPY1034
        • SPRKPY1035
        • SPRKPY1036
        • SPRKPY1037
        • SPRKPY1038
        • SPRKPY1039
        • SPRKPY1040
        • SPRKPY1041
        • SPRKPY1042
        • SPRKPY1043
        • SPRKPY1044
        • SPRKPY1045
        • SPRKPY1046
        • SPRKPY1047
        • SPRKPY1048
        • SPRKPY1049
        • SPRKPY1050
        • SPRKPY1051
        • SPRKPY1052
        • SPRKPY1053
        • SPRKPY1054
        • SPRKPY1055
        • SPRKPY1056
        • SPRKPY1057
        • SPRKPY1058
        • SPRKPY1059
        • SPRKPY1060
        • SPRKPY1061
        • SPRKPY1062
        • SPRKPY1063
        • SPRKPY1064
        • SPRKPY1065
        • SPRKPY1066
        • SPRKPY1067
        • SPRKPY1068
        • SPRKPY1069
        • SPRKPY1070
        • SPRKPY1071
        • SPRKPY1072
        • SPRKPY1073
        • SPRKPY1074
        • SPRKPY1075
        • SPRKPY1076
        • SPRKPY1077
        • SPRKPY1078
        • SPRKPY1079
        • SPRKPY1080
        • SPRKPY1081
        • SPRKPY1082
        • SPRKPY1083
        • SPRKPY1084
        • SPRKPY1085
        • SPRKPY1086
        • SPRKPY1087
        • SPRKPY1088
        • SPRKPY1089
        • SPRKPY1101
      • Spark Scala
        • SPRKSCL1000
        • SPRKSCL1001
        • SPRKSCL1002
        • SPRKSCL1100
        • SPRKSCL1101
        • SPRKSCL1102
        • SPRKSCL1103
        • SPRKSCL1104
        • SPRKSCL1105
        • SPRKSCL1106
        • SPRKSCL1107
        • SPRKSCL1108
        • SPRKSCL1109
        • SPRKSCL1110
        • SPRKSCL1111
        • SPRKSCL1112
        • SPRKSCL1113
        • SPRKSCL1114
        • SPRKSCL1115
        • SPRKSCL1116
        • SPRKSCL1117
        • SPRKSCL1118
        • SPRKSCL1119
        • SPRKSCL1120
        • SPRKSCL1121
        • SPRKSCL1122
        • SPRKSCL1123
        • SPRKSCL1124
        • SPRKSCL1125
        • SPRKSCL1126
        • SPRKSCL1127
        • SPRKSCL1128
        • SPRKSCL1129
        • SPRKSCL1130
        • SPRKSCL1131
        • SPRKSCL1132
        • SPRKSCL1133
        • SPRKSCL1134
        • SPRKSCL1135
        • SPRKSCL1136
        • SPRKSCL1137
        • SPRKSCL1138
        • SPRKSCL1139
        • SPRKSCL1140
        • SPRKSCL1141
        • SPRKSCL1142
        • SPRKSCL1143
        • SPRKSCL1144
        • SPRKSCL1145
        • SPRKSCL1146
        • SPRKSCL1147
        • SPRKSCL1148
        • SPRKSCL1149
        • SPRKSCL1150
        • SPRKSCL1151
        • SPRKSCL1152
        • SPRKSCL1153
        • SPRKSCL1154
        • SPRKSCL1155
        • SPRKSCL1156
        • SPRKSCL1157
        • SPRKSCL1158
        • SPRKSCL1159
        • SPRKSCL1160
        • SPRKSCL1161
        • SPRKSCL1162
        • SPRKSCL1163
        • SPRKSCL1164
        • SPRKSCL1165
        • SPRKSCL1166
        • SPRKSCL1167
        • SPRKSCL1168
        • SPRKSCL1169
        • SPRKSCL1170
        • SPRKSCL1171
        • SPRKSCL1172
        • SPRKSCL1173
        • SPRKSCL1174
        • SPRKSCL1175
      • SQL
        • SparkSQL
          • SPRKSPSQL1001
          • SPRKSPSQL1002
          • SPRKSPSQL1003
          • SPRKSPSQL1004
          • SPRKSPSQL1005
          • SPRKSPSQL1006
        • Hive
          • SPRKHVSQL1001
          • SPRKHVSQL1002
          • SPRKHVSQL1003
          • SPRKHVSQL1004
          • SPRKHVSQL1005
          • SPRKHVSQL1006
      • Pandas
        • PNDSPY1001
        • PNDSPY1002
        • PNDSPY1003
        • PNDSPY1004
      • DBX
        • SPRKDBX1001
    • Troubleshooting the Output Code
      • Locating Issues
    • Workarounds
    • Deploying the Output Code
  • Translation Reference
    • Translation Reference Overview
    • SIT Tagging
      • SQL statements
    • SQL Embedded code
    • HiveSQL
      • Supported functions
    • Spark SQL
      • Spark SQL DDL
        • Create Table
          • Using
      • Spark SQL DML
        • Merge
        • Select
          • Distinct
          • Values
          • Join
          • Where
          • Group By
          • Union
      • Spark SQL Data Types
      • Supported functions
  • Workspace Estimator
    • Overview
    • Getting Started
  • INTERACTIVE ASSESSMENT APPLICATION
    • Overview
    • Installation Guide
  • Support
    • General Troubleshooting
      • How do I give SMA permission to the config folder?
      • Invalid Access Code error on VDI
      • How do I give SMA permission to Documents, Desktop, and Downloads folders?
    • Frequently Asked Questions (FAQ)
      • Using SMA with Jupyter Notebooks
      • How to request an access code
      • Sharing the Output with Snowflake
      • DBC files explode
    • Glossary
    • Contact Us
Powered by GitBook
On this page
  • Description
  • Scenario
  • Additional recommendations
  1. Issue Analysis
  2. Issue Codes by Source
  3. Python

SPRKPY1001

File with parsing errors

PreviousSPRKPY1000NextSPRKPY1002

Last updated 6 months ago

Message: This code section has parsing errors

Category: Parsing error.

Description

A parsing error is reported by the Snowpark Migration Accelerator (SMA) when it cannot correctly read or understand the code in a file (it cannot correctly "parse" the file). This issue code appears when a file has one or more parsing error(s).

Scenario

Input: The EWI message appears when the code has invalid syntax, for example:

def foo():
    x = %%%%%%1###1

Output: SMA find a parsing error and comment the parsing error adding the corresponding EWI message:

def foo():
    x
# EWI: SPRKPY1101 => Unrecognized or invalid CODE STATEMENT @(2, 7). Last valid token was 'x' @(2, 5), failed token '=' @(2, 7)
#      = %%%%%%1###1

Additional recommendations

  • Check that the file contains valid Python code. (You can use the issues.csv file to find all files with this EWI code to determine which file(s) were not processed by the tool due to parsing error(s).) Many parsing errors occur because only part of the code is input into the tool, so it's bets to ensure that the code will run in the source. If it is valid, report that you encountered a parsing error using the Report an Issue option . Include the line of code that was causing a parsing error in the description when you file this issue.

  • For more support, you can email us at or post an issue .

in the SMA
sma-support@snowflake.com
in the SMA