Commit Graph

2427 Commits

Author SHA1 Message Date
ccurme
42de5168b1 langchain: deprecate LLMChain, RetrievalQA, and ConversationalRetrievalChain (#20751) 2024-04-23 15:55:34 -04:00
Eugene Yurtsev
1c89e45c14 langchain[major]: breaks some chains to remove hidden defaults (#20759)
Breaks some chains in langchain to remove hidden chat model / llm instantiation.
2024-04-23 11:11:40 -04:00
Eugene Yurtsev
ad6b5f84e5 community[patch],core[minor]: Move in memory cache implementation to core (#20753)
This PR moves the InMemoryCache implementation from community to core.
2024-04-23 11:10:11 -04:00
Eugene Yurtsev
645b1e142e core[minor],langchain[patch],community[patch]: Move InMemory and File implementations of Chat History to core (#20752)
This PR moves the implementations for chat history to core. So it's
easier to determine which dependencies need to be broken / add
deprecation warnings
2024-04-23 10:22:11 -04:00
Eugene Yurtsev
936c6cc74a langchain[patch]: Add missing deprecation for openai adapters (#20668)
Add missing deprecation for openai adapters
2024-04-22 14:05:55 -04:00
ccurme
c010ec8b71 patch: deprecate (a)get_relevant_documents (#20477)
- `.get_relevant_documents(query)` -> `.invoke(query)`
- `.get_relevant_documents(query=query)` -> `.invoke(query)`
- `.get_relevant_documents(query, callbacks=callbacks)` ->
`.invoke(query, config={"callbacks": callbacks})`
- `.get_relevant_documents(query, **kwargs)` -> `.invoke(query,
**kwargs)`

---------

Co-authored-by: Erick Friis <erick@langchain.dev>
2024-04-22 11:14:53 -04:00
Bagatur
d0cee65cdc langchain[patch]: langchain-pinecone self query support (#20702) 2024-04-21 15:42:39 -07:00
Leonid Ganeline
06d18c106d langchain[patch]: example_selector import fix (#20676)
Cleaned up updated imports
2024-04-19 21:42:18 -04:00
Leonid Ganeline
d6470aab60 langchain: dosctore import fix (#20678)
Cleaned up imports
2024-04-19 21:41:36 -04:00
Souls-R
36084e7500 docs: fix variable name typo in example code (#20658)
This pull request corrects a mistake in the variable name within the
example code. The variable doc_schema has been changed to dog_schema to
fix the error.
2024-04-19 14:08:25 +00:00
Sivaudha
baedc3ec0a langchain[minor]: Databricks vector search self query integration (#20627)
- Enable self querying feature for databricks vector search

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
2024-04-19 03:44:38 +00:00
Leonid Ganeline
95dc90609e experimental[patch]: prompts import fix (#20534)
Replaced `from langchain.prompts` with `from langchain_core.prompts`
where it is appropriate.
Most of the changes go to `langchain_experimental`
Similar to #20348
2024-04-18 16:09:11 -04:00
aditya thomas
cea379e7c7 community, core[callbacks]: move FileCallbackHandler from community to core (#20495)
**Description:** Move `FileCallbackHandler` from community to core
**Issue:** #20493 
**Dependencies:** None

(imo) `FileCallbackHandler` is a built-in LangChain callback handler
like `StdOutCallbackHandler` and should properly be in in core.
2024-04-17 22:29:30 -04:00
pjb157
479be3cc91 community[minor]: Unify Titan Takeoff Integrations and Adding Embedding Support (#18775)
**Community: Unify Titan Takeoff Integrations and Adding Embedding
Support**

 **Description:** 
Titan Takeoff no longer reflects this either of the integrations in the
community folder. The two integrations (TitanTakeoffPro and
TitanTakeoff) where causing confusion with clients, so have moved code
into one place and created an alias for backwards compatibility. Added
Takeoff Client python package to do the bulk of the work with the
requests, this is because this package is actively updated with new
versions of Takeoff. So this integration will be far more robust and
will not degrade as badly over time.

**Issue:**
Fixes bugs in the old Titan integrations and unified the code with added
unit test converge to avoid future problems.

**Dependencies:**
Added optional dependency takeoff-client, all imports still work without
dependency including the Titan Takeoff classes but just will fail on
initialisation if not pip installed takeoff-client

**Twitter**
@MeryemArik9

Thanks all :)

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
2024-04-17 01:43:35 +00:00
Prashanth Rao
295b9b704b community[patch]: Improve Kuzu Cypher generation prompt (#20481)
- [x] **PR title**: "community: improve kuzu cypher generation prompt"

- [x] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** Improves the Kùzu Cypher generation prompt to be more
robust to open source LLM outputs
    - **Issue:** N/A
    - **Dependencies:** N/A
    - **Twitter handle:** @kuzudb

- [x] **Add tests and docs**: If you're adding a new integration, please
include
No new tests (non-breaking. change)

- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
2024-04-16 18:01:36 -07:00
ccurme
22da9f5f3f update scheduled tests (#20526)
repurpose scheduled tests to test over provider packages
2024-04-16 16:49:46 -04:00
Leonid Ganeline
45d045b2c5 core[minor], langchain[patch]: tools dependencies refactoring (#18759)
The `langchain.tools`
[namespace](https://api.python.langchain.com/en/latest/langchain_api_reference.html#module-langchain.tools)
can be completely eliminated by moving one class and 3 functions into
`core`. It makes sense since the class and functions are very core.
2024-04-16 14:15:09 -04:00
ccurme
38faa74c23 community[patch]: update use of deprecated llm methods (#20393)
.predict and .predict_messages for BaseLanguageModel and BaseChatModel
2024-04-12 17:28:23 -04:00
Leonid Ganeline
e512d3c6a6 langchain: callbacks imports fix (#20348)
Replaced all `from langchain.callbacks` into `from
langchain_core.callbacks` .
Changes in the `langchain` and `langchain_experimental`

---------

Co-authored-by: Erick Friis <erick@langchain.dev>
2024-04-12 20:13:14 +00:00
Eugene Yurtsev
6470b30173 langchain[patch]: Add deprecation warning to extraction chains (#20224)
Add deprecation warnings to extraction chains
2024-04-12 10:24:32 -04:00
Eugene Yurtsev
b65a1d4cfd langchain[patch]: Add another unit test for indexing code (#20387)
Add another unit test for indexing
2024-04-12 10:19:18 -04:00
Bagatur
6608089030 langchain[patch]: Release 0.1.16 (#20335) 2024-04-11 09:28:37 -07:00
Bagatur
e936fba428 langchain[patch]: agents check prompt partial vars (#20303) 2024-04-11 03:55:09 -07:00
Yuki Watanabe
eef19954f3 core[patch]: fix duplicated kwargs in _load_sql_databse_chain (#19908)
`kwargs` is specified twice in [this
line](3218463f6a/libs/langchain/langchain/chains/loading.py (L386)),
causing runtime error when passing any keyword arguments.
2024-04-10 12:20:28 -07:00
Leonid Ganeline
4cb5f4c353 community[patch]: import flattening fix (#20110)
This PR should make it easier for linters to do type checking and for IDEs to jump to definition of code.

See #20050 as a template for this PR.
- As a byproduct: Added 3 missed `test_imports`.
- Added missed `SolarChat` in to __init___.py Added it into test_import
ut.
- Added `# type: ignore` to fix linting. It is not clear, why linting
errors appear after ^ changes.

---------

Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
2024-04-10 13:01:19 -04:00
ccurme
21c1ce0bc1 update agents to use tool call messages (#20074)
```python
from langchain.agents import AgentExecutor, create_tool_calling_agent, tool
from langchain_anthropic import ChatAnthropic
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder

prompt = ChatPromptTemplate.from_messages(
    [
        ("system", "You are a helpful assistant"),
        MessagesPlaceholder("chat_history", optional=True),
        ("human", "{input}"),
        MessagesPlaceholder("agent_scratchpad"),
    ]
)
model = ChatAnthropic(model="claude-3-opus-20240229")

@tool
def magic_function(input: int) -> int:
    """Applies a magic function to an input."""
    return input + 2

tools = [magic_function]

agent = create_tool_calling_agent(model, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)

agent_executor.invoke({"input": "what is the value of magic_function(3)?"})
```
```
> Entering new AgentExecutor chain...

Invoking: `magic_function` with `{'input': 3}`
responded: [{'text': '<thinking>\nThe user has asked for the value of magic_function applied to the input 3. Looking at the available tools, magic_function is the relevant one to use here, as it takes an integer input and returns an integer output.\n\nThe magic_function has one required parameter:\n- input (integer)\n\nThe user has directly provided the value 3 for the input parameter. Since the required parameter is present, we can proceed with calling the function.\n</thinking>', 'type': 'text'}, {'id': 'toolu_01HsTheJPA5mcipuFDBbJ1CW', 'input': {'input': 3}, 'name': 'magic_function', 'type': 'tool_use'}]

5
Therefore, the value of magic_function(3) is 5.

> Finished chain.
{'input': 'what is the value of magic_function(3)?',
 'output': 'Therefore, the value of magic_function(3) is 5.'}
```

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
2024-04-10 11:54:51 -04:00
Bagatur
9514bc4d67 core[minor], ...: add tool calls message (#18947)
core[minor], langchain[patch], openai[minor], anthropic[minor], fireworks[minor], groq[minor], mistralai[minor]

```python
class ToolCall(TypedDict):
    name: str
    args: Dict[str, Any]
    id: Optional[str]

class InvalidToolCall(TypedDict):
    name: Optional[str]
    args: Optional[str]
    id: Optional[str]
    error: Optional[str]

class ToolCallChunk(TypedDict):
    name: Optional[str]
    args: Optional[str]
    id: Optional[str]
    index: Optional[int]


class AIMessage(BaseMessage):
    ...
    tool_calls: List[ToolCall] = []
    invalid_tool_calls: List[InvalidToolCall] = []
    ...


class AIMessageChunk(AIMessage, BaseMessageChunk):
    ...
    tool_call_chunks: Optional[List[ToolCallChunk]] = None
    ...
```
Important considerations:
- Parsing logic occurs within different providers;
- ~Changing output type is a breaking change for anyone doing explicit
type checking;~
- ~Langsmith rendering will need to be updated:
https://github.com/langchain-ai/langchainplus/pull/3561~
- ~Langserve will need to be updated~
- Adding chunks:
- ~AIMessage + ToolCallsMessage = ToolCallsMessage if either has
non-null .tool_calls.~
- Tool call chunks are appended, merging when having equal values of
`index`.
  - additional_kwargs accumulate the normal way.
- During streaming:
- ~Messages can change types (e.g., from AIMessageChunk to
AIToolCallsMessageChunk)~
- Output parsers parse additional_kwargs (during .invoke they read off
tool calls).

Packages outside of `partners/`:
- https://github.com/langchain-ai/langchain-cohere/pull/7
- https://github.com/langchain-ai/langchain-google/pull/123/files

---------

Co-authored-by: Chester Curme <chester.curme@gmail.com>
2024-04-09 18:41:42 -05:00
Bagatur
e5913c8758 langchain[patch]: Release 0.1.15 (#20237) 2024-04-09 21:50:32 +00:00
Eugene Yurtsev
fe35e13083 langchain[patch]: Update unit test (#20228)
This unit test fails likely validation by the openai client.

Newer openai library seems to be doing more validation so the existing
test fails since http_client needs to be of httpx instance
2024-04-09 16:44:23 -04:00
Casper da Costa-Luis
b972f394c8 langchain[patch]: make BooleanOutputParser check words not substrings (#20064)
- **Description**: fixes BooleanOutputParser detecting sub-words ("NOW
this is likely (YES)" -> `True`, not `AmbiguousError`)
- **Issue(s)**: fixes #11408 (follow-up to #17810)
- **Dependencies**: None
- **GitHub handle**: @casperdcl

<!-- if unreviewd after a few days, @-mention one of baskaryan, efriis,
eyurtsev, hwchase17 -->

- [x] **Add tests and docs**: If you're adding a new integration, please
include
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in
`docs/docs/integrations` directory.
- [ ] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/

---------

Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
2024-04-09 20:43:31 +00:00
jeff kit
ac42e96e4c community[patch], langchain[minor]: Enhance Tencent Cloud VectorDB, langchain: make Tencent Cloud VectorDB self query retrieve compatible (#19651)
- make Tencent Cloud VectorDB support metadata filtering.
- implement delete function for Tencent Cloud VectorDB.
- support both Langchain Embedding model and Tencent Cloud VDB embedding
model.
- Tencent Cloud VectorDB support filter search keyword, compatible with
langchain filtering syntax.
- add Tencent Cloud VectorDB TranslationVisitor, now work with self
query retriever.
- more documentations.

---------

Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
2024-04-09 16:50:48 +00:00
Piyush Jain
cd7abc495a community[minor]: add neptune analytics graph (#20047)
Replacement for PR
[#19772](https://github.com/langchain-ai/langchain/pull/19772).

---------

Co-authored-by: Dave Bechberger <dbechbe@amazon.com>
Co-authored-by: bechbd <bechbd@users.noreply.github.com>
2024-04-09 09:20:59 -05:00
Bagatur
5ae0e687b3 docs: use standard openai params (#20160)
Part of #20085
2024-04-08 10:56:53 -05:00
Marlene
2f03bc397e Community: Updating Azure Retriever and Docs to be Azure AI Search instead of Azure Cognitive Search (#19925)
Last year Microsoft [changed the
name](https://learn.microsoft.com/en-us/azure/search/search-what-is-azure-search)
of Azure Cognitive Search to Azure AI Search. This PR updates the
Langchain Azure Retriever API and it's associated docs to reflect this
change. It may be confusing for users to see the name Cognitive here and
AI in the Microsoft documentation which is why this is needed. I've also
added a more detailed example to the Azure retriever doc page.

There are more places that need a similar update but I'm breaking it up
so the PRs are not too big 😄 Fixing my errors from the previous PR.

Twitter: @marlene_zw

Two new tests added to test backward compatibility in
`libs/community/tests/integration_tests/retrievers/test_azure_cognitive_search.py`

---------

Co-authored-by: Chester Curme <chester.curme@gmail.com>
2024-04-08 11:12:41 -04:00
Christophe Bornet
7e5c1905b1 core[minor]: Add async aformat_document method (#20037) 2024-04-05 10:29:53 -04:00
Chris Papademetrious
a954dedb77 langchain[minor]: enhance LocalFileStore to allow directory/file permissions to be specified (#18857)
**Description:**
The `LocalFileStore` class can be used to create an on-disk
`CacheBackedEmbeddings` cache. However, the default `umask` settings
gives file/directory write permissions only to the original user. Once
the cache directory is created by the first user, other users cannot
write their own cache entries into the directory.

To make the cache usable by multiple users, this pull request updates
the `LocalFileStore` constructor to allow the permissions for newly
created directories and files to be specified. The specified permissions
override the default `umask` values.

For example, when configured as follows:

```python
file_store = LocalFileStore(temp_dir, chmod_dir=0o770, chmod_file=0o660)
```

then "user" and "group" (but not "other") have permissions to access the
store, which means:

* Anyone in our group could contribute embeddings to the cache.
* If we implement cache cleanup/eviction in the future, anyone in our
group could perform the cleanup.

The default values for the `chmod_dir` and `chmod_file` parameters is
`None`, which retains the original behavior of using the default `umask`
settings.

**Issue:**
Implements enhancement #18075.

**Testing:**
I updated the `LocalFileStore` unit tests to test the permissions.

---------

Signed-off-by: chrispy <chrispy@synopsys.com>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
2024-04-04 16:40:16 +00:00
Jacob Lee
605c3f23e1 docs: reorg and visual refresh (#19765)
- put use cases in main sidebar
- move modules to own sidebar, rename components
- cleanup lcel section
- cleanup guides
- update font, cell highlighting

---------

Co-authored-by: Chester Curme <chester.curme@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-04-04 00:58:36 -07:00
Erick Friis
f0d5b59962 core[patch]: remove requests (#19891)
Removes required usage of `requests` from `langchain-core`, all of which
has been deprecated.

- removes Tracer V1 implementations
- removes old `try_load_from_hub` github-based hub implementations

Removal done in a way where imports will still succeed, and usage will
fail with a `RuntimeError`.
2024-04-02 20:28:10 +00:00
Max Jakob
22dbcc9441 langchain[patch]: fix ElasticsearchStore reference for self query (#19907)
Initializing self query with an ElasticsearchStore from the partners
packages failed previously, see
https://github.com/langchain-ai/langchain/discussions/18976.
2024-04-02 08:39:12 -07:00
Nuno Campos
2ae6dcdf01 core: Assign missing message ids in BaseChatModel (#19863)
- This ensures ids are stable across streamed chunks
- Multiple messages in batch call get separate ids
- Also fix ids being dropped when combining message chunks

Thank you for contributing to LangChain!

- [ ] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core,
experimental, etc. is being modified. Use "docs: ..." for purely docs
changes, "templates: ..." for template changes, "infra: ..." for CI
changes.
  - Example: "community: add foobar LLM"


- [ ] **PR message**: ***Delete this entire checklist*** and replace
with
    - **Description:** a description of the change
    - **Issue:** the issue # it fixes, if applicable
    - **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!


- [ ] **Add tests and docs**: If you're adding a new integration, please
include
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in
`docs/docs/integrations` directory.


- [ ] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/

Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.

If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
2024-04-02 01:18:36 +00:00
Bagatur
c4eb841c37 langchain[patch]: Release 0.1.14 (#19839) 2024-03-31 21:44:01 -07:00
Guangdong Liu
b6ebddbacc langchain[patch]: Upgrade openai's sdk and solve some interface adaptation problems. #19548 (#19785)
- #19548
- @baskaryan @eyurtsev PTAL

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-03-31 21:35:38 +00:00
Kenneth Choe
f98d7f7494 langchain[minor], community[minor]: add CrossEncoderReranker with HuggingFaceCrossEncoder and SagemakerEndpointCrossEncoder (#13687)
- **Description:** Support reranking based on cross encoder models
available from HuggingFace.
      - Added `CrossEncoder` schema
- Implemented `HuggingFaceCrossEncoder` and
`SagemakerEndpointCrossEncoder`
- Implemented `CrossEncoderReranker` that performs similar functionality
to `CohereRerank`
- Added `cross-encoder-reranker.ipynb` to demonstrate how to use it.
Please let me know if anything else needs to be done to make it visible
on the table-of-contents navigation bar on the left, or on the card list
on [retrievers documentation
page](https://python.langchain.com/docs/integrations/retrievers).
  - **Issue:** N/A
  - **Dependencies:** None other than the existing ones.

---------

Co-authored-by: Kenny Choe <kchoe@amazon.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-03-31 20:51:31 +00:00
DrKroll
c4da8d0813 langchain[patch]: load ReadFileTool (#14301)
---------

Co-authored-by: Dr. Simon Kroll <krolls@fida.de>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>
Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-03-30 00:46:24 +00:00
Ahmed Moubtahij
f5d4ce840f langchain[patch]: Simplify ensemble retriever (#14427)
- **Description:** code simplification to improve readability and remove
unnecessary memory allocations.
  - **Tag maintainer**: @baskaryan, @eyurtsev, @hwchase17.

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-03-29 16:49:49 -07:00
Guangdong Liu
cd55d587c2 langchain[patch]: Upgrade openai's sdk and solve some interface adaptation problems. (#19548)
- **Issue:** close #19534
2024-03-29 01:25:17 -07:00
Sachin Paryani
25c9f3d1d1 community[patch]: Support Streaming in Azure Machine Learning (#18246)
- [x] **PR title**: "community: Support streaming in Azure ML and few
naming changes"

- [x] **PR message**:
- **Description:** Added support for streaming for azureml_endpoint.
Also, renamed and AzureMLEndpointApiType.realtime to
AzureMLEndpointApiType.dedicated. Also, added new classes
CustomOpenAIChatContentFormatter and CustomOpenAIContentFormatter and
updated the classes LlamaChatContentFormatter and LlamaContentFormatter
to now show a deprecated warning message when instantiated.

---------

Co-authored-by: Sachin Paryani <saparan@microsoft.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-03-28 23:38:20 +00:00
xiaohuanshu
ecb11a4a32 langchain[patch]: fix BaseChatMemory get output data error with extra key (#18117)
**Description:** At times, BaseChatMemory._get_input_output may acquire
some extra keys such as 'intermediate_steps' (agent_executor with
return_intermediate_steps set to True) and 'messages'
(agent_executor.iter with memory). In these instances, _get_input_output
can raise an error due to the presence of multiple keys. The 'output'
field should be used as the default field in these cases.
**Issue:** #16791
2024-03-28 16:38:08 -07:00
Davide Menini
824dbc49ee langchain[patch]: add template_tool_response arg to create_json_chat (#19696)
In this small PR I added the `template_tool_response` arg to the
`create_json_chat` function, so that users can customize this prompt in
case of need.
Thanks for your reviews!

---------

Co-authored-by: taamedag <Davide.Menini@swisscom.com>
2024-03-28 13:59:54 -07:00
Nilanjan De
239dd7c0c0 langchain[patch]: Use map() and avoid "ValueError: max() arg is an empty sequence" in MergerRetriever (#18679)
- **Issue:** When passing an empty list to MergerRetriever it fails with
error: ValueError: max() arg is an empty sequence

- **Description:** We have a use case where we dynamically select
retrievers and use MergerRetriever for merging the output of the
retrievers. We faced this issue when the retriever_docs list is empty.
Adding a default 0 for cases when retriever_docs is an empty list to
avoid "ValueError: max() arg is an empty sequence". Also, changed to use
map() which is more than twice as fast compared to the current
implementation.
```
import timeit
# Sample retriever_docs with varying lengths of sublists
retriever_docs = [[i for i in range(j)] for j in range(1, 1000)]
# First code snippet
code1 = '''
max_docs = max(len(docs) for docs in retriever_docs)
'''
# Second code snippet
code2 = '''
max_docs = max(map(len, retriever_docs), default=0)
'''
# Benchmarking
time1 = timeit.timeit(stmt=code1, globals=globals(), number=10000)
time2 = timeit.timeit(stmt=code2, globals=globals(), number=10000)
# Output
print(f"Execution time for code snippet 1: {time1} seconds")
print(f"Execution time for code snippet 2: {time2} seconds")
```

- **Dependencies:** none
2024-03-27 23:52:57 -07:00