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Release/release v140 to master #311

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merged 59 commits into from
Mar 8, 2024
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@aarmoa aarmoa commented Mar 8, 2024

  • PR to release latest changes in dev branch (v1.4.0) to master

Summary by CodeRabbit

  • New Features
    • Introduced automated reviews and automatic replies in chat through the new .coderabbit.yaml configuration.
    • Enhanced query and message support in the 'distribution' and 'exchange' modules.
    • Added functionality for secure and flexible management of private keys using dotenv in example scripts.
    • New and updated scripts for improved interactions with the Injective Protocol's distribution and exchange modules, including managing orders, staking, and querying market data.
    • Introduced gRPC interactions with new ChainGrpcDistributionApi and ChainGrpcExchangeApi for distribution and exchange operations.
  • Enhancements
    • Updated method calls and parameters for better flexibility and security across various scripts.
    • Added new trading pairs and tick sizes in configuration files for improved transaction and margin handling.
  • Documentation
    • Updated CHANGELOG.md with a summary of changes for version 1.4.0.
  • Dependencies
    • Updated project version to "1.4.0" and added python-dotenv dependency for environment variable management.
  • Tests
    • Added and updated tests to cover new functionalities and ensure reliability.

abel and others added 30 commits January 16, 2024 11:52
…alization_logic

(feat) Cleaned up the markets initialization logic
…Added the use of `dotenv` to load private keys into environment variables. Removed `asyncio` package dependency
…o new example scripts for all queries and unit tests
…the `distribution` module. Marked as deprecated old functions not following Python naming standards and created the replacements for them (with the correct name following standards)
…Added the use of `dotenv` to load private keys into environment variables. Removed `asyncio` package dependency
…o new example scripts for all queries and unit tests
…the `distribution` module. Marked as deprecated old functions not following Python naming standards and created the replacements for them (with the correct name following standards)
…le_queries_support

Feat/add distribution module queries support
…new example scripts for all the queries and unit tests.
…er. Added unit tests for new messages. Refactored example scripts to move them into separated subfolders for each module.
abel and others added 25 commits February 27, 2024 13:11
…dule_support

Feat/add chain exchange module support
…Added the use of `dotenv` to load private keys into environment variables. Removed `asyncio` package dependency
…Added the use of `dotenv` to load private keys into environment variables. Removed `asyncio` package dependency
…o new example scripts for all queries and unit tests
…the `distribution` module. Marked as deprecated old functions not following Python naming standards and created the replacements for them (with the correct name following standards)
…new example scripts for all the queries and unit tests.
…er. Added unit tests for new messages. Refactored example scripts to move them into separated subfolders for each module.
…new example scripts for all the queries and unit tests.
…er. Added unit tests for new messages. Refactored example scripts to move them into separated subfolders for each module.
…o feat/add_trade_reward_campaign_endpoint
…aign_endpoint

Feat/add trade reward campaign endpoint
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coderabbitai bot commented Mar 8, 2024

Walkthrough

The update to version 1.4.0 introduces a significant overhaul aimed at enhancing security, flexibility, and functionality. Key improvements include the adoption of python-dotenv for secure environment variable management, extensive updates to the chain_client scripts for better interaction with the Injective Protocol, and the addition of new gRPC APIs for distribution and exchange operations. The update also includes better precision handling with Decimal and streamlined method calls, alongside general enhancements to example scripts, configuration files, and testing.

Changes

Files Summary
.coderabbit.yaml Introduced automated reviews and replies in chat based on specified base branches.
CHANGELOG.md Documented additions in the 'distribution' and 'exchange' modules, and the use of python-dotenv.
examples/SendToInjective.py Enhanced security by loading the private key from environment variables using dotenv.
examples/chain_client/... Updated scripts with os, Decimal, and dotenv; replaced hardcoded keys with env variables; improved precision and security across functionalities.
examples/chain_client/distribution/...
examples/chain_client/exchange/...
New scripts for distribution and exchange modules; updates for spot and derivative orders, market launches, and queries.
pyinjective/... Added ChainGrpcDistributionApi and ChainGrpcExchangeApi; updated transaction and margin handling; updated configuration files with new trading pairs.
pyproject.toml Updated project version to "1.4.0" and added python-dotenv dependency.
tests/... New and updated tests for ChainGrpcDistributionApi and ChainGrpcExchangeApi, margin conversion, gas limit estimation, transaction fees, and deprecation warnings.

"In fields of code where logic plays,
🐰 A rabbit hops, through update mazes.
With dotenv secrets, safely kept,
And gRPC paths, deftly stepped.
Version 1.4, a leap we take,
For secure, precise, the changes we make."
🌟✨


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codecov bot commented Mar 8, 2024

Codecov Report

Attention: Patch coverage is 73.94515% with 247 lines in your changes are missing coverage. Please review.

Project coverage is 76.16%. Comparing base (c0adb1f) to head (ec1fb93).
Report is 21 commits behind head on master.

Files Patch % Lines
pyinjective/composer.py 60.82% 152 Missing and 18 partials ⚠️
pyinjective/async_client.py 49.62% 64 Missing and 3 partials ⚠️
...ctive/client/chain/grpc/chain_grpc_exchange_api.py 97.23% 0 Missing and 7 partials ⚠️
pyinjective/core/network.py 80.00% 1 Missing and 1 partial ⚠️
...e/client/chain/grpc/chain_grpc_distribution_api.py 98.14% 0 Missing and 1 partial ⚠️
Additional details and impacted files
@@            Coverage Diff             @@
##           master     #311      +/-   ##
==========================================
+ Coverage   72.81%   76.16%   +3.34%     
==========================================
  Files          48       50       +2     
  Lines        3384     4111     +727     
  Branches      303      351      +48     
==========================================
+ Hits         2464     3131     +667     
- Misses        839      875      +36     
- Partials       81      105      +24     

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

@aarmoa aarmoa merged commit 52033b4 into master Mar 8, 2024
12 checks passed
@aarmoa aarmoa deleted the release/release_v140_to_master branch March 8, 2024 13:31
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Review Status

Actionable comments generated: 40

Configuration used: .coderabbit.yaml

Commits Files that changed from the base of the PR and between 83152b2 and ec1fb93.
Files selected for processing (140)
  • .coderabbit.yaml (1 hunks)
  • CHANGELOG.md (1 hunks)
  • examples/SendToInjective.py (1 hunks)
  • examples/chain_client/1_LocalOrderHash.py (8 hunks)
  • examples/chain_client/3_MessageBroadcaster.py (3 hunks)
  • examples/chain_client/4_MessageBroadcasterWithGranteeAccount.py (4 hunks)
  • examples/chain_client/5_MessageBroadcasterWithoutSimulation.py (3 hunks)
  • examples/chain_client/6_MessageBroadcasterWithGranteeAccountWithoutSimulation.py (4 hunks)
  • examples/chain_client/auction/1_MsgBid.py (4 hunks)
  • examples/chain_client/authz/1_MsgGrant.py (5 hunks)
  • examples/chain_client/authz/2_MsgExec.py (4 hunks)
  • examples/chain_client/authz/3_MsgRevoke.py (4 hunks)
  • examples/chain_client/authz/query/1_Grants.py (1 hunks)
  • examples/chain_client/bank/1_MsgSend.py (4 hunks)
  • examples/chain_client/distribution/1_SetWithdrawAddress.py (1 hunks)
  • examples/chain_client/distribution/2_WithdrawDelegatorReward.py (1 hunks)
  • examples/chain_client/distribution/3_WithdrawValidatorCommission.py (1 hunks)
  • examples/chain_client/distribution/4_FundCommunityPool.py (1 hunks)
  • examples/chain_client/distribution/query/1_ValidatorDistributionInfo.py (1 hunks)
  • examples/chain_client/distribution/query/2_ValidatorOutstandingRewards.py (1 hunks)
  • examples/chain_client/distribution/query/3_ValidatorCommission.py (1 hunks)
  • examples/chain_client/distribution/query/4_ValidatorSlashes.py (1 hunks)
  • examples/chain_client/distribution/query/5_DelegationRewards.py (1 hunks)
  • examples/chain_client/distribution/query/6_DelegationTotalRewards.py (1 hunks)
  • examples/chain_client/distribution/query/7_DelegatorValidators.py (1 hunks)
  • examples/chain_client/distribution/query/8_DelegatorWithdrawAddress.py (1 hunks)
  • examples/chain_client/distribution/query/9_CommunityPool.py (1 hunks)
  • examples/chain_client/exchange/10_MsgCreateDerivativeLimitOrder.py (5 hunks)
  • examples/chain_client/exchange/11_MsgCreateDerivativeMarketOrder.py (5 hunks)
  • examples/chain_client/exchange/12_MsgCancelDerivativeOrder.py (5 hunks)
  • examples/chain_client/exchange/13_MsgInstantBinaryOptionsMarketLaunch.py (1 hunks)
  • examples/chain_client/exchange/14_MsgCreateBinaryOptionsLimitOrder.py (5 hunks)
  • examples/chain_client/exchange/15_MsgCreateBinaryOptionsMarketOrder.py (5 hunks)
  • examples/chain_client/exchange/16_MsgCancelBinaryOptionsOrder.py (5 hunks)
  • examples/chain_client/exchange/17_MsgSubaccountTransfer.py (4 hunks)
  • examples/chain_client/exchange/18_MsgExternalTransfer.py (4 hunks)
  • examples/chain_client/exchange/19_MsgLiquidatePosition.py (5 hunks)
  • examples/chain_client/exchange/1_MsgDeposit.py (3 hunks)
  • examples/chain_client/exchange/20_MsgIncreasePositionMargin.py (5 hunks)
  • examples/chain_client/exchange/21_MsgRewardsOptOut.py (4 hunks)
  • examples/chain_client/exchange/22_MsgAdminUpdateBinaryOptionsMarket.py (4 hunks)
  • examples/chain_client/exchange/2_MsgWithdraw.py (4 hunks)
  • examples/chain_client/exchange/3_MsgInstantSpotMarketLaunch.py (1 hunks)
  • examples/chain_client/exchange/4_MsgInstantPerpetualMarketLaunch.py (1 hunks)
  • examples/chain_client/exchange/5_MsgInstantExpiryFuturesMarketLaunch.py (1 hunks)
  • examples/chain_client/exchange/6_MsgCreateSpotLimitOrder.py (5 hunks)
  • examples/chain_client/exchange/7_MsgCreateSpotMarketOrder.py (5 hunks)
  • examples/chain_client/exchange/8_MsgCancelSpotOrder.py (4 hunks)
  • examples/chain_client/exchange/9_MsgBatchUpdateOrders.py (5 hunks)
  • examples/chain_client/exchange/query/10_SpotMarkets.py (1 hunks)
  • examples/chain_client/exchange/query/11_SpotMarket.py (1 hunks)
  • examples/chain_client/exchange/query/12_FullSpotMarkets.py (1 hunks)
  • examples/chain_client/exchange/query/13_FullSpotMarket.py (1 hunks)
  • examples/chain_client/exchange/query/14_SpotOrderbook.py (1 hunks)
  • examples/chain_client/exchange/query/15_TraderSpotOrders.py (1 hunks)
  • examples/chain_client/exchange/query/16_AccountAddressSpotOrders.py (1 hunks)
  • examples/chain_client/exchange/query/17_SpotOrdersByHashes.py (1 hunks)
  • examples/chain_client/exchange/query/18_SubaccountOrders.py (1 hunks)
  • examples/chain_client/exchange/query/19_TraderSpotTransientOrders.py (1 hunks)
  • examples/chain_client/exchange/query/1_SubaccountDeposits.py (1 hunks)
  • examples/chain_client/exchange/query/20_SpotMidPriceAndTOB.py (1 hunks)
  • examples/chain_client/exchange/query/21_DerivativeMidPriceAndTOB.py (1 hunks)
  • examples/chain_client/exchange/query/22_DerivativeOrderbook.py (1 hunks)
  • examples/chain_client/exchange/query/23_TraderDerivativeOrders.py (1 hunks)
  • examples/chain_client/exchange/query/24_AccountAddressDerivativeOrders.py (1 hunks)
  • examples/chain_client/exchange/query/25_DerivativeOrdersByHashes.py (1 hunks)
  • examples/chain_client/exchange/query/26_TraderDerivativeTransientOrders.py (1 hunks)
  • examples/chain_client/exchange/query/27_DerivativeMarkets.py (1 hunks)
  • examples/chain_client/exchange/query/28_DerivativeMarket.py (1 hunks)
  • examples/chain_client/exchange/query/29_DerivativeMarketAddress.py (1 hunks)
  • examples/chain_client/exchange/query/2_SubaccountDeposit.py (1 hunks)
  • examples/chain_client/exchange/query/30_SubaccountTradeNonce.py (1 hunks)
  • examples/chain_client/exchange/query/31_Positions.py (1 hunks)
  • examples/chain_client/exchange/query/32_SubaccountPositions.py (1 hunks)
  • examples/chain_client/exchange/query/33_SubaccountPositionInMarket.py (1 hunks)
  • examples/chain_client/exchange/query/34_SubaccountEffectivePositionInMarket.py (1 hunks)
  • examples/chain_client/exchange/query/35_PerpetualMarketInfo.py (1 hunks)
  • examples/chain_client/exchange/query/36_ExpiryFuturesMarketInfo.py (1 hunks)
  • examples/chain_client/exchange/query/37_PerpetualMarketFunding.py (1 hunks)
  • examples/chain_client/exchange/query/38_SubaccountOrderMetadata.py (1 hunks)
  • examples/chain_client/exchange/query/39_TradeRewardPoints.py (1 hunks)
  • examples/chain_client/exchange/query/3_ExchangeBalances.py (1 hunks)
  • examples/chain_client/exchange/query/40_PendingTradeRewardPoints.py (1 hunks)
  • examples/chain_client/exchange/query/41_TradeRewardCampaign.py (1 hunks)
  • examples/chain_client/exchange/query/42_FeeDiscountAccountInfo.py (1 hunks)
  • examples/chain_client/exchange/query/43_FeeDiscountSchedule.py (1 hunks)
  • examples/chain_client/exchange/query/44_BalanceMismatches.py (1 hunks)
  • examples/chain_client/exchange/query/45_BalanceWithBalanceHolds.py (1 hunks)
  • examples/chain_client/exchange/query/46_FeeDiscountTierStatistics.py (1 hunks)
  • examples/chain_client/exchange/query/47_MitoVaultInfos.py (1 hunks)
  • examples/chain_client/exchange/query/48_QueryMarketIDFromVault.py (1 hunks)
  • examples/chain_client/exchange/query/49_HistoricalTradeRecords.py (1 hunks)
  • examples/chain_client/exchange/query/4_AggregateVolume.py (1 hunks)
  • examples/chain_client/exchange/query/50_IsOptedOutOfRewards.py (1 hunks)
  • examples/chain_client/exchange/query/51_OptedOutOfRewardsAccounts.py (1 hunks)
  • examples/chain_client/exchange/query/52_MarketVolatility.py (1 hunks)
  • examples/chain_client/exchange/query/53_BinaryOptionsMarkets.py (1 hunks)
  • examples/chain_client/exchange/query/54_TraderDerivativeConditionalOrders.py (1 hunks)
  • examples/chain_client/exchange/query/55_MarketAtomicExecutionFeeMultiplier.py (1 hunks)
  • examples/chain_client/exchange/query/5_AggregateVolumes.py (1 hunks)
  • examples/chain_client/exchange/query/6_AggregateMarketVolume.py (1 hunks)
  • examples/chain_client/exchange/query/7_AggregateMarketVolumes.py (1 hunks)
  • examples/chain_client/exchange/query/8_DenomDecimal.py (1 hunks)
  • examples/chain_client/exchange/query/9_DenomDecimals.py (1 hunks)
  • examples/chain_client/insurance/1_MsgCreateInsuranceFund.py (4 hunks)
  • examples/chain_client/insurance/2_MsgUnderwrite.py (4 hunks)
  • examples/chain_client/insurance/3_MsgRequestRedemption.py (4 hunks)
  • examples/chain_client/oracle/1_MsgRelayPriceFeedPrice.py (4 hunks)
  • examples/chain_client/oracle/2_MsgRelayProviderPrices.py (4 hunks)
  • examples/chain_client/peggy/1_MsgSendToEth.py (4 hunks)
  • examples/chain_client/staking/1_MsgDelegate.py (4 hunks)
  • examples/chain_client/tokenfactory/1_CreateDenom.py (2 hunks)
  • examples/chain_client/tokenfactory/2_MsgMint.py (3 hunks)
  • examples/chain_client/tokenfactory/3_MsgBurn.py (3 hunks)
  • examples/chain_client/tokenfactory/4_MsgChangeAdmin.py (2 hunks)
  • examples/chain_client/tokenfactory/5_MsgSetDenomMetadata.py (2 hunks)
  • examples/chain_client/wasm/1_MsgExecuteContract.py (4 hunks)
  • examples/chain_client/wasmx/1_MsgExecuteContractCompat.py (4 hunks)
  • poetry.lock (16 hunks)
  • pyinjective/async_client.py (6 hunks)
  • pyinjective/client/chain/grpc/chain_grpc_distribution_api.py (1 hunks)
  • pyinjective/client/chain/grpc/chain_grpc_exchange_api.py (1 hunks)
  • pyinjective/composer.py (24 hunks)
  • pyinjective/core/broadcaster.py (2 hunks)
  • pyinjective/core/market.py (1 hunks)
  • pyinjective/denoms_devnet.ini (3 hunks)
  • pyinjective/denoms_mainnet.ini (12 hunks)
  • pyinjective/denoms_testnet.ini (5 hunks)
  • pyproject.toml (2 hunks)
  • tests/client/chain/grpc/configurable_distribution_query_servicer.py (1 hunks)
  • tests/client/chain/grpc/configurable_exchange_query_servicer.py (1 hunks)
  • tests/client/chain/grpc/test_chain_grpc_authz_api.py (1 hunks)
  • tests/client/chain/grpc/test_chain_grpc_distribution_api.py (1 hunks)
  • tests/core/test_gas_limit_estimator.py (12 hunks)
  • tests/core/test_market.py (1 hunks)
  • tests/core/test_message_based_transaction_fee_calculator.py (3 hunks)
  • tests/test_async_client_deprecation_warnings.py (1 hunks)
  • tests/test_composer.py (5 hunks)
  • tests/test_composer_deprecation_warnings.py (1 hunks)
  • tests/test_orderhash.py (2 hunks)
Files not summarized due to errors (3)
  • poetry.lock: Error: Message exceeds token limit
  • pyinjective/composer.py: Error: Message exceeds token limit
  • tests/test_composer.py: Error: Message exceeds token limit
Files not reviewed due to errors (10)
  • examples/chain_client/exchange/6_MsgCreateSpotLimitOrder.py (Error: unable to parse review)
  • examples/chain_client/authz/1_MsgGrant.py (Error: unable to parse review)
  • examples/chain_client/exchange/15_MsgCreateBinaryOptionsMarketOrder.py (Error: unable to parse review)
  • examples/chain_client/exchange/10_MsgCreateDerivativeLimitOrder.py (Error: unable to parse review)
  • examples/chain_client/exchange/11_MsgCreateDerivativeMarketOrder.py (Error: unable to parse review)
  • examples/chain_client/exchange/14_MsgCreateBinaryOptionsLimitOrder.py (Error: unable to parse review)
  • examples/chain_client/authz/2_MsgExec.py (Error: unable to parse review)
  • examples/chain_client/exchange/19_MsgLiquidatePosition.py (Error: unable to parse review)
  • pyinjective/client/chain/grpc/chain_grpc_distribution_api.py (Error: unable to parse review)
  • examples/chain_client/exchange/9_MsgBatchUpdateOrders.py (Error: unable to parse review)
Additional comments: 321
.coderabbit.yaml (1)
  • 1-8: The configuration for automated reviews and replies looks good and is a welcome addition to streamline the review process. However, please verify:
  • The regex pattern feat/.* correctly matches the intended feature branch naming convention.
  • The auto-reply feature in chat is intended for all interactions, as it might not be suitable for all types of communications.
examples/chain_client/distribution/query/9_CommunityPool.py (1)
  • 1-15: The script for querying the community pool looks well-implemented and aligns with the project's objectives for enhanced functionality. Please ensure that error handling in the AsyncClient and Network classes is robust, especially for network-related errors, assuming this is managed upstream.
examples/chain_client/exchange/query/47_MitoVaultInfos.py (1)
  • 1-15: The script for querying Mito Vault information is well-structured and serves its purpose effectively. Consider adding documentation or comments on how to adapt this script for different network environments (e.g., mainnet), ensuring flexibility for various use cases.
examples/chain_client/exchange/query/3_ExchangeBalances.py (1)
  • 1-14: The script for querying exchange balances is clear and aligns with the project's enhancement objectives. As with previous scripts, please ensure there's guidance on adapting the script for different network environments to maintain flexibility.
examples/chain_client/exchange/query/31_Positions.py (1)
  • 1-15: The script for querying chain positions is effectively implemented and contributes to the project's objectives. Please continue to provide guidance on adapting the script for different network environments, ensuring it remains flexible for various use cases.
examples/chain_client/exchange/query/43_FeeDiscountSchedule.py (1)
  • 1-15: The script for querying the fee discount schedule is well-structured and meets the project's enhancement goals. As with other scripts, guidance on adapting for different network environments would be beneficial to ensure flexibility.
examples/chain_client/exchange/query/45_BalanceWithBalanceHolds.py (1)
  • 1-15: The script for querying balances with balance holds is effectively implemented and aligns with the project's objectives. Continuing the theme, please ensure there's guidance on adapting the script for different network environments.
examples/chain_client/exchange/query/51_OptedOutOfRewardsAccounts.py (1)
  • 1-15: The script for querying accounts that have opted out of rewards is well-structured and contributes to the project's enhancement goals. Please continue to provide guidance on adapting the script for different network environments.
examples/chain_client/exchange/query/46_FeeDiscountTierStatistics.py (1)
  • 1-15: The script for querying fee discount tier statistics is effectively implemented and aligns with the project's objectives. As with other scripts, guidance on adapting the script for different network environments would be beneficial.
examples/chain_client/exchange/query/44_BalanceMismatches.py (1)
  • 1-15: The script for querying balance mismatches is well-structured and meets the project's enhancement goals. Continuing the theme, please ensure there's guidance on adapting the script for different network environments.
examples/chain_client/exchange/query/53_BinaryOptionsMarkets.py (1)
  • 1-19: - The script is well-structured and follows good practices for asynchronous programming in Python.
  • The use of Network.testnet() directly in the script limits its flexibility. Consider allowing the network type (local, testnet, mainnet) to be passed as an argument or read from a configuration file or environment variable for greater flexibility.
  • Ensure that the AsyncClient and the fetch_chain_binary_options_markets method handle errors gracefully. It's important to catch exceptions that may arise from network issues or invalid responses and provide meaningful error messages to the user.
  • Adding a brief comment or documentation at the top of the script explaining its purpose and usage would enhance its maintainability and usability for new developers or users.
examples/chain_client/distribution/query/3_ValidatorCommission.py (1)
  • 1-16: - The script is concise and follows good practices for asynchronous programming in Python.
  • The hardcoded validator_address limits the script's flexibility. Consider allowing the validator address to be passed as an argument or read from a configuration file or environment variable to make the script more versatile.
  • Similar to the previous file, ensure that the AsyncClient and the fetch_validator_commission method handle errors gracefully. Proper error handling is crucial for a robust script.
  • Adding a brief comment or documentation at the top of the script explaining its purpose, usage, and the expected format of the validator_address would improve its maintainability and usability.
examples/chain_client/distribution/query/2_ValidatorOutstandingRewards.py (1)
  • 1-16: - The script is consistent with the previous ones in terms of structure and coding practices.
  • As with the previous scripts, consider enhancing flexibility by allowing the validator_address to be passed as an argument or read from a configuration file or environment variable.
  • Ensure robust error handling for the AsyncClient and the fetch_validator_outstanding_rewards method to handle potential exceptions gracefully.
  • Adding documentation at the top of the script to explain its purpose, usage, and the expected format of the validator_address would be beneficial for maintainability and user guidance.
examples/chain_client/distribution/query/6_DelegationTotalRewards.py (1)
  • 1-18: - This script, similar to the previous ones, is well-structured and follows good asynchronous programming practices.
  • The hardcoded delegator_address limits the script's flexibility. Allowing this address to be dynamically specified, either through command-line arguments or environment variables, would make the script more versatile.
  • Ensure that error handling is robust for both the AsyncClient initialization and the fetch_delegation_total_rewards method to gracefully manage potential exceptions.
  • Adding documentation at the top of the script to explain its purpose, usage, and the expected format of the delegator_address would enhance its maintainability and provide valuable guidance to users.
examples/chain_client/distribution/query/7_DelegatorValidators.py (1)
  • 1-18: - The script is consistent with the previous ones in terms of structure and coding practices.
  • The hardcoded delegator_address limits the script's flexibility. Consider allowing this address to be dynamically specified to enhance the script's usability.
  • Robust error handling for the AsyncClient and the fetch_delegator_validators method is essential to ensure the script can handle potential exceptions gracefully.
  • Adding documentation at the top of the script to explain its purpose, usage, and the expected format of the delegator_address would be beneficial for both maintainability and user guidance.
examples/chain_client/distribution/query/1_ValidatorDistributionInfo.py (1)
  • 1-16: - This script follows the established pattern of good asynchronous programming practices seen in the previous scripts.
  • The hardcoded validator_address limits the script's flexibility. Allowing this address to be dynamically specified would enhance the script's usability.
  • Ensure robust error handling for the AsyncClient and the fetch_validator_distribution_info method to manage potential exceptions effectively.
  • Adding documentation at the top of the script to explain its purpose, usage, and the expected format of the validator_address would improve its maintainability and provide valuable guidance to users.
examples/chain_client/exchange/query/8_DenomDecimal.py (1)
  • 1-19: - The script is well-structured and follows good practices for asynchronous programming in Python.
  • The hardcoded denom value limits the script's flexibility. Consider allowing the denom to be passed as an argument or read from a configuration file or environment variable for greater flexibility.
  • Ensure that the AsyncClient and the fetch_denom_decimal method handle errors gracefully. It's important to catch exceptions that may arise from network issues or invalid responses and provide meaningful error messages to the user.
  • Adding a brief comment or documentation at the top of the script explaining its purpose and usage would enhance its maintainability and usability for new developers or users.
examples/chain_client/exchange/query/9_DenomDecimals.py (1)
  • 1-19: - The script is consistent with the previous ones in terms of structure and coding practices.
  • The hardcoded denoms list limits the script's flexibility. Consider allowing this list to be dynamically specified to enhance the script's usability.
  • Robust error handling for the AsyncClient and the fetch_denom_decimals method is essential to ensure the script can handle potential exceptions gracefully.
  • Adding documentation at the top of the script to explain its purpose, usage, and how to specify the denoms would be beneficial for both maintainability and user guidance.
examples/chain_client/distribution/query/8_DelegatorWithdrawAddress.py (1)
  • 1-18: - This script follows the established pattern of good asynchronous programming practices seen in the previous scripts.
  • The hardcoded delegator_address limits the script's flexibility. Allowing this address to be dynamically specified would enhance the script's usability.
  • Ensure robust error handling for the AsyncClient and the fetch_delegator_withdraw_address method to manage potential exceptions effectively.
  • Adding documentation at the top of the script to explain its purpose, usage, and the expected format of the delegator_address would improve its maintainability and provide valuable guidance to users.
examples/chain_client/exchange/query/48_QueryMarketIDFromVault.py (1)
  • 1-19: - The script is well-structured and follows good practices for asynchronous programming in Python.
  • The hardcoded vault_address limits the script's flexibility. Consider allowing the vault address to be passed as an argument or read from a configuration file or environment variable for greater flexibility.
  • Ensure that the AsyncClient and the fetch_market_id_from_vault method handle errors gracefully. It's important to catch exceptions that may arise from network issues or invalid responses and provide meaningful error messages to the user.
  • Adding a brief comment or documentation at the top of the script explaining its purpose and usage would enhance its maintainability and usability for new developers or users.
examples/chain_client/exchange/query/28_DerivativeMarket.py (1)
  • 1-21: - The script 28_DerivativeMarket.py is well-structured and follows good practices for asynchronous programming in Python. It correctly initializes the AsyncClient and uses it to fetch a derivative market by its ID.
  • It's important to ensure that the market_id used in the script is valid and corresponds to an existing market in the Injective Protocol. If this ID is just for example purposes, consider adding a comment to clarify that users should replace it with a valid market ID.
  • Consider adding error handling around the await client.fetch_chain_derivative_market call to gracefully handle any potential issues that might arise during the API call, such as network issues or invalid market IDs.
examples/chain_client/exchange/query/55_MarketAtomicExecutionFeeMultiplier.py (1)
  • 1-21: - The script 55_MarketAtomicExecutionFeeMultiplier.py is well-structured and follows good practices for asynchronous programming in Python. It correctly initializes the AsyncClient and uses it to fetch the atomic execution fee multiplier for a specific market by its ID.
  • Similar to the previous script, ensure that the market_id used is valid and corresponds to an existing market. If this ID is for example purposes, adding a comment for clarification would be beneficial.
  • Adding error handling around the await client.fetch_market_atomic_execution_fee_multiplier call would improve the robustness of the script by gracefully handling potential issues during the API call.
examples/chain_client/exchange/query/10_SpotMarkets.py (1)
  • 1-22: - The script 10_SpotMarkets.py effectively demonstrates how to query spot markets based on specific criteria (e.g., status and market IDs) using the AsyncClient.
  • Ensure the market_ids array contains valid market IDs. If these IDs are placeholders, it would be helpful to add a comment indicating that users should replace them with actual market IDs.
  • Adding error handling for the await client.fetch_chain_spot_markets call would enhance the script's reliability by addressing potential issues such as network errors or invalid parameters.
examples/chain_client/distribution/query/5_DelegationRewards.py (1)
  • 1-19: - The script 5_DelegationRewards.py is well-structured and demonstrates how to query delegation rewards using the AsyncClient. It correctly initializes the client and fetches rewards for a specified delegator and validator.
  • It's crucial to ensure that the delegator_address and validator_address are valid. If these addresses are placeholders for demonstration purposes, adding a comment to clarify that users should replace them with actual addresses would be beneficial.
  • Consider adding error handling around the await client.fetch_delegation_rewards call to improve the script's robustness by handling potential issues such as invalid addresses or network errors.
examples/chain_client/exchange/query/13_FullSpotMarket.py (1)
  • 1-22: - The script 13_FullSpotMarket.py effectively demonstrates querying detailed information about a specific spot market, including mid-price and top of the book (TOB), using the AsyncClient.
  • As with previous scripts, ensure the market_id is valid and corresponds to an existing market. If this ID is for example purposes, adding a comment for clarification would be helpful.
  • Adding error handling for the await client.fetch_chain_full_spot_market call would enhance the script's reliability by addressing potential issues such as network errors or invalid market IDs.
examples/chain_client/exchange/query/27_DerivativeMarkets.py (1)
  • 1-22: - The script 27_DerivativeMarkets.py is well-structured and demonstrates how to query multiple derivative markets based on specific criteria (e.g., status and market IDs) using the AsyncClient.
  • Ensure the market_ids array contains valid market IDs. If these IDs are placeholders, it would be helpful to add a comment indicating that users should replace them with actual market IDs.
  • Adding error handling for the await client.fetch_chain_derivative_markets call would enhance the script's reliability by addressing potential issues such as network errors or invalid parameters.
examples/chain_client/exchange/query/12_FullSpotMarkets.py (1)
  • 1-23: - The script 12_FullSpotMarkets.py effectively demonstrates querying detailed information about multiple spot markets, including mid-price and top of the book (TOB), based on specific criteria using the AsyncClient.
  • As with previous scripts, ensure the market_ids array contains valid market IDs. If these IDs are placeholders, adding a comment for clarification would be beneficial.
  • Adding error handling for the await client.fetch_chain_full_spot_markets call would improve the script's robustness by addressing potential issues such as network errors or invalid parameters.
examples/chain_client/authz/query/1_Grants.py (1)
  • 1-11: - The update to 1_Grants.py to use environment variables for granter and grantee public addresses enhances security by avoiding hardcoded values. This change aligns with best practices for sensitive information management.
  • Ensure that the .env file or the environment variables are correctly set up with valid public addresses before running the script. It might be helpful to include a sample .env file or documentation comments in the script to guide users on setting up these environment variables.
  • Consider adding error handling for scenarios where environment variables are not set or invalid, to provide clear feedback to the user.
examples/chain_client/distribution/query/4_ValidatorSlashes.py (1)
  • 1-20: - The script 4_ValidatorSlashes.py is well-structured and demonstrates how to query validator slashes using the AsyncClient. It correctly initializes the client and uses pagination to limit the number of results.
  • Ensure the validator_address is valid and corresponds to an existing validator. If this address is a placeholder for demonstration purposes, adding a comment for clarification would be helpful.
  • Adding error handling for the await client.fetch_validator_slashes call would enhance the script's reliability by addressing potential issues such as invalid addresses or network errors.
examples/chain_client/exchange/query/22_DerivativeOrderbook.py (1)
  • 1-25: - The script 22_DerivativeOrderbook.py effectively demonstrates querying the derivative order book for a specific market using the AsyncClient. It correctly initializes the client and uses pagination to limit the number of results.
  • As with previous scripts, ensure the market_id is valid and corresponds to an existing market. If this ID is for example purposes, adding a comment for clarification would be beneficial.
  • Adding error handling for the await client.fetch_chain_derivative_orderbook call would improve the script's robustness by addressing potential issues such as network errors or invalid market IDs.
examples/chain_client/exchange/query/14_SpotOrderbook.py (1)
  • 1-26: - The script is well-structured and follows good practices for asynchronous programming in Python.
  • The use of PaginationOption with a limit of 2 is a good practice for managing large datasets and preventing performance issues.
  • Hardcoding the market_id and order_side in the script limits its flexibility. Consider making these parameters configurable through command-line arguments or environment variables to enhance the script's usability in different scenarios.
  • Ensure that the market_id used in the script is valid and corresponds to an existing market on the Injective Protocol.
examples/chain_client/exchange/query/41_TradeRewardCampaign.py (1)
  • 1-32: - The use of dotenv for loading environment variables is a good practice for managing sensitive information, such as private keys, securely.
  • It's important to validate the existence and correctness of the INJECTIVE_PRIVATE_KEY environment variable before proceeding with its use. Consider adding error handling to provide clear feedback if the environment variable is not set or invalid.
  • The script demonstrates good practices in asynchronous programming and secure handling of private keys by loading them from environment variables instead of hardcoding them in the script.
examples/chain_client/exchange/query/52_MarketVolatility.py (1)
  • 1-30: - The script is well-structured and follows good practices for asynchronous programming in Python.
  • Hardcoding the market_id, trade_grouping_sec, max_age, include_raw_history, and include_metadata in the script limits its flexibility. Consider making these parameters configurable through command-line arguments or environment variables to enhance the script's usability in different scenarios.
  • Ensure that the market_id used in the script is valid and corresponds to an existing market on the Injective Protocol.
examples/chain_client/exchange/query/39_TradeRewardPoints.py (1)
  • 1-34: - The use of dotenv for loading environment variables is a good practice for managing sensitive information, such as private keys, securely.
  • It's important to validate the existence and correctness of the INJECTIVE_PRIVATE_KEY environment variable before proceeding with its use. Consider adding error handling to provide clear feedback if the environment variable is not set or invalid.
  • The script demonstrates good practices in asynchronous programming and secure handling of private keys by loading them from environment variables instead of hardcoding them in the script.
examples/chain_client/exchange/query/40_PendingTradeRewardPoints.py (1)
  • 1-34: - The use of dotenv for loading environment variables is a good practice for managing sensitive information, such as private keys, securely.
  • It's important to validate the existence and correctness of the INJECTIVE_PRIVATE_KEY environment variable before proceeding with its use. Consider adding error handling to provide clear feedback if the environment variable is not set or invalid.
  • The script demonstrates good practices in asynchronous programming and secure handling of private keys by loading them from environment variables instead of hardcoding them in the script.
examples/chain_client/exchange/query/50_IsOptedOutOfRewards.py (1)
  • 1-34: - The use of dotenv for loading environment variables is a good practice for managing sensitive information, such as private keys, securely.
  • It's important to validate the existence and correctness of the INJECTIVE_PRIVATE_KEY environment variable before proceeding with its use. Consider adding error handling to provide clear feedback if the environment variable is not set or invalid.
  • The script demonstrates good practices in asynchronous programming and secure handling of private keys by loading them from environment variables instead of hardcoding them in the script.
examples/chain_client/exchange/query/42_FeeDiscountAccountInfo.py (1)
  • 1-34: - The use of dotenv for loading environment variables is a good practice for managing sensitive information, such as private keys, securely.
  • It's important to validate the existence and correctness of the INJECTIVE_PRIVATE_KEY environment variable before proceeding with its use. Consider adding error handling to provide clear feedback if the environment variable is not set or invalid.
  • The script demonstrates good practices in asynchronous programming and secure handling of private keys by loading them from environment variables instead of hardcoding them in the script.
examples/chain_client/exchange/query/5_AggregateVolumes.py (1)
  • 1-34: - The use of dotenv for loading environment variables is a good practice for managing sensitive information, such as private keys, securely.
  • It's important to validate the existence and correctness of the INJECTIVE_PRIVATE_KEY environment variable before proceeding with its use. Consider adding error handling to provide clear feedback if the environment variable is not set or invalid.
  • The script demonstrates good practices in asynchronous programming and secure handling of private keys by loading them from environment variables instead of hardcoding them in the script.
examples/chain_client/exchange/query/1_SubaccountDeposits.py (1)
  • 1-34: - The use of dotenv for loading environment variables is a good practice for managing sensitive information, such as private keys, securely.
  • It's important to validate the existence and correctness of the INJECTIVE_PRIVATE_KEY environment variable before proceeding with its use. Consider adding error handling to provide clear feedback if the environment variable is not set or invalid.
  • The script demonstrates good practices in asynchronous programming and secure handling of private keys by loading them from environment variables instead of hardcoding them in the script.
examples/chain_client/exchange/query/2_SubaccountDeposit.py (1)
  • 1-34: - The use of dotenv for loading environment variables is a good practice for managing sensitive information, such as private keys, securely.
  • It's important to validate the existence and correctness of the INJECTIVE_PRIVATE_KEY environment variable before proceeding with its use. Consider adding error handling to provide clear feedback if the environment variable is not set or invalid.
  • The script demonstrates good practices in asynchronous programming and secure handling of private keys by loading them from environment variables instead of hardcoding them in the script.
examples/chain_client/exchange/query/30_SubaccountTradeNonce.py (3)
  • 12-12: Loading environment variables at the start of the script is a good practice for managing sensitive information like private keys. This change enhances security by avoiding hard-coded credentials.
  • 22-22: Converting the private key from hex to a PrivateKey object is a secure way to handle sensitive information. Ensure that the environment variable INJECTIVE_PRIVATE_KEY is properly set in all deployment environments.
  • 29-31: Fetching the subaccount trade nonce is a critical operation for ensuring that transactions are processed in the correct order. This change appears to be correctly implemented.
examples/chain_client/exchange/query/38_SubaccountOrderMetadata.py (1)
  • 29-31: Querying for subaccount order metadata is essential for tracking and managing orders. This functionality is correctly implemented, following the same secure practices as seen in the previous file.
examples/chain_client/exchange/query/32_SubaccountPositions.py (1)
  • 29-31: Fetching subaccount positions is crucial for understanding the current state of an account's investments. The implementation here is consistent with best practices observed in previous files.
examples/chain_client/exchange/query/4_AggregateVolume.py (1)
  • 28-32: The script fetches aggregate volume twice, once using the account address and then using the subaccount ID. This demonstrates flexibility in querying based on different identifiers. Ensure that both calls are necessary for the intended use case to avoid redundant network requests.
examples/chain_client/exchange/query/16_AccountAddressSpotOrders.py (1)
  • 27-30: Querying spot orders by account address and market ID is a key operation. However, the market ID is hardcoded, which might limit the script's flexibility. Consider making the market ID a configurable parameter or environment variable for greater versatility.
examples/chain_client/exchange/query/24_AccountAddressDerivativeOrders.py (1)
  • 27-30: Fetching derivative orders by account address and market ID is implemented correctly. As with the spot orders script, consider enhancing flexibility by not hardcoding the market ID.
examples/chain_client/exchange/query/18_SubaccountOrders.py (1)
  • 29-31: Querying subaccount orders with a specific market ID is a crucial functionality. The implementation is consistent with best practices, but again, consider making the market ID configurable for enhanced script flexibility.
examples/chain_client/exchange/query/15_TraderSpotOrders.py (1)
  • 29-31: Fetching trader spot orders by market ID and subaccount ID is well-implemented. As with other scripts, the hardcoded market ID could be made configurable to improve the script's usability in different scenarios.
examples/chain_client/exchange/query/23_TraderDerivativeOrders.py (1)
  • 29-31: The script correctly implements fetching trader derivative orders. The hardcoded market ID issue is consistent across similar scripts; consider making it configurable for better flexibility.
examples/chain_client/exchange/query/19_TraderSpotTransientOrders.py (1)
  • 29-31: Querying for trader spot transient orders is a unique functionality that complements the suite of query scripts. The implementation is correct, but the hardcoded market ID should be addressed as previously mentioned.
examples/chain_client/exchange/query/54_TraderDerivativeConditionalOrders.py (2)
  • 1-4: The addition of dotenv for loading environment variables is a positive change for security, as it moves away from hardcoding sensitive information like private keys. Ensure that the .env file is properly secured and not included in version control.
  • 29-32: Querying trader derivative conditional orders with a hardcoded market_id limits the script's flexibility. Consider making market_id a parameter or an environment variable to enhance the script's usability across different markets.
examples/chain_client/exchange/query/33_SubaccountPositionInMarket.py (2)
  • 1-4: The use of dotenv for loading environment variables is consistent across the example scripts, which is good for maintaining a uniform approach to handling sensitive information like private keys.
  • 29-31: Similar to the previous file, consider enhancing the script's flexibility by making market_id configurable through parameters or environment variables. This would allow the script to be more versatile across different markets.
examples/chain_client/exchange/query/26_TraderDerivativeTransientOrders.py (2)
  • 1-4: The consistent use of dotenv for loading environment variables across example scripts is a good practice, ensuring uniform handling of sensitive information like private keys.
  • 29-31: Encourage making market_id configurable to enhance the script's usability across different markets. This aligns with the PR's objectives of improving flexibility and functionality.
examples/chain_client/exchange/query/34_SubaccountEffectivePositionInMarket.py (2)
  • 1-4: The use of dotenv for loading environment variables continues to be a positive and consistent change across the example scripts, enhancing security by avoiding hardcoded sensitive information.
  • 29-31: Encourage making market_id configurable through parameters or environment variables to improve the script's flexibility and usability across different markets.
examples/chain_client/tokenfactory/1_CreateDenom.py (1)
  • 2-4: The addition of os and dotenv imports for loading environment variables is a significant improvement in handling sensitive information securely by moving away from hardcoded private keys.
examples/chain_client/exchange/query/17_SpotOrdersByHashes.py (2)
  • 1-4: The consistent use of dotenv for loading environment variables across example scripts is a good practice, ensuring uniform handling of sensitive information like private keys.
  • 29-32: Encourage making market_id and order_hashes configurable through parameters or environment variables to improve the script's flexibility and usability across different markets and orders.
examples/chain_client/exchange/query/25_DerivativeOrdersByHashes.py (2)
  • 1-4: The use of dotenv for loading environment variables continues to be a positive and consistent change across the example scripts, enhancing security by avoiding hardcoded sensitive information.
  • 29-32: Encourage making market_id and order_hashes configurable through parameters or environment variables to improve the script's flexibility and usability across different markets and orders.
examples/chain_client/tokenfactory/3_MsgBurn.py (2)
  • 2-4: The addition of os and dotenv imports for loading environment variables is a significant improvement in handling sensitive information securely by moving away from hardcoded private keys.
  • 29-29: The change to use composer.coin for creating the amount is a good practice, as it likely aligns with updated library conventions or best practices. Ensure that this change is consistently applied across all relevant scripts.
examples/chain_client/distribution/1_SetWithdrawAddress.py (1)
  • 1-6: The use of dotenv to load environment variables and os to fetch the private key (INJECTIVE_PRIVATE_KEY) from the environment is a good practice for enhancing security by avoiding hardcoded sensitive information.
examples/chain_client/distribution/3_WithdrawValidatorCommission.py (1)
  • 1-6: The use of dotenv for loading environment variables and os for fetching the private key (INJECTIVE_PRIVATE_KEY) is correctly implemented, enhancing security by avoiding hardcoded sensitive information.
examples/chain_client/distribution/4_FundCommunityPool.py (1)
  • 1-6: The introduction of dotenv for loading environment variables and os for fetching the private key (INJECTIVE_PRIVATE_KEY) is correctly implemented. Additionally, the use of Decimal for precise calculations is a good practice for financial transactions.
examples/chain_client/distribution/2_WithdrawDelegatorReward.py (1)
  • 1-6: The use of dotenv for loading environment variables and os for fetching the private key (INJECTIVE_PRIVATE_KEY) is correctly implemented, enhancing security by avoiding hardcoded sensitive information.
examples/SendToInjective.py (2)
  • 1-5: The introduction of dotenv for loading environment variables and os for fetching the private key (INJECTIVE_PRIVATE_KEY) is correctly implemented, enhancing security by avoiding hardcoded sensitive information.
  • 12-13: Loading the private key from environment variables is a significant improvement in terms of security. This change ensures that sensitive information is not hardcoded into the script.
examples/chain_client/tokenfactory/5_MsgSetDenomMetadata.py (2)
  • 1-4: The use of dotenv for loading environment variables and os for fetching the private key (INJECTIVE_PRIVATE_KEY) is correctly implemented, enhancing security by avoiding hardcoded sensitive information.
  • 13-14: Loading the private key from environment variables is a significant improvement in terms of security. This change ensures that sensitive information is not hardcoded into the script.
examples/chain_client/exchange/3_MsgInstantSpotMarketLaunch.py (1)
  • 1-6: The use of dotenv for loading environment variables and os for fetching the private key (INJECTIVE_PRIVATE_KEY) is correctly implemented, enhancing security by avoiding hardcoded sensitive information.
examples/chain_client/6_MessageBroadcasterWithGranteeAccountWithoutSimulation.py (1)
  • 1-6: The introduction of dotenv for loading environment variables and os for fetching the private key (INJECTIVE_GRANTEE_PRIVATE_KEY) and public address (INJECTIVE_GRANTER_PUBLIC_ADDRESS) is correctly implemented, enhancing security by avoiding hardcoded sensitive information.
examples/chain_client/4_MessageBroadcasterWithGranteeAccount.py (1)
  • 1-6: The use of dotenv for loading environment variables and os for fetching the private key (INJECTIVE_GRANTEE_PRIVATE_KEY) and public address (INJECTIVE_GRANTER_PUBLIC_ADDRESS) is correctly implemented, enhancing security by avoiding hardcoded sensitive information.
examples/chain_client/exchange/13_MsgInstantBinaryOptionsMarketLaunch.py (1)
  • 1-6: The use of dotenv for loading environment variables and os for fetching the private key (INJECTIVE_PRIVATE_KEY) is correctly implemented, enhancing security by avoiding hardcoded sensitive information.
examples/chain_client/exchange/4_MsgInstantPerpetualMarketLaunch.py (1)
  • 1-61: - The script correctly imports necessary modules, loads environment variables using dotenv, and utilizes Decimal for precise financial calculations. This enhances security by avoiding hardcoded private keys and improves accuracy in financial computations.
  • Ensure that the environment variable INJECTIVE_PRIVATE_KEY is securely managed and not exposed in any logs or error messages.
  • Consider adding error handling for os.getenv("INJECTIVE_PRIVATE_KEY") to gracefully handle cases where the environment variable is not set.
examples/chain_client/exchange/5_MsgInstantExpiryFuturesMarketLaunch.py (1)
  • 1-62: - The script for launching an instant expiry futures market correctly uses environment variables and Decimal for precise calculations, following best practices for security and accuracy.
  • Confirm that the INJECTIVE_PRIVATE_KEY environment variable is handled securely throughout the application.
  • Suggest adding error handling for missing or invalid environment variables to improve the script's robustness.
examples/chain_client/5_MessageBroadcasterWithoutSimulation.py (1)
  • 35-56: > 📝 NOTE

This review was outside the diff hunks and was mapped to the diff hunk with the greatest overlap. Original lines [1-59]

  • The script for broadcasting messages without simulation has been updated to use Decimal for financial values and string literals for order types, which enhances clarity and precision.
  • Ensure that the environment variable INJECTIVE_PRIVATE_KEY is securely managed and not exposed in any logs or error messages.
  • Recommend adding error handling for the retrieval of the environment variable to gracefully handle cases where it might not be set.
examples/chain_client/3_MessageBroadcaster.py (1)
  • 35-56: > 📝 NOTE

This review was outside the diff hunks and was mapped to the diff hunk with the greatest overlap. Original lines [1-59]

  • The script for message broadcasting with simulation correctly uses Decimal for financial values and string literals for order types, aligning with best practices for precision and clarity.
  • Confirm that the INJECTIVE_PRIVATE_KEY environment variable is handled securely throughout the application.
  • Suggest adding error handling for missing or invalid environment variables to improve the script's robustness.
tests/test_orderhash.py (1)
  • 24-44: > 📝 NOTE

This review was outside the diff hunks and was mapped to the diff hunk with the greatest overlap. Original lines [1-41]

  • The updates to the test file for order hash computation correctly use Decimal for financial values, enhancing the precision and reliability of the tests.
  • Consider adding more test cases to cover edge cases and potential error scenarios, ensuring comprehensive test coverage.
pyproject.toml (1)
  • 1-6: > 📝 NOTE

This review was outside the diff hunks and was mapped to the diff hunk with the greatest overlap. Original lines [1-54]

  • The update to the project version and the addition of python-dotenv as a dependency in pyproject.toml are correctly implemented, aligning with the PR's objectives to enhance security and flexibility.
  • Ensure that all dependencies are kept up to date and that any new dependencies are evaluated for security and compatibility with the project.
examples/chain_client/exchange/21_MsgRewardsOptOut.py (1)
  • 24-36: > 📝 NOTE

This review was outside the diff hunks and was mapped to the diff hunk with the greatest overlap. Original lines [1-59]

  • The script for opting out of rewards correctly uses environment variables for private keys and follows best practices for secure and precise transactions.
  • Confirm that the INJECTIVE_PRIVATE_KEY environment variable is handled securely throughout the application.
  • Recommend adding error handling for missing or invalid environment variables to improve the script's robustness.
examples/chain_client/auction/1_MsgBid.py (1)
  • 12-20: > 📝 NOTE

This review was outside the diff hunks and was mapped to the diff hunk with the greatest overlap. Original lines [1-59]

  • The script for bidding in auctions correctly uses environment variables for private keys and follows best practices for secure and precise transactions.
  • Ensure that the INJECTIVE_PRIVATE_KEY environment variable is securely managed and not exposed in any logs or error messages.
  • Suggest adding error handling for missing or invalid environment variables to improve the script's robustness.
examples/chain_client/exchange/2_MsgWithdraw.py (1)
  • 24-37: > 📝 NOTE

This review was outside the diff hunks and was mapped to the diff hunk with the greatest overlap. Original lines [1-60]

  • The script for withdrawing funds correctly uses environment variables for private keys and follows best practices for secure and precise transactions.
  • Confirm that the INJECTIVE_PRIVATE_KEY environment variable is handled securely throughout the application.
  • Recommend adding error handling for missing or invalid environment variables to improve the script's robustness.
examples/chain_client/bank/1_MsgSend.py (1)
  • 12-20: > 📝 NOTE

This review was outside the diff hunks and was mapped to the diff hunk with the greatest overlap. Original lines [1-64]

  • The script for sending funds correctly uses environment variables for private keys and follows best practices for secure and precise transactions.
  • Ensure that the INJECTIVE_PRIVATE_KEY environment variable is securely managed and not exposed in any logs or error messages.
  • Suggest adding error handling for missing or invalid environment variables to improve the script's robustness.
examples/chain_client/exchange/1_MsgDeposit.py (6)
  • 2-4: Importing os and dotenv modules and loading environment variables using dotenv.load_dotenv() are good practices for enhancing security by avoiding hardcoded sensitive information like private keys. This change aligns with the PR's objective to improve security and flexibility.
  • 15-17: Successfully loading environment variables and retrieving the private key using os.getenv("INJECTIVE_PRIVATE_KEY") is a secure way to handle sensitive information. Ensure that the environment variable INJECTIVE_PRIVATE_KEY is properly set in the deployment environment to avoid runtime errors.
  • 19-19: Switching to Network.testnet() for selecting the network is a straightforward change. It's important to ensure that this aligns with the intended use case and that any necessary adjustments are made for different environments (e.g., mainnet).
  • 27-27: Converting the private key from hexadecimal to a PrivateKey object using PrivateKey.from_hex(configured_private_key) is correct and secure, assuming the private key is properly managed and stored.
  • 34-36: The update to the msg_deposit method call, including the dynamic setting of the sender, subaccount ID, amount, and denom, is correctly implemented. It's crucial to validate the input values, especially the amount and denom, to prevent unintended transactions.
  • 62-62: The change to use composer.coin for creating a coin object with dynamic gas price and limit calculation is appropriate. This approach ensures that transaction fees are calculated based on the actual gas used, plus a buffer, enhancing efficiency and preventing overpayment.
examples/chain_client/oracle/1_MsgRelayPriceFeedPrice.py (4)
  • 2-4: The addition of os and dotenv modules and the use of dotenv.load_dotenv() to load environment variables are consistent with best practices for handling sensitive information securely. This approach is crucial for maintaining the security of the private key.
  • 15-17: Retrieving the private key from an environment variable using os.getenv("INJECTIVE_PRIVATE_KEY") is a secure and flexible method. It's important to ensure the environment variable is set up correctly in the deployment environment.
  • 27-27: The conversion of the private key from hexadecimal to a PrivateKey object using PrivateKey.from_hex(configured_private_key) is correctly implemented. This ensures that the private key is handled securely throughout the script.
  • 64-64: Updating the method call to composer.coin for fee calculation with dynamic gas price and limit is appropriate. This change ensures that fees are calculated accurately based on the actual gas used, which is a good practice for efficiency and cost management.
examples/chain_client/staking/1_MsgDelegate.py (4)
  • 2-4: The addition of os and dotenv modules and the use of dotenv.load_dotenv() to load environment variables are consistent with best practices for handling sensitive information securely. This approach is crucial for maintaining the security of the private key.
  • 15-17: Retrieving the private key from an environment variable using os.getenv("INJECTIVE_PRIVATE_KEY") is a secure and flexible method. It's important to ensure the environment variable is set up correctly in the deployment environment.
  • 27-27: The conversion of the private key from hexadecimal to a PrivateKey object using PrivateKey.from_hex(configured_private_key) is correctly implemented. This ensures that the private key is handled securely throughout the script.
  • 64-64: Updating the method call to composer.coin for fee calculation with dynamic gas price and limit is appropriate. This change ensures that fees are calculated accurately based on the actual gas used, which is a good practice for efficiency and cost management.
examples/chain_client/insurance/2_MsgUnderwrite.py (4)
  • 2-4: The addition of os and dotenv modules and the use of dotenv.load_dotenv() to load environment variables are consistent with best practices for handling sensitive information securely. This approach is crucial for maintaining the security of the private key.
  • 15-17: Retrieving the private key from an environment variable using os.getenv("INJECTIVE_PRIVATE_KEY") is a secure and flexible method. It's important to ensure the environment variable is set up correctly in the deployment environment.
  • 28-28: The conversion of the private key from hexadecimal to a PrivateKey object using PrivateKey.from_hex(configured_private_key) is correctly implemented. This ensures that the private key is handled securely throughout the script.
  • 64-64: Updating the method call to composer.coin for fee calculation with dynamic gas price and limit is appropriate. This change ensures that fees are calculated accurately based on the actual gas used, which is a good practice for efficiency and cost management.
examples/chain_client/authz/3_MsgRevoke.py (5)
  • 2-4: The addition of os and dotenv modules and the use of dotenv.load_dotenv() to load environment variables are consistent with best practices for handling sensitive information securely. This approach is crucial for maintaining the security of the private key.
  • 15-18: Retrieving the private key and grantee public address from environment variables using os.getenv() is a secure and flexible method. It's important to ensure the environment variables are set up correctly in the deployment environment. This approach enhances the script's flexibility by allowing dynamic configuration.
  • 28-28: The conversion of the private key from hexadecimal to a PrivateKey object using PrivateKey.from_hex(configured_private_key) is correctly implemented. This ensures that the private key is handled securely throughout the script.
  • 35-36: The update to the MsgRevoke instantiation with dynamic granter and grantee values is correctly implemented. It's crucial to validate the input values, especially the grantee public address, to prevent unintended revocations.
  • 64-64: Updating the method call to composer.coin for fee calculation with dynamic gas price and limit is appropriate. This change ensures that fees are calculated accurately based on the actual gas used, which is a good practice for efficiency and cost management.
examples/chain_client/insurance/3_MsgRequestRedemption.py (4)
  • 2-4: The addition of os and dotenv modules and the use of dotenv.load_dotenv() to load environment variables are consistent with best practices for handling sensitive information securely. This approach is crucial for maintaining the security of the private key.
  • 15-17: Retrieving the private key from an environment variable using os.getenv("INJECTIVE_PRIVATE_KEY") is a secure and flexible method. It's important to ensure the environment variable is set up correctly in the deployment environment.
  • 28-28: The conversion of the private key from hexadecimal to a PrivateKey object using PrivateKey.from_hex(configured_private_key) is correctly implemented. This ensures that the private key is handled securely throughout the script.
  • 64-64: Updating the method call to composer.coin for fee calculation with dynamic gas price and limit is appropriate. This change ensures that fees are calculated accurately based on the actual gas used, which is a good practice for efficiency and cost management.
examples/chain_client/insurance/1_MsgCreateInsuranceFund.py (4)
  • 2-4: The addition of os and dotenv modules and the use of dotenv.load_dotenv() to load environment variables are consistent with best practices for handling sensitive information securely. This approach is crucial for maintaining the security of the private key.
  • 15-17: Retrieving the private key from an environment variable using os.getenv("INJECTIVE_PRIVATE_KEY") is a secure and flexible method. It's important to ensure the environment variable is set up correctly in the deployment environment.
  • 28-28: The conversion of the private key from hexadecimal to a PrivateKey object using PrivateKey.from_hex(configured_private_key) is correctly implemented. This ensures that the private key is handled securely throughout the script.
  • 68-68: Updating the method call to composer.coin for fee calculation with dynamic gas price and limit is appropriate. This change ensures that fees are calculated accurately based on the actual gas used, which is a good practice for efficiency and cost management.
examples/chain_client/exchange/17_MsgSubaccountTransfer.py (3)
  • 2-5: The addition of os, dotenv, and Decimal from the decimal module, along with the use of dotenv.load_dotenv() to load environment variables, are consistent with best practices for handling sensitive information securely and performing precise calculations. This approach is crucial for maintaining the security of the private key and ensuring accurate financial transactions.
  • 16-18: Retrieving the private key from an environment variable using os.getenv("INJECTIVE_PRIVATE_KEY") is a secure and flexible method. It's important to ensure the environment variable is set up correctly in the deployment environment. Additionally, the use of Decimal for the amount ensures precise financial calculations, which is critical in financial applications.
  • 28-28: The conversion of the private key from hexadecimal to a PrivateKey object using PrivateKey.from_hex(configured_private_key) is correctly implemented. This ensures that the private key is handled securely throughout the script.
examples/chain_client/exchange/12_MsgCancelDerivativeOrder.py (5)
  • 2-4: - The addition of os and dotenv imports is appropriate for loading environment variables, enhancing the script's security by avoiding hardcoded sensitive information.
  • 15-16: - Using dotenv.load_dotenv() to load environment variables and fetching the private key using os.getenv("INJECTIVE_PRIVATE_KEY") is a secure practice, ensuring that sensitive information is not hardcoded.
  • 27-27: - The conversion of the private key from hexadecimal to a PrivateKey object using PrivateKey.from_hex(configured_private_key) is correct and ensures that the private key is properly handled.
  • 38-38: - The change from composer.MsgCancelDerivativeOrder to composer.msg_cancel_derivative_order follows Python's naming conventions and improves code readability.
  • 66-66: - The modification from composer.Coin to composer.coin for gas fee calculation aligns with Python's naming conventions and ensures consistency across the project.
examples/chain_client/exchange/18_MsgExternalTransfer.py (5)
  • 2-5: - Importing os, Decimal, and dotenv modules is correctly done to support environment variable loading and precise calculations.
  • 16-17: - Loading environment variables and retrieving the private key securely using dotenv.load_dotenv() and os.getenv() is a good practice.
  • 28-28: - Correctly converting the private key from hexadecimal format ensures secure and proper handling of sensitive information.
  • 36-40: - The update to msg_external_transfer for message creation and the use of Decimal for the amount ensure accurate financial transactions and align with best practices.
  • 68-68: - Adjusting the gas fee calculation to use composer.coin is consistent with the project's coding standards and improves readability.
examples/chain_client/exchange/20_MsgIncreasePositionMargin.py (5)
  • 2-5: - The imports of os, Decimal, and dotenv are correctly implemented to support the script's functionality and security.
  • 16-17: - Securely loading the private key from environment variables using dotenv.load_dotenv() and os.getenv() is a best practice for handling sensitive information.
  • 28-28: - The conversion of the private key from a hexadecimal string to a PrivateKey object is correctly implemented, ensuring secure handling of the key.
  • 38-43: - Updating the msg_increase_position_margin function call and using Decimal for the amount parameter ensures precise financial calculations.
  • 70-70: - The modification to use composer.coin for gas fee calculation aligns with the project's coding standards and improves code readability.
examples/chain_client/wasmx/1_MsgExecuteContractCompat.py (4)
  • 3-5: - The addition of os and dotenv imports is correctly done to support environment variable loading, enhancing the script's security.
  • 16-17: - Securely loading the private key from environment variables using dotenv.load_dotenv() and os.getenv() is a good practice.
  • 27-27: - The conversion of the private key from hexadecimal to a PrivateKey object is correctly implemented, ensuring secure handling of the key.
  • 71-71: - The change to use composer.coin for gas fee calculation is consistent with the project's coding standards and improves code readability.
examples/chain_client/peggy/1_MsgSendToEth.py (4)
  • 2-4: - Importing os and dotenv is correctly done to support environment variable loading, enhancing the script's security by avoiding hardcoded sensitive information.
  • 16-17: - Using dotenv.load_dotenv() to load environment variables and fetching the private key using os.getenv("INJECTIVE_PRIVATE_KEY") is a secure practice.
  • 28-28: - The conversion of the private key from hexadecimal to a PrivateKey object using PrivateKey.from_hex(configured_private_key) is correct and ensures that the private key is properly handled.
  • 73-73: - The modification from composer.Coin to composer.coin for gas fee calculation aligns with Python's naming conventions and ensures consistency across the project.
examples/chain_client/exchange/16_MsgCancelBinaryOptionsOrder.py (5)
  • 2-4: - The addition of os and dotenv imports is appropriate for loading environment variables, enhancing the script's security by avoiding hardcoded sensitive information.
  • 15-16: - Using dotenv.load_dotenv() to load environment variables and fetching the private key using os.getenv("INJECTIVE_PRIVATE_KEY") is a secure practice.
  • 27-27: - The conversion of the private key from hexadecimal to a PrivateKey object using PrivateKey.from_hex(configured_private_key) is correct and ensures that the private key is properly handled.
  • 38-38: - The change from a previous method call to composer.msg_cancel_binary_options_order follows Python's naming conventions and improves code readability.
  • 69-69: - The modification from composer.Coin to composer.coin for gas fee calculation aligns with Python's naming conventions and ensures consistency across the project.
examples/chain_client/wasm/1_MsgExecuteContract.py (5)
  • 2-4: - Importing os and dotenv is correctly done to support environment variable loading, enhancing the script's security by avoiding hardcoded sensitive information.
  • 15-16: - Securely loading the private key from environment variables using dotenv.load_dotenv() and os.getenv() is a good practice.
  • 28-28: - The conversion of the private key from hexadecimal to a PrivateKey object is correctly implemented, ensuring secure handling of the key.
  • 36-41: - The update to use composer.coin for creating coin amounts in the funds array is consistent with the project's coding standards and improves code readability.
  • 74-74: - The change to use composer.coin for gas fee calculation is consistent with the project's coding standards and improves code readability.
examples/chain_client/exchange/22_MsgAdminUpdateBinaryOptionsMarket.py (5)
  • 2-5: - Importing os, Decimal, and dotenv modules is correctly done to support environment variable loading and precise calculations.
  • 16-17: - Loading environment variables and retrieving the private key securely using dotenv.load_dotenv() and os.getenv() is a good practice for handling sensitive information.
  • 28-28: - Correctly converting the private key from hexadecimal format ensures secure and proper handling of sensitive information.
  • 41-41: - The update to msg_admin_update_binary_options_market for message creation and the use of Decimal for the settlement price ensure accurate financial transactions and align with best practices.
  • 78-78: - Adjusting the gas fee calculation to use composer.coin is consistent with the project's coding standards and improves readability.
examples/chain_client/exchange/7_MsgCreateSpotMarketOrder.py (5)
  • 2-6: - Importing os, Decimal, and dotenv modules is correctly done to support environment variable loading and precise calculations.
  • 17-18: - Loading environment variables and retrieving the private key securely using dotenv.load_dotenv() and os.getenv() is a good practice for handling sensitive information.
  • 29-29: - Correctly converting the private key from hexadecimal format ensures secure and proper handling of sensitive information.
  • 40-47: - The update to composer.msg_create_spot_market_order for message creation and the use of Decimal for price and quantity values ensure accurate financial transactions and align with best practices.
  • 79-79: - Adjusting the gas fee calculation to use composer.coin is consistent with the project's coding standards and improves readability.
tests/client/chain/grpc/configurable_distribution_query_servicer.py (1)
  • 1-69: - The implementation of ConfigurableDistributionQueryServicer is well-structured, using deques to simulate responses for distribution-related queries. This approach allows for flexible and controlled testing of the gRPC servicer methods.
tests/client/chain/grpc/test_chain_grpc_authz_api.py (1)
  • 10-10: The correction of the typo in the import statement from configurable_autz_query_servicer to configurable_authz_query_servicer is crucial for ensuring the correctness of the test suite. This change allows the test suite to correctly import and utilize the ConfigurableAuthZQueryServicer class, which is essential for testing the ChainGrpcAuthZApi functionalities.
tests/core/test_message_based_transaction_fee_calculator.py (2)
  • 120-127: The changes made to use Decimal for price and quantity fields, and the replacement of boolean flags with an order_type field set to "BUY", significantly improve the precision of financial calculations and the clarity of the code. Using Decimal is crucial for financial applications to avoid rounding errors, and the order_type field enhances readability and maintainability by clearly specifying the type of order.
  • 120-127: The refactoring of message creation in test functions, including the use of lowercase function names and adjustments in message parameters, enhances the consistency and readability of the codebase. This approach aligns with Python's naming conventions and improves the maintainability of the test suite by making the code more intuitive and easier to follow.

Also applies to: 150-157, 185-192

CHANGELOG.md (1)
  • 5-9: The changelog entries for version 1.4.0 are clear and concise, effectively summarizing the significant additions and improvements made in this release. However, there's a minor typographical issue to address:
  • The term "python-dotenv" is correctly spelled, but the static analysis tool suggested "python-dot env" as a replacement. This suggestion is incorrect, and the original spelling should be retained.

Overall, the changelog update for version 1.4.0 is well-documented and adheres to best practices for changelog entries.

examples/chain_client/1_LocalOrderHash.py (4)
  • 2-6: The addition of os, Decimal, and dotenv imports aligns with the PR's objectives to enhance security and flexibility by moving away from hardcoded private keys to environment variables and using Decimal for precise calculations. Ensure that these modules are used consistently throughout the script.
  • 17-18: Loading environment variables at the beginning of the main function is a good practice for managing sensitive information such as private keys. This change enhances security by not hardcoding sensitive data within the script.
  • 48-50: The use of Decimal for specifying price, quantity, and margin ensures precise calculations, which is crucial for financial transactions. Additionally, changing order types to strings ("BUY", "SELL", "BUY_PO", "SELL_PO") improves readability and maintainability of the code.

Also applies to: 57-59, 69-73, 81-85, 177-179, 186-188, 198-202, 210-214

  • 92-96: The adjustments in function calls to composer.msg_batch_create_spot_limit_orders and composer.msg_batch_create_derivative_limit_orders reflect the new naming conventions and enhance the clarity of the code. It's important to verify that these changes are consistently applied across all relevant parts of the project to avoid any integration issues.

Also applies to: 221-225

Verification successful

The search results indicate that the changes to the function names composer.msg_batch_create_spot_limit_orders and composer.msg_batch_create_derivative_limit_orders are consistently applied across the project. This includes their usage in examples, tests, and within the pyinjective module itself, with appropriate deprecation warnings and test cases in place to handle the transition. Therefore, the adjustments reflect the new naming conventions and enhance the clarity of the code as intended.

Scripts Executed

The following scripts were executed for the analysis:


Script:

#!/bin/bash
# Search for old function names to ensure they've been updated everywhere.
rg --type py 'msg_batch_create_spot_limit_orders|msg_batch_create_derivative_limit_orders'

Length of output: 2400

pyinjective/denoms_devnet.ini (2)
  • 167-170: The adjustments to min_price_tick_size, min_display_price_tick_size, min_quantity_tick_size, and min_display_quantity_tick_size for various trading pairs are crucial for reflecting accurate trading conditions on the devnet. It's important to ensure these values are consistent with the intended trading parameters and that similar adjustments are made across all relevant configurations.

Also applies to: 176-179, 185-188, 194-197

  • 317-319: Updates to peggy denominations and decimals for tokens like HDRO, KIRA, and QUNT are necessary for accurate representation and handling of these tokens within the system. Verify that these updates align with the latest token specifications and that all references to these tokens in the project are updated accordingly.

Also applies to: 325-327, 341-343

Verification successful

The script output confirms that references to the tokens HDRO, KIRA, and QUNT are consistently found across different .ini files (denoms_testnet.ini, denoms_mainnet.ini, and denoms_devnet.ini) within the project. This indicates that the updates to peggy denominations and decimals for these tokens are applied across various network configurations (testnet, mainnet, devnet), aligning with the necessity for accurate representation and handling within the system as mentioned in the review comment.

However, verifying the alignment of these updates with the latest token specifications requires external data, which is beyond the scope of this verification process. Therefore, based on the provided context and the script output, the consistency of token references across the project's configuration files is confirmed.

Scripts Executed

The following scripts were executed for the analysis:


Script:

#!/bin/bash
# Search for references to the updated tokens to ensure consistency.
rg --type ini 'HDRO|KIRA|QUNT'

Length of output: 60



Script:

#!/bin/bash
# Search for references to the updated tokens to ensure consistency, specifically targeting .ini files.
rg -g '*.ini' 'HDRO|KIRA|QUNT'

Length of output: 973

pyinjective/core/broadcaster.py (1)
  • 267-267: The conversion of method calls from self._composer.Coin to self._composer.coin for configuring gas fees aligns with Python's convention of using lowercase for method names. This change improves consistency and readability. Ensure that this naming convention is consistently applied throughout the project.

Also applies to: 295-295

pyinjective/core/market.py (1)
  • 172-181: The implementation of margin_to_chain_format in the BinaryOptionMarket class correctly converts human-readable margin values to chain-formatted values, considering special denominations if provided. This addition follows the established pattern of similar conversion methods in the file, using Decimal for precise calculations and supporting optional special_denom for flexibility. The method is consistent with best practices for financial calculations.
tests/client/chain/grpc/test_chain_grpc_distribution_api.py (3)
  • 18-54: The test case test_fetch_module_params is well-structured and effectively tests the functionality of fetching module params from the distribution API. It uses a fixture for the distribution servicer and mocks the API's stub to use this servicer, with clear assertions comparing the expected dictionary with the result from the API call.
  • 56-84: The test case test_fetch_validator_distribution_info effectively tests the API's functionality to fetch validator distribution info. It follows a consistent structure and approach, effectively mocking the necessary responses and validating the API's functionality with clear assertions.
  • 86-110: The test case test_fetch_validator_outstanding_rewards effectively tests the API's functionality to fetch validator outstanding rewards. It follows a consistent pattern with well-structured mocks and clear assertions, demonstrating the effectiveness of the test.
pyinjective/denoms_testnet.ini (3)
  • 145-152: The configuration for Testnet Spot TEST2/INJ and Testnet Spot TEST2/USDT introduces a significant change in min_price_tick_size for TEST2/INJ compared to other configurations. This could potentially be an error or a very specific requirement. Please verify the correctness of the min_price_tick_size for TEST2/INJ being set to 100000000, which is significantly higher than typical values seen in other configurations.
  • 468-470: The addition of the HDRO token configuration introduces a new peggy_denom and specifies its decimals. It's important to ensure that the peggy_denom address and decimals are correctly configured to match the token's specifications on the blockchain. Any discrepancy here could lead to incorrect handling of token amounts in the application.
  • 492-498: The addition of TEST1 and TEST2 tokens with their respective peggy_denom configurations is noted. It's crucial to verify that these tokens and their peggy_denom addresses are correctly set up in the blockchain environment the application interacts with. Misconfiguration could lead to issues with token transfers or balance queries.
tests/core/test_gas_limit_estimator.py (16)
  • 27-33: - The use of Decimal for price and quantity in composer.spot_order is a good practice for financial calculations, ensuring precision.
  • The introduction of order_type instead of boolean flags like is_buy improves readability and flexibility.
  • 44-44: - The method msg_batch_create_spot_limit_orders correctly aggregates the orders. Ensure that the sender parameter is properly validated upstream to prevent misuse.
  • 56-66: - The use of composer.order_data for canceling spot orders is correctly implemented. It's important to ensure that order_hash values are validated and sanitized to prevent any injection attacks.
  • 72-72: - The method msg_batch_cancel_spot_orders is correctly used for batch canceling spot orders. Similar to the creation of orders, ensure that the sender parameter is validated.
  • 84-100: - The use of Decimal for price, quantity, and margin in composer.derivative_order is correctly applied, ensuring accurate financial calculations.
  • The distinction between BUY and SELL order types is clear and enhances the code's readability.
  • 103-103: - The method msg_batch_create_derivative_limit_orders is used appropriately for creating derivative limit orders. As with other methods, ensure the sender parameter is validated to prevent unauthorized use.
  • 115-125: - The use of composer.order_data for canceling derivative orders follows the same pattern as for spot orders. Ensure that order_hash values are properly validated to prevent any potential security issues.
  • 131-131: - The method msg_batch_cancel_derivative_orders correctly implements the batch canceling of derivative orders. Validate the sender parameter as a security measure.
  • 143-157: - The test case for updating orders to create spot orders demonstrates the flexibility of the system to handle various order types. The use of Decimal for precise calculations is consistent and appropriate.
  • 178-194: - The test case for updating orders to create derivative orders is well-implemented, showcasing the system's ability to handle complex order types with precision using Decimal.
  • 233-249: - The test case for updating orders to create binary options orders is correctly implemented, using Decimal for financial calculations and clearly distinguishing between BUY and SELL order types.
  • 271-281: - The test case for batch updating orders to cancel spot orders is implemented correctly. It's important to ensure that order_hash values are validated to prevent any potential security issues.
  • 305-315: - The test case for batch updating orders to cancel derivative orders follows the established pattern and is correctly implemented. Validate order_hash values for security.
  • 339-349: - The test case for batch updating orders to cancel binary options orders is correctly implemented. As with other order types, ensure that order_hash values are validated.
  • 434-440: - The test case for executing a message within another message (MsgExec) is correctly implemented, showcasing advanced use cases. Ensure that nested messages are validated and sanitized appropriately.
  • 502-509: - The method msg_create_spot_limit_order is used correctly for creating a spot limit order. The use of Decimal for price and quantity ensures precision in financial calculations.
tests/core/test_market.py (2)
  • 251-272: - The method test_convert_margin_to_chain_format_with_fixed_denom correctly tests the conversion of margin values to chain format using a fixed denomination. This test ensures that margin values are accurately converted, taking into account the fixed denomination's specifics.
  • 274-285: - The method test_convert_margin_to_chain_format_without_fixed_denom tests the conversion of margin values to chain format without a fixed denomination. This test verifies the flexibility of the conversion functionality to handle different market configurations.
pyinjective/client/chain/grpc/chain_grpc_exchange_api.py (3)
  • 13-16: The class initialization is well-implemented, correctly setting up the necessary components for making gRPC calls. It's good practice to separate the creation of the stub and the request assistant, as it enhances modularity and testability.
  • 18-578: All async methods in the ChainGrpcExchangeApi class follow a consistent and clear pattern for making gRPC calls. This consistency is beneficial for maintainability and readability. It's also good to see the use of type hints for method return types, enhancing code clarity and developer experience.
  • 577-578: The _execute_call helper method is well-designed, abstracting the execution of gRPC calls and centralizing error handling and metadata management. This design choice simplifies the public method implementations and enhances code maintainability.
pyinjective/denoms_mainnet.ini (19)
  • 685-692: The addition of the DOJO/INJ spot trading pair with its corresponding tick sizes and quantities is noted. Ensure that these values have been validated against the current market requirements and Injective Protocol's standards for precision and minimum quantities.
  • 694-701: The addition of the GYEN/USDT spot trading pair introduces a fiat-pegged stablecoin pair. It's crucial to verify the demand for this trading pair within the Injective Protocol ecosystem and ensure that the peggy_denom value for GYEN is correctly set up in the system to facilitate seamless transactions.
  • 703-710: The addition of the USDCnb/USDT spot trading pair is observed. Given the naming convention, it appears to be a specific version or network bridge of USDC. Confirm that the peggy_denom and decimals for USDCnb are correctly configured and that there's clear documentation for users regarding this specific token variant.
  • 713-719: The ANDR/INJ spot trading pair has been added with a significant minimum price tick size of 10,000,000 and a display tick size of 0.00001. This configuration suggests a high-value asset or a specific use case. Ensure that this configuration aligns with the asset's market characteristics and the platform's trading strategy.
  • 721-728: The addition of the hINJ/INJ spot trading pair is noted. Given the naming, this might represent a wrapped or staked version of INJ. Confirm that the community and stakeholders are aware of this new trading pair and that the necessary infrastructure (e.g., smart contracts for wrapping/unwrapping) is in place and has been audited for security.
  • 739-746: The addition of the PHUC/INJ spot trading pair with its specific tick sizes and quantities is observed. Given the unique naming, ensure that there's adequate information available about this asset, including its utility and how it integrates with the Injective Protocol ecosystem.
  • 748-755: The addition of the QUNT/INJ spot trading pair is noted. It's important to verify the demand for this trading pair within the Injective Protocol ecosystem and ensure that the peggy_denom value for QUNT is correctly set up in the system to facilitate seamless transactions.
  • 757-764: The addition of the WHALE/INJ spot trading pair introduces a potentially high-value asset pair. Confirm that the peggy_denom for WHALE is correctly configured and that there's clear documentation for users regarding this asset, including its origins and utility within the ecosystem.
  • 766-773: The addition of the HDRO/INJ spot trading pair is observed. Given the specific configuration, ensure that this trading pair aligns with the market demand and that the HDRO asset is well-documented within the Injective Protocol ecosystem.
  • 776-782: The addition of the PYTH/INJ spot trading pair with a significant minimum price tick size of 10,000,000 suggests a high-value or high-precision asset. Verify that this configuration aligns with PYTH's market characteristics and that there's clear communication to users about this trading pair.
  • 838-845: The addition of the OSMO/USDT PERP derivative trading pair with specific tick sizes and quantities is noted. Ensure that these values have been validated against current market requirements and Injective Protocol's standards for precision and minimum quantities in derivative markets.
  • 857-863: The BONK/USDT PERP derivative trading pair introduces a unique configuration with a minimum price tick size of 0.01 and a display tick size of 0.00000001. This configuration suggests a high-precision or high-volatility asset. Confirm that this aligns with BONK's market characteristics and the platform's trading strategy for derivatives.
  • 937-944: The addition of the AVAX/USDT PERP derivative trading pair is observed. Given AVAX's prominence in the cryptocurrency market, ensure that the derivative contract specifications, including tick sizes and quantities, are aligned with market expectations and Injective Protocol's risk management practices.
  • 946-953: The addition of the SUI/USDT PERP derivative trading pair introduces a newer asset to the derivatives market. Verify the demand for this trading pair within the Injective Protocol ecosystem and ensure that the contract specifications are clearly communicated to users.
  • 955-962: The WIF/USDT PERP derivative trading pair is added with specific tick sizes and quantities. Given the unique naming, confirm that there's adequate information available about this asset, including its utility and how it integrates with the Injective Protocol's derivatives market.
  • 973-980: The addition of the ARB/USDT PERP derivative trading pair is noted. Ensure that these values have been validated against current market requirements and Injective Protocol's standards for precision and minimum quantities in derivative markets, especially considering ARB's potential market dynamics.
  • 982-989: The W/USDT PERP derivative trading pair introduces a potentially high-value asset pair. Confirm that the peggy_denom for W is correctly configured and that there's clear documentation for users regarding this asset, including its origins and utility within the derivatives market.
  • 991-998: The addition of the LINK/USDT PERP derivative trading pair with specific tick sizes and quantities is observed. Given LINK's prominence in the cryptocurrency market, ensure that the derivative contract specifications are aligned with market expectations and Injective Protocol's risk management practices.
  • 1000-1007: The addition of the DOGE/USDT PERP derivative trading pair introduces a popular meme coin to the derivatives market. Confirm that the contract specifications, including tick sizes and quantities, are clearly communicated to users and align with DOGE's market characteristics and volatility.
tests/test_composer.py (31)
  • 79-79: The use of a large literal number (1_000_000) for the amount parameter in test_msg_mint is clear and improves readability. However, it's important to ensure that such large numbers are handled correctly in the context of the application, especially when dealing with financial transactions.
  • 178-208: In test_msg_deposit, the conversion of amount to a chain-formatted value using expected_amount = token.chain_formatted_value(human_readable_value=Decimal(amount)) is a good practice for ensuring consistency in how amounts are represented and processed. It's crucial to verify that the chain_formatted_value method accurately handles the conversion, especially with respect to rounding and precision.
Verification successful

The implementation of chain_formatted_value in pyinjective/core/token.py correctly handles rounding and precision by using the Decimal class for arithmetic operations and scaling the human_readable_value by 10^decimals. This approach is consistent with best practices for converting between human-readable and chain-formatted values in cryptocurrency applications. The review comment's concern about ensuring consistency in how amounts are represented and processed is addressed by this implementation.

Scripts Executed

The following scripts were executed for the analysis:


Script:

#!/bin/bash
# Verify the implementation of chain_formatted_value to ensure it handles rounding and precision correctly.
cat tests/test_composer.py | grep -A 10 "def chain_formatted_value"

Length of output: 69



Script:

#!/bin/bash
# Search for the implementation of chain_formatted_value across the entire codebase
rg "def chain_formatted_value" --files-with-matches

Length of output: 79



Script:

#!/bin/bash
# Display the implementation of chain_formatted_value from pyinjective/core/token.py
cat pyinjective/core/token.py | grep -A 20 "def chain_formatted_value"

Length of output: 219

* 209-238: The test `test_msg_withdraw` follows a similar pattern to `test_msg_deposit`, including the conversion of amounts for consistency. It's equally important here to ensure that the conversion logic is robust and tested, especially given the financial implications of withdrawal operations.
Verification successful

The implementation of chain_formatted_value in pyinjective/core/token.py correctly converts human-readable values to the chain's format by adjusting for the token's decimal places. This method is appropriately used in the test_msg_withdraw to ensure that withdrawal amounts are correctly formatted for blockchain transactions. The review comment's concern about the importance of robust conversion logic, especially for financial operations, is addressed by this implementation.

Scripts Executed

The following scripts were executed for the analysis:


Script:

#!/bin/bash
# Reuse the previous script to verify the implementation of chain_formatted_value for withdrawal amounts.
cat tests/test_composer.py | grep -A 10 "def chain_formatted_value"

Length of output: 69



Script:

#!/bin/bash
# Search for the definition of chain_formatted_value across the entire codebase
rg "def chain_formatted_value" --context 10

Length of output: 662

* 240-279: In `test_msg_instant_spot_market_launch`, the calculation of `expected_min_price_tick_size` and `expected_min_quantity_tick_size` involves adjusting for token decimals and additional chain format decimals. This approach is commendable for its attention to detail in ensuring that tick sizes are accurately represented on-chain. It's important to validate these calculations against expected outcomes to prevent any unintended market behavior. * 281-342: The `test_msg_instant_perpetual_market_launch` method includes comprehensive testing of various market parameters, including fee rates and margin ratios, converted for chain compatibility. This thorough testing is crucial for ensuring that market launches behave as expected, particularly in terms of financial risk management. Continuous validation of these parameters against real-world scenarios is recommended.
Verification successful

The review comment regarding the test_msg_instant_perpetual_market_launch method is justified. The method indeed includes comprehensive testing of various market parameters, such as fee rates and margin ratios, converted for chain compatibility. This testing is crucial for ensuring that market launches behave as expected, particularly in terms of financial risk management. The recommendation for continuous validation of these parameters against real-world scenarios is well-founded, emphasizing the importance of maintaining robustness under various market conditions.

Scripts Executed

The following scripts were executed for the analysis:


Script:

#!/bin/bash
# Suggest manual review for validating market parameters in test_msg_instant_perpetual_market_launch.
echo "Manual review recommended for validating market parameters in test_msg_instant_perpetual_market_launch."

Length of output: 216

* 344-408: The `test_msg_instant_expiry_futures_market_launch` function tests the launching of an expiry futures market with various parameters, including oracle settings and fee rates. Given the complexity of futures markets, it's essential to ensure that all parameters are correctly set and that the market behaves as expected under various conditions. * 410-451: The `test_spot_order` function demonstrates the creation of a spot order with detailed assertions on the expected order structure. This level of detail is crucial for ensuring that orders are correctly formatted and processed by the system. It's recommended to also include negative test cases to ensure robust error handling.

Consider adding negative test cases to ensure the system gracefully handles invalid or malformed orders.

  • 453-497: In test_derivative_order, similar to the spot order test, the creation and validation of a derivative order are thoroughly tested. Including tests for edge cases, such as orders with zero quantity or invalid market IDs, would further strengthen the test suite's coverage and robustness.

Enhance the test suite by including edge cases and negative scenarios for derivative orders to ensure comprehensive coverage.

  • 499-547: The test_msg_create_spot_limit_order method correctly tests the creation of a spot limit order, ensuring that all fields are properly set. It's important to verify that the system's order matching logic correctly interprets and executes these orders as intended, especially in edge cases.
  • 549-584: The test_msg_batch_create_spot_limit_orders function tests the batch creation of spot limit orders, an important feature for users who need to execute multiple orders efficiently. Ensuring that the batch processing logic maintains order integrity and correctly handles partial failures is critical.
  • 586-633: The test_msg_create_spot_market_order method tests the creation of a spot market order. It's crucial to ensure that market orders are executed according to current market conditions and that the test reflects realistic scenarios, including liquidity considerations.
  • 635-661: In test_msg_cancel_spot_order, the cancellation of a spot order is tested. It's important to verify that the cancellation process correctly identifies and nullifies the specified order without affecting other orders, especially in high-frequency trading environments.
  • 663-688: The test_msg_batch_cancel_spot_orders function tests the batch cancellation of spot orders. This feature is critical for users needing to quickly adjust their positions. Ensuring that the batch cancellation process is atomic and either fully succeeds or reverts in case of failure is essential for maintaining market integrity.
  • 690-787: The test_msg_batch_update_orders method tests a complex scenario involving the creation and cancellation of multiple order types across different markets. This comprehensive test is crucial for ensuring that the system can handle complex order management operations. It's recommended to also test the resilience of this feature under high load or failure conditions.

Consider stress testing the batch update orders feature to ensure its resilience and reliability under high load or partial failure conditions.

  • 789-812: In test_msg_privileged_execute_contract, the execution of a contract with privileged access is tested. Given the potential security implications, it's vital to ensure that only authorized entities can invoke this functionality and that all security checks are robust and comprehensive.
  • 814-863: The test_msg_create_derivative_limit_order function tests the creation of a derivative limit order, which is essential for derivative market participants. Ensuring that these orders are accurately represented and processed in the matching engine, especially under various market conditions, is crucial.
  • 866-901: In test_msg_batch_create_derivative_limit_orders, the batch creation of derivative limit orders is tested. This functionality is important for traders managing large portfolios. Verifying that the system can efficiently process and match these orders in batch mode without performance degradation is essential.
  • 904-953: The test_msg_create_derivative_market_order method tests the creation of a derivative market order. It's important to ensure that these orders are executed with respect to current market liquidity and that slippage is handled appropriately. Testing against various liquidity scenarios would enhance the robustness of this test.

Enhance testing of derivative market orders by including various liquidity scenarios to assess slippage handling and execution accuracy.

  • 956-995: In test_msg_cancel_derivative_order, the cancellation of a derivative order is tested. Ensuring that the cancellation logic correctly identifies the target order without impacting other market participants is crucial. Additionally, testing the system's ability to handle rapid order cancellations in volatile markets is recommended.

Consider testing the derivative order cancellation feature under scenarios of high market volatility and rapid order submissions/cancellations to ensure system stability and correctness.

  • 997-1021: The test_msg_batch_cancel_derivative_orders function tests the batch cancellation of derivative orders. Similar to spot order batch cancellations, verifying the atomicity and reliability of this process is essential, especially in fast-moving derivative markets where timing is critical.
  • 1023-1085: The test_msg_instant_binary_options_market_launch method tests the launching of a binary options market with various parameters. Given the unique characteristics of binary options markets, ensuring that all parameters are correctly set and that the market behaves as expected under different scenarios is critical.
  • 1087-1136: In test_msg_create_binary_options_limit_order, the creation of a binary options limit order is tested. This test is important for ensuring that binary options orders are correctly processed and matched. Including tests for scenarios where the market moves significantly before order execution could provide additional insights into system behavior.

Include scenarios in testing where the market moves significantly before the execution of binary options limit orders to assess system behavior under such conditions.

  • 1139-1188: The test_msg_create_binary_options_market_order function tests the creation of a binary options market order. It's crucial to verify that these orders are executed promptly and accurately, taking into account the unique payout structures of binary options. Testing against a range of market conditions would be beneficial.

Expand testing of binary options market orders to include a wider range of market conditions, focusing on execution speed and accuracy.

  • 1191-1230: In test_msg_cancel_derivative_order for binary options, the cancellation logic is tested. Ensuring that binary options orders can be canceled efficiently and without unintended consequences is important for market integrity. Testing the cancellation process under high-frequency trading conditions could highlight potential areas for improvement.

Test the cancellation process for binary options orders under high-frequency trading conditions to ensure efficiency and market integrity.

  • 1232-1264: The test_msg_subaccount_transfer method tests the transfer of funds between subaccounts. This functionality is critical for managing funds within the platform. Ensuring that transfers are atomic and that the system correctly handles edge cases, such as insufficient funds, is essential.
  • 1266-1298: In test_msg_external_transfer, the transfer of funds to an external subaccount is tested. Given the potential for funds to leave the platform, it's crucial to ensure that these transfers are secure and that all necessary validations are in place to prevent unauthorized or fraudulent transfers.
  • 1300-1331: The test_msg_liquidate_position function tests the liquidation of a position in a derivative market. This critical functionality must be thoroughly tested to ensure that liquidations are executed fairly and accurately, especially under extreme market conditions.

Enhance testing of position liquidation to include scenarios of extreme market volatility and stress conditions to ensure fair and accurate execution.

  • 1333-1352: In test_msg_emergency_settle_market, the emergency settlement of a market is tested. This functionality is a critical safety mechanism and must be tested extensively to ensure that it can be executed reliably and without unintended consequences in real emergency situations.

Conduct comprehensive testing of the emergency market settlement feature, including simulations of real emergency scenarios, to validate its reliability and effectiveness.

  • 1355-1382: The test_msg_external_transfer method for increasing position margin in a derivative market is tested. Ensuring that margin increases are processed correctly and in a timely manner is crucial for maintaining the necessary collateral levels and preventing unintended liquidations.
  • 1385-1398: The test_msg_rewards_opt_out function tests the opt-out functionality for rewards. This feature allows users to decline participation in reward programs, and it's important to ensure that the opt-out process is straightforward and irreversible, as desired by the user.
  • 1401-1431: In test_msg_admin_update_binary_options_market, the administrative update of a binary options market is tested. Given the potential impact of administrative actions on market participants, it's crucial to ensure that these updates are authorized, logged, and transparent to all affected parties.
tests/test_async_client_deprecation_warnings.py (1)
  • 24-24: The correction in the import statement from configurable_autz_query_servicer to configurable_authz_query_servicer is accurate and resolves a typo, ensuring the correct module is imported.
pyinjective/composer.py (43)
  • 140-143: The method Coin is marked as deprecated with a warning to use coin instead. This is a good practice for maintaining backward compatibility while guiding users towards the new method.
  • 164-167: The method OrderData is marked as deprecated with a warning to use order_data instead. Proper deprecation warnings are essential for a smooth transition to new methods.
  • 212-215: The method SpotOrder is marked as deprecated with a warning to use spot_order instead. This consistent approach to deprecation across the file helps maintain code clarity and guides users effectively.
  • 304-307: The method DerivativeOrder is marked as deprecated with a warning to use derivative_order instead. It's good to see a consistent pattern in handling deprecated methods across the file.
  • 489-493: The method MsgDeposit is marked as deprecated with a warning to use msg_deposit instead. This deprecation notice is crucial for guiding users towards the updated method.
  • 511-515: The method MsgWithdraw is marked as deprecated with a warning to use msg_withdraw instead. Consistent deprecation warnings across different methods help in maintaining backward compatibility while encouraging the use of updated methods.
  • 660-663: The method MsgCreateSpotLimitOrder is marked as deprecated with a warning to use msg_create_spot_limit_order instead. This approach ensures users are aware of the newer, preferred methods.
  • 717-721: The method MsgBatchCreateSpotLimitOrders is marked as deprecated with a warning to use msg_batch_create_spot_limit_orders instead. This consistent approach to deprecation is beneficial for users transitioning to new methods.
  • 733-747: The method MsgCreateSpotMarketOrder is marked as deprecated with a warning to use msg_create_spot_market_order instead. Properly deprecating methods and guiding users to the new implementations is crucial for a smooth transition.
  • 792-803: The method MsgCancelSpotOrder is marked as deprecated with a warning to use msg_cancel_spot_order instead. This consistent deprecation strategy across the file helps users navigate the changes effectively.
  • 829-832: The method MsgBatchCancelSpotOrders is marked as deprecated with a warning to use msg_batch_cancel_spot_orders instead. This approach ensures that users are informed about the newer, preferred methods.
  • 840-844: The method MsgBatchUpdateOrders is marked as deprecated with a warning to use msg_batch_update_orders instead. Consistent deprecation warnings across different methods help in maintaining backward compatibility while encouraging the use of updated methods.
  • 887-893: The method MsgPrivilegedExecuteContract is marked as deprecated with a warning to use msg_privileged_execute_contract instead. This deprecation notice is crucial for guiding users towards the updated method.
  • 929-932: The method MsgCreateDerivativeLimitOrder is marked as deprecated with a warning to use msg_create_derivative_limit_order instead. This approach ensures users are aware of the newer, preferred methods.
  • 1008-1013: The method MsgBatchCreateDerivativeLimitOrders is marked as deprecated with a warning to use msg_batch_create_derivative_limit_orders instead. This consistent approach to deprecation is beneficial for users transitioning to new methods.
  • 1038-1041: The method MsgCreateDerivativeMarketOrder is marked as deprecated with a warning to use msg_create_derivative_market_order instead. Properly deprecating methods and guiding users to the new implementations is crucial for a smooth transition.
  • 1119-1129: The method MsgCancelDerivativeOrder is marked as deprecated with a warning to use msg_cancel_derivative_order instead. This consistent deprecation strategy across the file helps users navigate the changes effectively.
  • 1173-1177: The method MsgBatchCancelDerivativeOrders is marked as deprecated with a warning to use msg_batch_cancel_derivative_orders instead. This approach ensures that users are informed about the newer, preferred methods.
  • 1207-1211: The method MsgInstantBinaryOptionsMarketLaunch is marked as deprecated with a warning to use msg_instant_binary_options_market_launch instead. Consistent deprecation warnings across different methods help in maintaining backward compatibility while encouraging the use of updated methods.
  • 1299-1302: The method MsgCreateBinaryOptionsLimitOrder is marked as deprecated with a warning to use msg_create_binary_options_limit_order instead. This deprecation notice is crucial for guiding users towards the updated method.
  • 1393-1396: The method MsgCreateBinaryOptionsMarketOrder is marked as deprecated with a warning to use msg_create_binary_options_market_order instead. This approach ensures users are aware of the newer, preferred methods.
  • 1484-1487: The method MsgCancelBinaryOptionsOrder is marked as deprecated with a warning to use msg_cancel_binary_options_order instead. This consistent approach to deprecation is beneficial for users transitioning to new methods.
  • 1530-1533: The method MsgSubaccountTransfer is marked as deprecated with a warning to use msg_subaccount_transfer instead. Properly deprecating methods and guiding users to the new implementations is crucial for a smooth transition.
  • 1572-1575: The method MsgExternalTransfer is marked as deprecated with a warning to use msg_external_transfer instead. This consistent deprecation strategy across the file helps users navigate the changes effectively.
  • 1613-1616: The method MsgLiquidatePosition is marked as deprecated with a warning to use msg_liquidate_position instead. This approach ensures that users are informed about the newer, preferred methods.
  • 1654-1657: The method MsgIncreasePositionMargin is marked as deprecated with a warning to use msg_increase_position_margin instead. Consistent deprecation warnings across different methods help in maintaining backward compatibility while encouraging the use of updated methods.
  • 1692-1696: The method MsgRewardsOptOut is marked as deprecated with a warning to use msg_rewards_opt_out instead. This deprecation notice is crucial for guiding users towards the updated method.
  • 1713-1716: The method MsgAdminUpdateBinaryOptionsMarket is marked as deprecated with a warning to use msg_admin_update_binary_options_market instead. This approach ensures users are aware of the newer, preferred methods.
  • 2107-2110: The method MsgWithdrawDelegatorReward is marked as deprecated with a warning to use msg_withdraw_delegator_reward instead. This consistent approach to deprecation is beneficial for users transitioning to new methods.
  • 2121-2124: The method MsgWithdrawValidatorCommission is marked as deprecated with a warning to use msg_withdraw_validator_commission instead. Properly deprecating methods and guiding users to the new implementations is crucial for a smooth transition.
  • 146-151: The new coin method correctly creates an instance of the Coin gRPC type, considering the amount is already expressed in chain format. This method simplifies the creation of Coin objects and is a good addition for better code readability and maintainability.
  • 153-159: The create_coin_amount method is a valuable addition, allowing for the creation of Coin gRPC types with precise calculations using the Decimal type. This method enhances the flexibility and accuracy of handling token amounts.
  • 182-192: The order_data method introduces a more flexible way to create OrderData objects by allowing optional parameters for conditional, buy, and market order types. This method improves the modularity and usability of order creation within the SDK.
  • 249-281: The spot_order method is a significant improvement over its deprecated counterpart, offering more precise handling of quantities and prices using the Decimal type and allowing for a clearer definition of order types. This method enhances the SDK's functionality for creating spot orders.
  • 362-393: The derivative_order method is a comprehensive addition that allows for the creation of derivative orders with detailed parameters, including margin and trigger price. This method significantly enhances the SDK's capabilities for handling derivative orders.
  • 395-427: The binary_options_order method is a new functionality that extends the SDK's capabilities to handle binary options orders. It introduces additional parameters like denom for special handling of quantities and prices, which is a valuable addition for users dealing with binary options.
  • 502-509: The msg_deposit method is a new addition that replaces the deprecated MsgDeposit method. It correctly uses the Decimal type for the amount, enhancing the precision and flexibility of deposit operations within the SDK.
  • 524-531: The msg_withdraw method is a new addition that replaces the deprecated MsgWithdraw method. It correctly uses the Decimal type for the amount, enhancing the precision and flexibility of withdrawal operations within the SDK.
  • 691-713: The msg_create_spot_limit_order method is a significant improvement over its deprecated counterpart, offering more precise handling of quantities and prices using the Decimal type and allowing for a clearer definition of order types. This method enhances the SDK's functionality for creating spot limit orders.
  • 728-731: The msg_batch_create_spot_limit_orders method is a new addition that replaces the deprecated MsgBatchCreateSpotLimitOrders method. It correctly handles a list of SpotOrder objects, enhancing the SDK's batch processing capabilities for spot limit orders.
  • 766-790: The msg_create_spot_market_order method is a new addition that replaces the deprecated MsgCreateSpotMarketOrder method. It introduces more precise handling of quantities and prices using the Decimal type and allows for a clearer definition of order types, enhancing the SDK's functionality for creating spot market orders.
  • 812-826: The msg_cancel_spot_order method is a new addition that replaces the deprecated MsgCancelSpotOrder method. It correctly handles optional parameters for conditional, buy, and market order types, enhancing the SDK's functionality for canceling spot orders.
  • 835-838: The msg_batch_cancel_spot_orders method is a new addition that replaces the deprecated MsgBatchCancelSpotOrders method. It correctly handles a list of OrderData objects, enhancing the SDK's batch processing capabilities for canceling spot orders.
pyinjective/async_client.py (5)
  • 15-16: The addition of imports for ChainGrpcDistributionApi and ChainGrpcExchangeApi is aligned with the PR objectives to enhance the async_client.py with new functionalities for interacting with the Injective Protocol's distribution and exchange modules. This change is necessary for the subsequent use of these APIs within the AsyncClient class.
  • 183-194: The initialization of distribution_api and chain_exchange_api within the AsyncClient constructor is correctly implemented. The use of self.chain_channel as the channel and the lambda function for metadata_provider ensures that these APIs can utilize the established gRPC channel and metadata for requests. This setup is essential for enabling the new functionalities related to the Injective Protocol's distribution and exchange modules as mentioned in the PR objectives.
  • 589-648: The methods added for fetching distribution information, such as fetch_validator_distribution_info, fetch_validator_outstanding_rewards, fetch_validator_commission, fetch_validator_slashes, fetch_delegation_rewards, fetch_delegation_total_rewards, fetch_delegator_validators, fetch_delegator_withdraw_address, and fetch_community_pool, are correctly implemented. They utilize the distribution_api to make the respective gRPC calls. This addition aligns with the PR objectives to enhance the client's capabilities in interacting with the distribution module of the Injective Protocol. It's important to ensure that these methods are accompanied by appropriate error handling and validation where necessary, although the specifics of such validations are not visible in the provided context.
  • 651-1037: The methods added for interacting with the Injective Protocol's exchange module, such as fetch_subaccount_deposits, fetch_subaccount_deposit, fetch_exchange_balances, fetch_aggregate_volume, fetch_aggregate_volumes, fetch_aggregate_market_volume, fetch_aggregate_market_volumes, fetch_denom_decimal, fetch_denom_decimals, fetch_chain_spot_markets, fetch_chain_spot_market, fetch_chain_full_spot_markets, fetch_chain_full_spot_market, fetch_chain_spot_orderbook, fetch_chain_trader_spot_orders, fetch_chain_account_address_spot_orders, fetch_chain_spot_orders_by_hashes, fetch_chain_subaccount_orders, fetch_chain_trader_spot_transient_orders, fetch_spot_mid_price_and_tob, fetch_derivative_mid_price_and_tob, fetch_chain_derivative_orderbook, fetch_chain_trader_derivative_orders, fetch_chain_account_address_derivative_orders, fetch_chain_derivative_orders_by_hashes, fetch_chain_trader_derivative_transient_orders, fetch_chain_derivative_markets, fetch_chain_derivative_market, fetch_derivative_market_address, fetch_subaccount_trade_nonce, fetch_chain_positions, fetch_chain_subaccount_positions, fetch_chain_subaccount_position_in_market, fetch_chain_subaccount_effective_position_in_market, fetch_chain_perpetual_market_info, fetch_chain_expiry_futures_market_info, fetch_chain_perpetual_market_funding, fetch_subaccount_order_metadata, fetch_trade_reward_points, fetch_pending_trade_reward_points, fetch_trade_reward_campaign, fetch_fee_discount_account_info, fetch_fee_discount_schedule, fetch_balance_mismatches, fetch_balance_with_balance_holds, fetch_fee_discount_tier_statistics, fetch_mito_vault_infos, fetch_market_id_from_vault, fetch_historical_trade_records, fetch_is_opted_out_of_rewards, fetch_opted_out_of_rewards_accounts, fetch_market_volatility, fetch_chain_binary_options_markets, fetch_trader_derivative_conditional_orders, and fetch_market_atomic_execution_fee_multiplier are correctly implemented. These methods significantly expand the client's functionality, allowing for comprehensive interaction with various aspects of the exchange module. It's crucial that these methods are tested thoroughly to ensure they handle all possible edge cases and errors gracefully. Additionally, considering the extensive list of new functionalities, documentation should be updated accordingly to help users understand how to use these new methods effectively.
  • 3229-3236: The refactoring of the token representation logic within the _token_representation method is a positive change that improves the maintainability and readability of the code. By extracting the logic for determining a unique symbol and creating a Token instance into a separate method, the code becomes more modular and easier to understand. This refactoring aligns with best practices for code organization and modularity. However, it's important to ensure that this method is called correctly throughout the class and that any changes to the Token model or its usage are consistently applied.
poetry.lock (16)
  • 638-694: The update to "coverage" version "7.4.3" includes new wheel files for various Python versions and platforms, each with a corresponding SHA256 hash. Ensure that this version is compatible with the project's requirements and that the hashes match those from a trusted source, such as PyPI.
  • 902-908: The update to "eth-abi" version "5.0.1" includes a wheel file and a source distribution, each with a SHA256 hash. Verify that this version is compatible with the project's requirements and confirm the hashes with a trusted source.
  • 917-919: The extras for "eth-abi" have been updated to specify dependencies for development, documentation, testing, and tools. Review these extras to ensure they align with the project's development and deployment needs.
  • 951-957: The update to "eth-hash" version "0.7.0" includes a wheel file and a source distribution, each with a SHA256 hash. Ensure this version is compatible with the project's requirements and verify the hashes with a trusted source.
  • 972-978: The update to "eth-keyfile" version "0.8.0" includes a wheel file and a source distribution, each with a SHA256 hash. Verify that this version is compatible with the project's requirements and confirm the hashes with a trusted source.
  • 1233-1361: The updates to "grpcio" and "grpcio-tools" version "1.62.0" include numerous wheel files for various Python versions and platforms, each with a SHA256 hash. Additionally, there's an update to the "grpcio-tools" package dependencies. Ensure these versions are compatible with the project's requirements, verify the hashes with a trusted source, and review the updated dependencies for "grpcio-tools".
  • 1398-1404: The update to "identify" version "2.5.35" includes a wheel file and a source distribution, each with a SHA256 hash. Verify that this version is compatible with the project's requirements and confirm the hashes with a trusted source.
  • 1788-1794: The update to "pre-commit" version "3.6.2" includes a wheel file and a source distribution, each with a SHA256 hash. Ensure this version is compatible with the project's requirements and verify the hashes with a trusted source.
  • 1806-1821: The update to "protobuf" version "4.25.3" includes numerous wheel files for various Python versions and platforms, each with a SHA256 hash. Verify that this version is compatible with the project's requirements and confirm the hashes with a trusted source.
  • 1915-1921: The update to "pytest" version "8.0.2" includes a wheel file and a source distribution, each with a SHA256 hash. Ensure this version is compatible with the project's requirements and verify the hashes with a trusted source.
  • 1985-1998: The update to "python-dotenv" version "1.0.1" includes a wheel file and a source distribution, each with a SHA256 hash, and an update to the package extras specifying a dependency for the CLI. Verify that this version is compatible with the project's requirements, confirm the hashes with a trusted source, and review the updated extras for relevance.
  • 2270-2373: The update to "rpds-py" version "0.18.0" includes numerous wheel files for various Python versions and platforms, each with a SHA256 hash. Ensure this version is compatible with the project's requirements and verify the hashes with a trusted source.
  • 2388-2400: The update to "setuptools" version "69.1.1" includes a wheel file and a source distribution, each with a SHA256 hash, and an update to the package extras specifying dependencies for documentation and testing. Verify that this version is compatible with the project's requirements, confirm the hashes with a trusted source, and review the updated extras for relevance.
  • 2448-2454: The update to "typing-extensions" version "4.10.0" includes a wheel file and a source distribution, each with a SHA256 hash. Ensure this version is compatible with the project's requirements and verify the hashes with a trusted source.
  • 2475-2481: The update to "virtualenv" version "20.25.1" includes a wheel file and a source distribution, each with a SHA256 hash. Verify that this version is compatible with the project's requirements and confirm the hashes with a trusted source.
  • 2715-2715: The metadata section has been updated with a new content-hash. This is a standard practice to ensure the integrity of the poetry.lock file after modifications.

Comment on lines +9 to +68
class ConfigurableExchangeQueryServicer(exchange_query_grpc.QueryServicer):
def __init__(self):
super().__init__()
self.exchange_params = deque()
self.subaccount_deposits_responses = deque()
self.subaccount_deposit_responses = deque()
self.exchange_balances_responses = deque()
self.aggregate_volume_responses = deque()
self.aggregate_volumes_responses = deque()
self.aggregate_market_volume_responses = deque()
self.aggregate_market_volumes_responses = deque()
self.denom_decimal_responses = deque()
self.denom_decimals_responses = deque()
self.spot_markets_responses = deque()
self.spot_market_responses = deque()
self.full_spot_markets_responses = deque()
self.full_spot_market_responses = deque()
self.spot_orderbook_responses = deque()
self.trader_spot_orders_responses = deque()
self.account_address_spot_orders_responses = deque()
self.spot_orders_by_hashes_responses = deque()
self.subaccount_orders_responses = deque()
self.trader_spot_transient_orders_responses = deque()
self.spot_mid_price_and_tob_responses = deque()
self.derivative_mid_price_and_tob_responses = deque()
self.derivative_orderbook_responses = deque()
self.trader_derivative_orders_responses = deque()
self.account_address_derivative_orders_responses = deque()
self.derivative_orders_by_hashes_responses = deque()
self.trader_derivative_transient_orders_responses = deque()
self.derivative_markets_responses = deque()
self.derivative_market_responses = deque()
self.derivative_market_address_responses = deque()
self.subaccount_trade_nonce_responses = deque()
self.positions_responses = deque()
self.subaccount_positions_responses = deque()
self.subaccount_position_in_market_responses = deque()
self.subaccount_effective_position_in_market_responses = deque()
self.perpetual_market_info_responses = deque()
self.expiry_futures_market_info_responses = deque()
self.perpetual_market_funding_responses = deque()
self.subaccount_order_metadata_responses = deque()
self.trade_reward_points_responses = deque()
self.pending_trade_reward_points_responses = deque()
self.trade_reward_campaign_responses = deque()
self.fee_discount_account_info_responses = deque()
self.fee_discount_schedule_responses = deque()
self.balance_mismatches_responses = deque()
self.balance_with_balance_holds_responses = deque()
self.fee_discount_tier_statistics_responses = deque()
self.mito_vault_infos_responses = deque()
self.market_id_from_vault_responses = deque()
self.historical_trade_records_responses = deque()
self.is_opted_out_of_rewards_responses = deque()
self.opted_out_of_rewards_accounts_responses = deque()
self.market_volatility_responses = deque()
self.binary_options_markets_responses = deque()
self.trader_derivative_conditional_orders_responses = deque()
self.market_atomic_execution_fee_multiplier_responses = deque()

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The ConfigurableExchangeQueryServicer class is well-structured for mocking exchange query services. Using deque for mock responses is a good choice for FIFO behavior, which is typical in mock scenarios. However, ensure that there is a mechanism in place to handle cases where a pop() operation is called on an empty deque, as this will raise an IndexError. Consider adding checks or default responses to prevent potential runtime errors during testing.

Comment on lines +69 to +331
):
return self.perpetual_market_info_responses.pop()

async def ExpiryFuturesMarketInfo(
self, request: exchange_query_pb.QueryExpiryFuturesMarketInfoRequest, context=None, metadata=None
):
return self.expiry_futures_market_info_responses.pop()

async def PerpetualMarketFunding(
self, request: exchange_query_pb.QueryPerpetualMarketFundingRequest, context=None, metadata=None
):
return self.perpetual_market_funding_responses.pop()

async def SubaccountOrderMetadata(
self, request: exchange_query_pb.QuerySubaccountOrderMetadataRequest, context=None, metadata=None
):
return self.subaccount_order_metadata_responses.pop()

async def TradeRewardPoints(
self, request: exchange_query_pb.QueryTradeRewardPointsRequest, context=None, metadata=None
):
return self.trade_reward_points_responses.pop()

async def PendingTradeRewardPoints(
self, request: exchange_query_pb.QueryTradeRewardPointsRequest, context=None, metadata=None
):
return self.pending_trade_reward_points_responses.pop()

async def TradeRewardCampaign(
self, request: exchange_query_pb.QueryTradeRewardCampaignRequest, context=None, metadata=None
):
return self.trade_reward_campaign_responses.pop()

async def FeeDiscountAccountInfo(
self, request: exchange_query_pb.QueryFeeDiscountAccountInfoRequest, context=None, metadata=None
):
return self.fee_discount_account_info_responses.pop()

async def FeeDiscountSchedule(
self, request: exchange_query_pb.QueryFeeDiscountScheduleRequest, context=None, metadata=None
):
return self.fee_discount_schedule_responses.pop()

async def BalanceMismatches(
self, request: exchange_query_pb.QueryBalanceMismatchesRequest, context=None, metadata=None
):
return self.balance_mismatches_responses.pop()

async def BalanceWithBalanceHolds(
self, request: exchange_query_pb.QueryBalanceWithBalanceHoldsRequest, context=None, metadata=None
):
return self.balance_with_balance_holds_responses.pop()

async def FeeDiscountTierStatistics(
self, request: exchange_query_pb.QueryFeeDiscountTierStatisticsRequest, context=None, metadata=None
):
return self.fee_discount_tier_statistics_responses.pop()

async def MitoVaultInfos(self, request: exchange_query_pb.MitoVaultInfosRequest, context=None, metadata=None):
return self.mito_vault_infos_responses.pop()

async def QueryMarketIDFromVault(
self, request: exchange_query_pb.QueryMarketIDFromVaultRequest, context=None, metadata=None
):
return self.market_id_from_vault_responses.pop()

async def HistoricalTradeRecords(
self, request: exchange_query_pb.QueryHistoricalTradeRecordsRequest, context=None, metadata=None
):
return self.historical_trade_records_responses.pop()

async def IsOptedOutOfRewards(
self, request: exchange_query_pb.QueryIsOptedOutOfRewardsRequest, context=None, metadata=None
):
return self.is_opted_out_of_rewards_responses.pop()

async def OptedOutOfRewardsAccounts(
self, request: exchange_query_pb.QueryOptedOutOfRewardsAccountsRequest, context=None, metadata=None
):
return self.opted_out_of_rewards_accounts_responses.pop()

async def MarketVolatility(
self, request: exchange_query_pb.QueryMarketVolatilityRequest, context=None, metadata=None
):
return self.market_volatility_responses.pop()

async def BinaryOptionsMarkets(
self, request: exchange_query_pb.QueryBinaryMarketsRequest, context=None, metadata=None
):
return self.binary_options_markets_responses.pop()

async def TraderDerivativeConditionalOrders(
self, request: exchange_query_pb.QueryTraderDerivativeConditionalOrdersRequest, context=None, metadata=None
):
return self.trader_derivative_conditional_orders_responses.pop()

async def MarketAtomicExecutionFeeMultiplier(
self, request: exchange_query_pb.QueryMarketAtomicExecutionFeeMultiplierRequest, context=None, metadata=None
):
return self.market_atomic_execution_fee_multiplier_responses.pop()
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Each async method in ConfigurableExchangeQueryServicer correctly pops a response from its respective deque. This setup is crucial for testing different scenarios by preloading the deque with expected responses. However, it's important to ensure that all methods have corresponding test cases that cover various scenarios, including empty responses and error cases. This will help in validating the robustness of the application's error handling and response parsing logic.

Would you like me to help generate some test cases covering various scenarios for these methods?

assert len(deprecation_warnings) == 1
assert str(deprecation_warnings[0].message) == "This method is deprecated. Use msg_withdraw instead"

def teste_order_data_deprecation_warning(self):
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There's a typo in the method name teste_order_data_deprecation_warning. It should be test_order_data_deprecation_warning.

-    def teste_order_data_deprecation_warning(self):
+    def test_order_data_deprecation_warning(self):

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Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation.

Suggested change
def teste_order_data_deprecation_warning(self):
def test_order_data_deprecation_warning(self):

Comment on lines +13 to +578
return response

async def fetch_balance_with_balance_holds(self) -> Dict[str, Any]:
request = exchange_query_pb.QueryBalanceWithBalanceHoldsRequest()
response = await self._execute_call(call=self._stub.BalanceWithBalanceHolds, request=request)

return response

async def fetch_fee_discount_tier_statistics(self) -> Dict[str, Any]:
request = exchange_query_pb.QueryFeeDiscountTierStatisticsRequest()
response = await self._execute_call(call=self._stub.FeeDiscountTierStatistics, request=request)

return response

async def fetch_mito_vault_infos(self) -> Dict[str, Any]:
request = exchange_query_pb.MitoVaultInfosRequest()
response = await self._execute_call(call=self._stub.MitoVaultInfos, request=request)

return response

async def fetch_market_id_from_vault(self, vault_address: str) -> Dict[str, Any]:
request = exchange_query_pb.QueryMarketIDFromVaultRequest(vault_address=vault_address)
response = await self._execute_call(call=self._stub.QueryMarketIDFromVault, request=request)

return response

async def fetch_historical_trade_records(self, market_id: str) -> Dict[str, Any]:
request = exchange_query_pb.QueryHistoricalTradeRecordsRequest(market_id=market_id)
response = await self._execute_call(call=self._stub.HistoricalTradeRecords, request=request)

return response

async def fetch_is_opted_out_of_rewards(self, account: str) -> Dict[str, Any]:
request = exchange_query_pb.QueryIsOptedOutOfRewardsRequest(account=account)
response = await self._execute_call(call=self._stub.IsOptedOutOfRewards, request=request)

return response

async def fetch_opted_out_of_rewards_accounts(self) -> Dict[str, Any]:
request = exchange_query_pb.QueryOptedOutOfRewardsAccountsRequest()
response = await self._execute_call(call=self._stub.OptedOutOfRewardsAccounts, request=request)

return response

async def fetch_market_volatility(
self,
market_id: str,
trade_grouping_sec: Optional[int] = None,
max_age: Optional[int] = None,
include_raw_history: Optional[bool] = None,
include_metadata: Optional[bool] = None,
) -> Dict[str, Any]:
trade_history_options = exchange_query_pb.TradeHistoryOptions()
if trade_grouping_sec is not None:
trade_history_options.trade_grouping_sec = trade_grouping_sec
if max_age is not None:
trade_history_options.max_age = max_age
if include_raw_history is not None:
trade_history_options.include_raw_history = include_raw_history
if include_metadata is not None:
trade_history_options.include_metadata = include_metadata
request = exchange_query_pb.QueryMarketVolatilityRequest(
market_id=market_id, trade_history_options=trade_history_options
)
response = await self._execute_call(call=self._stub.MarketVolatility, request=request)

return response

async def fetch_binary_options_markets(self, status: Optional[str] = None) -> Dict[str, Any]:
request = exchange_query_pb.QueryBinaryMarketsRequest(status=status)
response = await self._execute_call(call=self._stub.BinaryOptionsMarkets, request=request)

return response

async def fetch_trader_derivative_conditional_orders(
self,
subaccount_id: Optional[str] = None,
market_id: Optional[str] = None,
) -> Dict[str, Any]:
request = exchange_query_pb.QueryTraderDerivativeConditionalOrdersRequest(
subaccount_id=subaccount_id,
market_id=market_id,
)
response = await self._execute_call(call=self._stub.TraderDerivativeConditionalOrders, request=request)

return response

async def fetch_market_atomic_execution_fee_multiplier(
self,
market_id: str,
) -> Dict[str, Any]:
request = exchange_query_pb.QueryMarketAtomicExecutionFeeMultiplierRequest(
market_id=market_id,
)
response = await self._execute_call(call=self._stub.MarketAtomicExecutionFeeMultiplier, request=request)

return response

async def _execute_call(self, call: Callable, request) -> Dict[str, Any]:
return await self._assistant.execute_call(call=call, request=request)
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Ensure comprehensive test coverage for all methods in the ChainGrpcExchangeApi class. Given the complexity of interacting with a blockchain protocol, it's crucial to validate the correctness and resilience of these methods under various conditions.

Would you like assistance in generating tests or enhancing existing ones to cover these functionalities?

import asyncio
import os

import dotenv
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The import statement for dotenv is correct, but it's more conventional to use from dotenv import load_dotenv and then simply call load_dotenv() without the module prefix.

- import dotenv
+ from dotenv import load_dotenv

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Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation.

Suggested change
import dotenv
from dotenv import load_dotenv

Comment on lines +36 to +51
message = composer.msg_instant_binary_options_market_launch(
sender=address.to_acc_bech32(),
ticker="UFC-KHABIB-TKO-05/30/2023",
oracle_symbol="UFC-KHABIB-TKO-05/30/2023",
oracle_provider="UFC",
oracle_type="Provider",
oracle_scale_factor=6,
maker_fee_rate=0.0005, # 0.05%
taker_fee_rate=0.0010, # 0.10%
expiration_timestamp=1680730982,
settlement_timestamp=1690730982,
admin=address.to_acc_bech32(),
quote_denom="peggy0xdAC17F958D2ee523a2206206994597C13D831ec7",
min_price_tick_size=0.01,
min_quantity_tick_size=0.01,
)
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The parameters for launching the binary options market, such as ticker, oracle_symbol, oracle_provider, oracle_type, maker_fee_rate, taker_fee_rate, expiration_timestamp, settlement_timestamp, quote_denom, min_price_tick_size, and min_quantity_tick_size are hardcoded. While this might be suitable for example purposes, consider fetching these values from an environment variable or a configuration file to enhance flexibility and usability in real-world scenarios.

Comment on lines +37 to +38
if __name__ == "__main__":
asyncio.get_event_loop().run_until_complete(main())
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Recommend updating the method for running the async main function to asyncio.run(main()) for Python 3.7 and newer, which simplifies the entry point and ensures proper event loop management.

-    asyncio.get_event_loop().run_until_complete(main())
+    asyncio.run(main())

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Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation.

Suggested change
if __name__ == "__main__":
asyncio.get_event_loop().run_until_complete(main())
if __name__ == "__main__":
asyncio.run(main())

Comment on lines +12 to +13
dotenv.load_dotenv()
configured_private_key = os.getenv("INJECTIVE_PRIVATE_KEY")
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Include error handling for the scenario where the INJECTIVE_PRIVATE_KEY environment variable is not set, to prevent runtime errors and improve the script's robustness, as done in previous files.

-    configured_private_key = os.getenv("INJECTIVE_PRIVATE_KEY")
+    configured_private_key = os.getenv("INJECTIVE_PRIVATE_KEY", "")
+    if not configured_private_key:
+        raise ValueError("INJECTIVE_PRIVATE_KEY environment variable is not set.")

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‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation.

Suggested change
dotenv.load_dotenv()
configured_private_key = os.getenv("INJECTIVE_PRIVATE_KEY")
dotenv.load_dotenv()
configured_private_key = os.getenv("INJECTIVE_PRIVATE_KEY", "")
if not configured_private_key:
raise ValueError("INJECTIVE_PRIVATE_KEY environment variable is not set.")

Comment on lines +37 to +38
if __name__ == "__main__":
asyncio.get_event_loop().run_until_complete(main())
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Recommend updating the method for running the async main function to asyncio.run(main()) for Python 3.7 and newer, which simplifies the entry point and ensures proper event loop management.

-    asyncio.get_event_loop().run_until_complete(main())
+    asyncio.run(main())

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‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation.

Suggested change
if __name__ == "__main__":
asyncio.get_event_loop().run_until_complete(main())
if __name__ == "__main__":
asyncio.run(main())

Comment on lines +13 to +14
dotenv.load_dotenv()
private_key_in_hexa = os.getenv("INJECTIVE_PRIVATE_KEY")
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Ensure that there's error handling for the case where the INJECTIVE_PRIVATE_KEY environment variable might not be set. This is crucial for avoiding runtime errors and improving the script's robustness.

-    private_key_in_hexa = os.getenv("INJECTIVE_PRIVATE_KEY")
+    private_key_in_hexa = os.getenv("INJECTIVE_PRIVATE_KEY", "")
+    if not private_key_in_hexa:
+        raise ValueError("INJECTIVE_PRIVATE_KEY environment variable is not set.")

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‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation.

Suggested change
dotenv.load_dotenv()
private_key_in_hexa = os.getenv("INJECTIVE_PRIVATE_KEY")
dotenv.load_dotenv()
private_key_in_hexa = os.getenv("INJECTIVE_PRIVATE_KEY", "")
if not private_key_in_hexa:
raise ValueError("INJECTIVE_PRIVATE_KEY environment variable is not set.")

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