├── .gitignore ├── .pre-commit-config.yaml ├── Dockerfile ├── LICENSE ├── README.md ├── app.py ├── data_guide ├── 1.png ├── 2.png ├── 3.png ├── 4.png ├── 5.png ├── 6.png ├── 7.png └── README.md ├── helpers.py ├── media ├── app │ ├── all.png │ ├── everything.png │ └── wordcloud.png └── linkedin.png ├── poetry.lock ├── pyproject.toml └── requirements.txt /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | pip-wheel-metadata/ 24 | share/python-wheels/ 25 | *.egg-info/ 26 | .installed.cfg 27 | *.egg 28 | MANIFEST 29 | 30 | # PyInstaller 31 | # Usually these files are written by a python script from a template 32 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 33 | *.manifest 34 | *.spec 35 | 36 | # Installer logs 37 | pip-log.txt 38 | pip-delete-this-directory.txt 39 | 40 | # Unit test / coverage reports 41 | htmlcov/ 42 | .tox/ 43 | .nox/ 44 | .coverage 45 | .coverage.* 46 | .cache 47 | nosetests.xml 48 | coverage.xml 49 | *.cover 50 | *.py,cover 51 | .hypothesis/ 52 | .pytest_cache/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | target/ 76 | 77 | # Jupyter Notebook 78 | .ipynb_checkpoints 79 | 80 | # IPython 81 | profile_default/ 82 | ipython_config.py 83 | 84 | # pyenv 85 | .python-version 86 | 87 | # pipenv 88 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 89 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 90 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 91 | # install all needed dependencies. 92 | #Pipfile.lock 93 | 94 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow 95 | __pypackages__/ 96 | 97 | # Celery stuff 98 | celerybeat-schedule 99 | celerybeat.pid 100 | 101 | # SageMath parsed files 102 | *.sage.py 103 | 104 | # Environments 105 | .env 106 | .venv 107 | env/ 108 | venv/ 109 | ENV/ 110 | env.bak/ 111 | venv.bak/ 112 | 113 | # Spyder project settings 114 | .spyderproject 115 | .spyproject 116 | 117 | # Rope project settings 118 | .ropeproject 119 | 120 | # mkdocs documentation 121 | /site 122 | 123 | # mypy 124 | .mypy_cache/ 125 | .dmypy.json 126 | dmypy.json 127 | 128 | # Pyre type checker 129 | .pyre/ 130 | 131 | # data file 132 | data/ 133 | 134 | network.html 135 | -------------------------------------------------------------------------------- /.pre-commit-config.yaml: -------------------------------------------------------------------------------- 1 | repos: 2 | - repo: https://github.com/pre-commit/pre-commit-hooks 3 | rev: v2.3.0 4 | hooks: 5 | - id: check-yaml 6 | - id: end-of-file-fixer 7 | - id: trailing-whitespace 8 | - repo: https://github.com/psf/black 9 | rev: 22.3.0 10 | hooks: 11 | - id: black 12 | -------------------------------------------------------------------------------- /Dockerfile: -------------------------------------------------------------------------------- 1 | FROM python:3.9 2 | WORKDIR /app.py 3 | COPY . . 4 | RUN pip install -r requirements.txt 5 | EXPOSE 8501 6 | ENTRYPOINT ["streamlit", "run", "app.py"] 7 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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If the Program does not specify a version number of the 576 | GNU General Public License, you may choose any version ever published 577 | by the Free Software Foundation. 578 | 579 | If the Program specifies that a proxy can decide which future 580 | versions of the GNU General Public License can be used, that proxy's 581 | public statement of acceptance of a version permanently authorizes you 582 | to choose that version for the Program. 583 | 584 | Later license versions may give you additional or different 585 | permissions. However, no additional obligations are imposed on any 586 | author or copyright holder as a result of your choosing to follow a 587 | later version. 588 | 589 | 15. Disclaimer of Warranty. 590 | 591 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY 592 | APPLICABLE LAW. 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It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Linkedin Connections Insights 🪄 2 | 3 | [![Streamlit App](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://share.streamlit.io/benthecoder/linkedin-visualizer/main/app.py) 4 | 5 | Get helpful statistics on your LinkedIn connection now! 6 | 7 | Learn more about the project ([Link](https://medium.com/bitgrit-data-science-publication/visualize-your-linkedin-network-with-python-59a213786c4)) 8 | 9 | Check out a walkthrough of the app of my LinkedIn connections ([Link](https://benedictxneo.medium.com/the-missing-feature-on-linkedin-160682a8ccc1)) 10 | 11 | ![all](media/app/everything.png) 12 | 13 | ## Features 14 | 15 | This app tells you the information below 16 | 17 | - Total connections on LinkedIn 18 | - Where most of your connections work at 19 | - Who most of your connections are (what job title they hold) 20 | - Who you last connected with 21 | - Who you first connected with (send them a message!) 22 | - Bar chart of top companies and positions 23 | - Time series plot of your connections over time (find out when you had the most connections) 24 | - A graph/network of your connections (see your connections in a graph) 25 | - A wordcloud of your chat messages with your connections _(new!)_ 26 | - Last but not least, a "who you can cold email" section that provides a list of emails of your connections (perks of LinkedIn connections!) 27 | 28 | [Use it now!](https://share.streamlit.io/benthecoder/linkedin-visualizer/main/app.py) 29 | 30 | ## Word Cloud (New Feature!) 31 | 32 | ![wordcloud](media/app/wordcloud.png) 33 | 34 | ## Run Locally 35 | 36 | Clone the project 37 | 38 | ```bash 39 | git clone https://github.com/benthecoder/linkedin-visualizer.git 40 | ``` 41 | 42 | Go to the project directory 43 | 44 | ```bash 45 | cd linkedin-visualizer 46 | ``` 47 | 48 | ### Using Docker 49 | 50 | Build an Image 51 | 52 | ```bash 53 | docker build -t linkedin-visualizer:1.0 . 54 | ``` 55 | 56 | Run the Image 57 | 58 | ```bash 59 | docker run -p 8501:8501 linkedin-visualizer:1.0 60 | ``` 61 | 62 | The app is now live on http://localhost:8501/ 63 | 64 | ### Using Conda 65 | 66 | Create Conda environment 67 | 68 | ```bash 69 | conda create --name env_name python=3.8 70 | ``` 71 | 72 | Activate the environment 73 | 74 | ```bash 75 | conda activate env_name 76 | ``` 77 | 78 | Install requirements 79 | 80 | ```bash 81 | pip install -r requirements.txt 82 | ``` 83 | 84 | Run streamlit 85 | 86 | ```bash 87 | streamlit run app.py 88 | ``` 89 | 90 | ### Using Poetry 91 | 92 | first make sure you have python 3.8 93 | 94 | ```bash 95 | poetry install 96 | ``` 97 | 98 | ```bash 99 | poetry run streamlit run app.py 100 | ``` 101 | 102 | ## Contributing 103 | 104 | Contributions are always welcome! 105 | 106 | ## All connections 107 | 108 | Here's what happens when I display all of the companies where my connections work at 109 | 110 | 111 | -------------------------------------------------------------------------------- /app.py: -------------------------------------------------------------------------------- 1 | # import libraries 2 | import re 3 | import streamlit as st 4 | import pandas as pd 5 | import janitor 6 | import streamlit.components.v1 as components 7 | from zipfile import ZipFile 8 | from pathlib import Path 9 | import shutil 10 | 11 | # helper functions 12 | from helpers import * 13 | 14 | 15 | def get_data(usr_file, data="connections") -> pd.DataFrame: 16 | 17 | if usr_file is None: 18 | return 19 | 20 | with ZipFile(usr_file, "r") as zipObj: 21 | # Extract all the contents of zip file in current directory 22 | zipObj.extractall("data") 23 | 24 | raw_df = pd.read_csv("data/Connections.csv", skiprows=3) 25 | 26 | if data == "messages": 27 | raw_df = pd.read_csv("data/messages.csv") 28 | 29 | # delete the data 30 | shutil.rmtree("data", ignore_errors=True) 31 | 32 | return raw_df 33 | 34 | 35 | def main(): 36 | # streamlit config 37 | st.set_page_config( 38 | page_title="Linkedin Network Visualizer", 39 | page_icon="🕸️", 40 | initial_sidebar_state="expanded", 41 | layout="wide", 42 | ) 43 | st.markdown( 44 | """ 45 |

Linkedin Network Visualizer

46 |

The missing feature in LinkedIn

47 | 48 | """, 49 | unsafe_allow_html=True, 50 | ) 51 | 52 | # center image 53 | col1, col2, col3 = st.columns([1, 5, 1]) 54 | col2.image("media/app/everything.png", use_column_width=True) 55 | 56 | st.subheader("First, upload your data 💾") 57 | st.caption( 58 | """ 59 | Don't know where to find it? 60 | [Click here](https://github.com/benthecoder/linkedin-visualizer/tree/main/data_guide#how-to-get-the-data). 61 | """ 62 | ) 63 | # upload files 64 | usr_file = st.file_uploader("Drop your zip file 👇", type={"zip"}) 65 | 66 | df_ori = get_data(usr_file) 67 | 68 | # if data not uploaded yet, return None 69 | if df_ori is None: 70 | return 71 | 72 | df_clean = clean_df(df_ori) 73 | 74 | with st.expander("Show raw data"): 75 | st.dataframe(df_ori) 76 | 77 | # Data wrangling 78 | agg_df_company = agg_sum(df_clean, "company") 79 | agg_df_position = agg_sum(df_clean, "position") 80 | 81 | this_month_df = df_clean[ 82 | (df_clean["connected_on"].dt.month == 1) 83 | & (df_clean["connected_on"].dt.year == 2022) 84 | ] 85 | 86 | # Getting some stats 87 | total_conn = len(df_ori) 88 | top_pos = agg_df_position["position"][0] 89 | top_comp = agg_df_company["company"][0] 90 | second_comp = agg_df_company["company"][1] 91 | top_pos_count = agg_df_position["count"][0] 92 | first_c = df_clean.iloc[-1] 93 | last_c = df_clean.iloc[0] 94 | 95 | # calculating stats 96 | st.markdown( 97 | """ 98 | --- 99 | ### Here's a breakdown of your connections 👇 100 | """ 101 | ) 102 | 103 | # Metrics 104 | pos, comp, conn = st.columns(3) 105 | pos.metric("Top Position", f"{top_pos[0:18]}..." if len(top_pos) > 18 else top_pos) 106 | comp.metric( 107 | "Top Company", f"{top_comp[0:18]}..." if len(top_comp) > 18 else top_comp 108 | ) 109 | conn.metric("Total Connections", f"{total_conn}", len(this_month_df)) 110 | 111 | # Summary 112 | st.subheader("Full summary") 113 | st.markdown( 114 | f""" 115 | - You have _{len(this_month_df)}_ new ⭐ connections this month, with a total of _{total_conn}_! 116 | - Most of your connections work at **{top_comp}**" (dream company?), closely followed by {second_comp} 117 | - You love connecting with people 🤵 with the title – **{top_pos}**, _{top_pos_count}_ of them! 118 | - Your first ever connection is {first_c['name']} and they work as a {first_c.position} at {first_c.company} 119 | - Your most recent connection is {last_c['name']} and they work as a {last_c.position} at {last_c.company} 120 | 121 | --- 122 | """ 123 | ) 124 | 125 | st.caption("Scroll down 🖱️⬇️ to see some cool visualizations!") 126 | 127 | # visualizations 128 | st.sidebar.subheader("Bar Charts") 129 | top_n = st.sidebar.slider("Top n", 0, 50, 10, key="1") 130 | 131 | # top n companies and positions 132 | st.subheader(f"Top {top_n} companies & positions") 133 | 134 | company_plt, positions_plt = st.columns(2) 135 | company_plt.plotly_chart(plot_bar(agg_df_company, top_n), use_container_width=True) 136 | positions_plt.plotly_chart( 137 | plot_bar(agg_df_position, top_n), use_container_width=True 138 | ) 139 | 140 | col1, col2 = st.columns(2) 141 | with col1: 142 | with st.expander("View top companies data", expanded=True): 143 | st.dataframe(agg_df_company) 144 | with col2: 145 | with st.expander("View top positions data", expanded=True): 146 | st.dataframe(agg_df_position) 147 | 148 | # connections timeline 149 | st.subheader("Timeline of connections") 150 | st.plotly_chart(plot_timeline(df_clean), use_container_width=True) 151 | 152 | st.write("let's look at on what days do you have the most connections") 153 | st.plotly_chart(plot_day(df_clean), use_container_width=True) 154 | 155 | # cumulative graph 156 | st.subheader("Connections overtime") 157 | st.plotly_chart(plot_cumsum(df_clean), use_container_width=True) 158 | 159 | # Graph network 160 | st.sidebar.subheader("Connection network") 161 | network_num = st.sidebar.slider( 162 | "cutoff point for connections (the smaller it is the larger the network)", 163 | 2, 164 | 50, 165 | 6, 166 | key="3", 167 | ) 168 | 169 | log_bool = False 170 | if st.sidebar.checkbox("Log scale"): 171 | log_bool = True 172 | 173 | st.subheader("Company Network") 174 | generate_network(df_clean, agg_df_company, log_bool, network_num) 175 | 176 | st.subheader("Positions Network") 177 | generate_network(df_clean, agg_df_position, log_bool, network_num) 178 | 179 | # emails 180 | st.write("Now to put your connections to good use") 181 | st.subheader("Who can you cold email 📧?") 182 | 183 | emails = df_clean[df_clean.notnull()["email_address"]].drop( 184 | ["connected_on", "weekday"], axis=1 185 | ) 186 | 187 | st.write(f"Answer: {len(emails)} of your connections shared their emails!") 188 | st.dataframe(emails) 189 | 190 | st.sidebar.write( 191 | "Interested in the code? Head over to the [Github Repo](https://github.com/benthecoder/linkedin-visualizer)" 192 | ) 193 | 194 | # chats 195 | st.markdown("---") 196 | st.subheader("Chats analysis") 197 | messages = get_data(usr_file, data="messages") 198 | messages["DATE"] = pd.to_datetime(messages["DATE"], format="%Y-%m-%d %H:%M:%S UTC") 199 | messages["DATE"] = ( 200 | messages["DATE"].dt.tz_localize("UTC").dt.tz_convert("US/Central") 201 | ) 202 | 203 | total, from_count, to_count = st.columns(3) 204 | total.metric("Total Conversations", f"{messages['CONVERSATION ID'].nunique()}") 205 | from_count.metric("Total Sent", f"{messages.FROM.nunique()}") 206 | to_count.metric("Total Received", f"{messages.TO.nunique()}") 207 | 208 | messages_FROM = agg_sum(messages, "FROM").iloc[1:] 209 | messages_TO = agg_sum(messages, "TO").iloc[1:] 210 | 211 | from_plt, to_plt = st.columns(2) 212 | from_plt.plotly_chart( 213 | plot_bar(messages_FROM, top_n, title="Messages FROM"), use_column_width=True 214 | ) 215 | to_plt.plotly_chart( 216 | plot_bar(messages_TO, top_n, title="Messages TO"), use_column_width=True 217 | ) 218 | 219 | st.write("what hour of the day do you have the most messages?") 220 | 221 | st.plotly_chart(plot_chat_hour(messages), use_container_width=True) 222 | 223 | st.write( 224 | "trend of your messages over time. p.s. hover over the line to see who you talked with" 225 | ) 226 | st.plotly_chart(plot_chat_people(messages), use_container_width=True) 227 | 228 | st.subheader("wordcloud of all chats") 229 | 230 | with st.spinner("Wordcloud generating..."): 231 | st.pyplot(plot_wordcloud(messages)) 232 | 233 | 234 | if __name__ == "__main__": 235 | main() 236 | -------------------------------------------------------------------------------- /data_guide/1.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/benthecoder/linkedin-visualizer/4708e9311ecc63e563a244500cf6ed28ce40bbbe/data_guide/1.png -------------------------------------------------------------------------------- /data_guide/2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/benthecoder/linkedin-visualizer/4708e9311ecc63e563a244500cf6ed28ce40bbbe/data_guide/2.png -------------------------------------------------------------------------------- /data_guide/3.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/benthecoder/linkedin-visualizer/4708e9311ecc63e563a244500cf6ed28ce40bbbe/data_guide/3.png -------------------------------------------------------------------------------- /data_guide/4.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/benthecoder/linkedin-visualizer/4708e9311ecc63e563a244500cf6ed28ce40bbbe/data_guide/4.png -------------------------------------------------------------------------------- /data_guide/5.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/benthecoder/linkedin-visualizer/4708e9311ecc63e563a244500cf6ed28ce40bbbe/data_guide/5.png -------------------------------------------------------------------------------- /data_guide/6.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/benthecoder/linkedin-visualizer/4708e9311ecc63e563a244500cf6ed28ce40bbbe/data_guide/6.png -------------------------------------------------------------------------------- /data_guide/7.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/benthecoder/linkedin-visualizer/4708e9311ecc63e563a244500cf6ed28ce40bbbe/data_guide/7.png -------------------------------------------------------------------------------- /data_guide/README.md: -------------------------------------------------------------------------------- 1 | ## How to get the data? 2 | 3 | First head over to the home page and click on your profile image 4 | 5 | 6 | 7 | Click on the settings 8 | 9 | 10 | 11 | Head to the data privacy tab 12 | 13 | 14 | 15 | Find "Get a copy of your data" 16 | 17 | ![1](4.png) 18 | 19 | Click on download larger data archive 20 | 21 | ![1](5.png) 22 | 23 | Click request archive and type your LinkedIn password 24 | 25 | ![1](6.png) 26 | 27 | Now just wait a few minutes and the archive will arrive to your mail! 28 | ![1](7.png) 29 | 30 | Once you get the data, just drag it to the file uploader and enjoy the insights :) 31 | -------------------------------------------------------------------------------- /helpers.py: -------------------------------------------------------------------------------- 1 | import streamlit.components.v1 as components 2 | import streamlit as st 3 | import pandas as pd 4 | import numpy as np 5 | 6 | # fuzzy match 7 | from thefuzz import fuzz 8 | from thefuzz import process 9 | 10 | # visualizations 11 | import plotly.express as px 12 | import networkx as nx 13 | from pyvis.network import Network 14 | import matplotlib 15 | import matplotlib.pyplot as plt 16 | from PIL import Image 17 | from wordcloud import WordCloud, STOPWORDS, ImageColorGenerator 18 | 19 | # clean text 20 | import re 21 | import nltk 22 | 23 | nltk.download("stopwords") 24 | from nltk.corpus import stopwords 25 | from nltk.stem.porter import PorterStemmer 26 | 27 | 28 | def clean_df(df: pd.DataFrame, privacy: bool = False) -> pd.DataFrame: 29 | """This function cleans the dataframe containing LinkedIn 30 | connections data" 31 | 32 | 33 | Args: 34 | df (pd.DataFrame): data frame before cleaning 35 | 36 | Returns: 37 | pd.DataFrame: data frame after cleaning 38 | """ 39 | if privacy: 40 | df.drop(columns=["first_name", "last_name", "email_address"]) 41 | else: 42 | clean_df = ( 43 | df 44 | # remomves spacing and capitalization in column names 45 | .clean_names() 46 | # drop missing values in company and position 47 | .dropna(subset=["company", "position"]) 48 | # join first name and last name 49 | .concatenate_columns( 50 | column_names=["first_name", "last_name"], 51 | new_column_name="name", 52 | sep=" ", 53 | ) 54 | # drop first name and last name 55 | .drop(columns=["first_name", "last_name"]) 56 | # truncate company names that exceed 57 | .transform_column("company", lambda s: s[:35]) 58 | .to_datetime("connected_on") 59 | .filter_string( 60 | column_name="company", 61 | search_string=r"[Ff]reelance|[Ss]elf-[Ee]mployed|\.|\-", 62 | complement=True, 63 | ) 64 | ) 65 | 66 | # fuzzy match on Data Scientist titles 67 | replace_fuzzywuzzy_match(clean_df, "position", "Data Scientist") 68 | # fuzzy match on Software Engineer titles 69 | replace_fuzzywuzzy_match(clean_df, "position", "Software Engineer", min_ratio=85) 70 | 71 | return clean_df 72 | 73 | 74 | def replace_fuzzywuzzy_match( 75 | df: pd.DataFrame, column: str, query: str, min_ratio: int = 75 76 | ): 77 | """Replace the fuzz matches with query string 78 | thefuzz github : https://github.com/seatgeek/thefuzz 79 | 80 | Args: 81 | df (pd.DataFrame): data frame of connections 82 | column (str): column to performn fuzzy matching 83 | query (str): query string 84 | min_ratio (int, optional): minimum score to remove. Defaults to 60. 85 | """ 86 | 87 | # get list of all unique positions 88 | pos_names = df[column].unique() 89 | 90 | # get top 500 close matches 91 | matches = process.extract(query, pos_names, limit=500) 92 | 93 | # filter matches with ratio >= 75 94 | matching_pos_name = [match[0] for match in matches if match[1] >= min_ratio] 95 | 96 | # for position in above_ratio: 97 | # print(f"replacing {position} with {query}") 98 | 99 | # get rows of all close matches 100 | matches_rows = df[column].isin(matching_pos_name) 101 | 102 | # replace all rows containing close matches with query string 103 | df.loc[matches_rows, column] = query 104 | 105 | 106 | def agg_sum(df: pd.DataFrame, name: str) -> pd.DataFrame: 107 | """Does a value count on company and positions and sorts by count 108 | 109 | Args: 110 | df (pd.DataFrame): data frame before aggregation 111 | name (str): company | position 112 | 113 | Returns: 114 | pd.DataFrame: aggregated data frame 115 | """ 116 | df = df[name].value_counts().reset_index() 117 | df.columns = [name, "count"] 118 | df = df.sort_values(by="count", ascending=False) 119 | return df 120 | 121 | 122 | def plot_bar(df: pd.DataFrame, rows: int, title=""): 123 | height = 500 124 | if rows > 25: 125 | height = 900 126 | 127 | name, count = list(df.columns) 128 | 129 | fig = px.histogram( 130 | df.head(rows), 131 | x=count, 132 | y=name, 133 | template="plotly_dark", 134 | hover_data={name: False}, 135 | ) 136 | fig.update_layout( 137 | height=height, 138 | width=600, 139 | margin=dict(pad=5), 140 | hovermode="y", 141 | yaxis_title="", 142 | xaxis_title="", 143 | title=title, 144 | yaxis=dict(autorange="reversed"), 145 | ) 146 | 147 | return fig 148 | 149 | 150 | def plot_timeline(df: pd.DataFrame): 151 | df = df["connected_on"].value_counts().reset_index() 152 | df.rename(columns={"index": "connected_on", "connected_on": "count"}, inplace=True) 153 | df = df.sort_values(by="connected_on", ascending=True) 154 | fig = px.line(df, x="connected_on", y="count") 155 | 156 | # add range slider 157 | fig.update_layout( 158 | xaxis=dict( 159 | rangeselector=dict( 160 | buttons=list( 161 | [ 162 | dict(count=1, label="1m", step="month", stepmode="backward"), 163 | dict(count=6, label="6m", step="month", stepmode="backward"), 164 | dict(count=1, label="YTD", step="year", stepmode="todate"), 165 | dict(count=1, label="1y", step="year", stepmode="backward"), 166 | dict(step="all"), 167 | ] 168 | ), 169 | bgcolor="black", 170 | ), 171 | rangeslider=dict(visible=True), 172 | type="date", 173 | ), 174 | xaxis_title="Date", 175 | ) 176 | 177 | return fig 178 | 179 | 180 | def plot_day(df: pd.DataFrame): 181 | 182 | # get weekday name 183 | df["weekday"] = df["connected_on"].dt.day_name() 184 | df = df["weekday"].value_counts().reset_index() 185 | df.rename(columns={"index": "weekday_name", "weekday": "count"}, inplace=True) 186 | 187 | cats = [ 188 | "Monday", 189 | "Tuesday", 190 | "Wednesday", 191 | "Thursday", 192 | "Friday", 193 | "Saturday", 194 | "Sunday", 195 | ] 196 | df["weekday_name"] = pd.Categorical( 197 | df["weekday_name"], categories=cats, ordered=True 198 | ) 199 | df = df.sort_values("weekday_name") 200 | 201 | # plot weekday in plotly 202 | fig = px.histogram( 203 | df, 204 | x="weekday_name", 205 | y="count", 206 | template="plotly_dark", 207 | ) 208 | fig.update_layout( 209 | height=500, 210 | width=700, 211 | margin=dict(pad=5), 212 | xaxis_title="", 213 | yaxis_title="", 214 | ) 215 | return fig 216 | 217 | 218 | def plot_cumsum(df: pd.DataFrame): 219 | df = df["connected_on"].value_counts().reset_index() 220 | df.rename(columns={"index": "connected_on", "connected_on": "count"}, inplace=True) 221 | df = df.sort_values(by="connected_on", ascending=True) 222 | df["cum_sum"] = df["count"].cumsum() 223 | 224 | fig = px.area(df, x="connected_on", y="cum_sum") 225 | 226 | fig.update_layout( 227 | xaxis=dict( 228 | rangeslider=dict(visible=True), 229 | type="date", 230 | ), 231 | xaxis_title="Date", 232 | yaxis_title="count", 233 | ) 234 | 235 | return fig 236 | 237 | 238 | def generate_network( 239 | df: pd.DataFrame, agg_df: pd.DataFrame, log_bool: bool, cutoff: int = 5 240 | ): 241 | """This function generates a network of connections of the user 242 | 243 | Args: 244 | df (pd.DataFrame): data frame containing 245 | agg_df (pd.DataFrame): 246 | cutoff (int, optional): the min number of connections at which nodes are created. Defaults to 5. 247 | """ 248 | 249 | col_name = agg_df.columns[0] 250 | 251 | # initialize a graph 252 | g = nx.Graph() 253 | # intialize user as central node 254 | g.add_node("you") 255 | 256 | # create network and provide specifications 257 | nt = Network(height="600px", width="700px", bgcolor="black", font_color="white") 258 | 259 | # reduce size of connections 260 | df_reduced = agg_df.loc[agg_df["count"] >= cutoff] 261 | 262 | # use iterrows tp iterate through the data frame 263 | for _, row in df_reduced.iterrows(): 264 | 265 | # store company name and count 266 | name = row[col_name][:50] 267 | count = row["count"] 268 | 269 | title = f"{name} – {count}" 270 | positions = set([x for x in df[name == df[col_name]]["position"]]) 271 | positions = "".join("
  • {}
    • ".format(x) for x in positions) 272 | 273 | position_list = f"
      {positions}
    " 274 | hover_info = title + position_list 275 | 276 | if log_bool: 277 | count = np.log(count) * 7 278 | 279 | g.add_node(name, size=count * 1.7, title=hover_info, color="#3449eb") 280 | g.add_edge("you", name, color="grey") 281 | 282 | # generate the graph 283 | nt.from_nx(g) 284 | nt.hrepulsion() 285 | nt.toggle_stabilization(True) 286 | nt.show("network.html") 287 | 288 | # Save and read graph as HTML file (on Streamlit Sharing) 289 | try: 290 | path = "/tmp" 291 | nt.save_graph(f"{path}/network.html") 292 | HtmlFile = open(f"{path}/network.html", "r", encoding="utf-8") 293 | 294 | # Save and read graph as HTML file (locally) 295 | except: 296 | path = "/html_files" 297 | nt.save_graph(f"{path}/network.html") 298 | HtmlFile = open(f"{path}/network.html", "r", encoding="utf-8") 299 | 300 | # Load HTML file in HTML component for display on Streamlit page 301 | components.html(HtmlFile.read(), height=650, width=800) 302 | 303 | 304 | def plot_chat_hour(chats: pd.DataFrame): 305 | chats["HOUR"] = chats["DATE"].dt.hour 306 | 307 | # plot chat by hour 308 | 309 | chats["HOUR"].value_counts().reset_index(name="count").sort_values(by="index") 310 | 311 | # plot a value count of hours 312 | fig = px.bar( 313 | chats["HOUR"].value_counts().reset_index(name="count").sort_values(by="index"), 314 | x="index", 315 | y="count", 316 | ) 317 | fig.update_layout(xaxis_title="") 318 | fig.update_xaxes(type="category") 319 | return fig 320 | 321 | 322 | def plot_chat_people(chats: pd.DataFrame): 323 | # join all people on a particular day into a set 324 | chats["DATE"] = chats["DATE"].dt.date 325 | date_people = ( 326 | chats.groupby("DATE")[["FROM", "TO"]] 327 | .agg(lambda x: x.unique().tolist()) 328 | .reset_index() 329 | ) 330 | date_people["people"] = date_people.apply( 331 | lambda x: set(x["FROM"] + x["TO"]), axis=1 332 | ) 333 | date_people["people"] = date_people["people"].apply( 334 | lambda x: x.difference(["Benedict Neo"]) 335 | ) 336 | date_people = date_people[["DATE", "people"]] 337 | date_people 338 | 339 | # counts of date 340 | chats_time = chats["DATE"].value_counts().reset_index() 341 | chats_time.rename(columns={"index": "DATE", "DATE": "count"}, inplace=True) 342 | chats_time.sort_values(by="DATE") 343 | chats_time = chats_time.sort_values(by="DATE") 344 | 345 | # merge date_people with chats_time to get people column 346 | date_count_people = chats_time.merge(date_people, on="DATE", how="left") 347 | # join set into one string and ignore strings that are nan 348 | date_count_people["people"] = date_count_people["people"].apply( 349 | lambda x: "
    ".join(map(str, x) if str(x) != "nan" else x) 350 | ) 351 | date_count_people 352 | 353 | # value count on date column 354 | fig = px.line(date_count_people, x="DATE", y="count", hover_data=["people"]) 355 | 356 | # print("plotly express hovertemplate:", fig.data[0].hovertemplate) 357 | 358 | # change hover template to show only people 359 | fig.update_traces(hovertemplate="%{customdata[0]}") 360 | 361 | # add range slider 362 | fig.update_layout( 363 | xaxis=dict( 364 | rangeselector=dict( 365 | buttons=list( 366 | [ 367 | dict(count=1, label="1m", step="month", stepmode="backward"), 368 | dict(count=6, label="6m", step="month", stepmode="backward"), 369 | dict(count=1, label="YTD", step="year", stepmode="todate"), 370 | dict(count=1, label="1y", step="year", stepmode="backward"), 371 | dict(step="all"), 372 | ] 373 | ), 374 | bgcolor="black", 375 | ), 376 | rangeslider=dict(visible=True), 377 | type="date", 378 | ), 379 | xaxis_title="Date", 380 | ) 381 | return fig 382 | 383 | 384 | @st.cache(hash_funcs={matplotlib.figure.Figure: lambda _: None}) 385 | def plot_wordcloud(chats: pd.DataFrame): 386 | 387 | # remove spam messages (chats with subject lines are usually spam) 388 | chats_nospam = chats[chats.SUBJECT.isnull()] 389 | # remove rows where content contains html tags 390 | chats_nospam_nohtml = chats_nospam[ 391 | chats_nospam.CONTENT.str.contains("<|>") == False 392 | ] 393 | # drop missing value in content column 394 | messages = chats_nospam_nohtml.dropna(subset=["CONTENT"])["CONTENT"].values 395 | 396 | corpus = [] 397 | for i, message in enumerate(messages): 398 | # remove urls 399 | message = re.sub(r"http[s]\S+", "", message) 400 | # keep only letters 401 | message = re.sub("[^a-zA-Z]", " ", messages[i]) 402 | # remove singular letters 403 | message = re.sub(r"\s+[a-zA-Z]\s+", " ", message) 404 | # convert to lower case 405 | message = message.lower() 406 | # split into words 407 | message = message.split() 408 | # remove stop words and singular letters 409 | message = [ 410 | word for word in message if not word in set(stopwords.words("english")) 411 | ] 412 | message = " ".join(message) 413 | corpus.append(message) 414 | 415 | corpus = " ".join(corpus) 416 | 417 | # Import image to np.array 418 | linkedin_mask = np.array(Image.open("media/linkedin.png")) 419 | wordcloud = WordCloud( 420 | width=3000, 421 | height=3000, 422 | random_state=1, 423 | background_color="black", 424 | colormap="Blues", # https://matplotlib.org/stable/tutorials/colors/colormaps.html 425 | collocations=False, # prevent duplicates 426 | stopwords=STOPWORDS, 427 | mask=linkedin_mask, 428 | contour_color="white", 429 | contour_width=2, 430 | ).generate(corpus) 431 | 432 | # show 433 | image_colors = ImageColorGenerator(linkedin_mask) 434 | fig = plt.figure(figsize=[50, 50]) 435 | # ax.imshow(wordcloud.recolor(color_func=image_colors), interpolation="bilinear") 436 | plt.imshow(wordcloud) 437 | plt.axis("off") 438 | 439 | return fig 440 | -------------------------------------------------------------------------------- /media/app/all.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/benthecoder/linkedin-visualizer/4708e9311ecc63e563a244500cf6ed28ce40bbbe/media/app/all.png -------------------------------------------------------------------------------- /media/app/everything.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/benthecoder/linkedin-visualizer/4708e9311ecc63e563a244500cf6ed28ce40bbbe/media/app/everything.png -------------------------------------------------------------------------------- /media/app/wordcloud.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/benthecoder/linkedin-visualizer/4708e9311ecc63e563a244500cf6ed28ce40bbbe/media/app/wordcloud.png -------------------------------------------------------------------------------- /media/linkedin.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/benthecoder/linkedin-visualizer/4708e9311ecc63e563a244500cf6ed28ce40bbbe/media/linkedin.png -------------------------------------------------------------------------------- /poetry.lock: -------------------------------------------------------------------------------- 1 | [[package]] 2 | name = "altair" 3 | version = "4.2.0" 4 | description = "Altair: A declarative statistical visualization library for Python." 5 | category = "main" 6 | optional = false 7 | python-versions = ">=3.7" 8 | 9 | [package.dependencies] 10 | entrypoints = "*" 11 | jinja2 = "*" 12 | jsonschema = ">=3.0" 13 | numpy = "*" 14 | pandas = ">=0.18" 15 | toolz = "*" 16 | 17 | [package.extras] 18 | dev = ["black", "docutils", "flake8", "ipython", "m2r", "mistune (<2.0.0)", "pytest", "recommonmark", "sphinx", "vega-datasets"] 19 | 20 | [[package]] 21 | name = "appnope" 22 | version = "0.1.3" 23 | description = "Disable App Nap on macOS >= 10.9" 24 | category = "main" 25 | optional = false 26 | python-versions = "*" 27 | 28 | [[package]] 29 | name = "asttokens" 30 | version = "2.0.8" 31 | description = "Annotate AST trees with source code positions" 32 | category = "main" 33 | optional = false 34 | python-versions = "*" 35 | 36 | [package.dependencies] 37 | six = "*" 38 | 39 | [package.extras] 40 | test = ["astroid (<=2.5.3)", "pytest"] 41 | 42 | [[package]] 43 | name = "attrs" 44 | version = "22.1.0" 45 | description = "Classes Without Boilerplate" 46 | category = "main" 47 | optional = false 48 | python-versions = ">=3.5" 49 | 50 | [package.extras] 51 | dev = ["cloudpickle", "coverage[toml] (>=5.0.2)", "furo", "hypothesis", "mypy (>=0.900,!=0.940)", "pre-commit", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "sphinx", "sphinx-notfound-page", "zope.interface"] 52 | docs = ["furo", "sphinx", "sphinx-notfound-page", "zope.interface"] 53 | tests = ["cloudpickle", "coverage[toml] (>=5.0.2)", "hypothesis", "mypy (>=0.900,!=0.940)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "zope.interface"] 54 | tests_no_zope = ["cloudpickle", "coverage[toml] (>=5.0.2)", "hypothesis", "mypy (>=0.900,!=0.940)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins"] 55 | 56 | [[package]] 57 | name = "backcall" 58 | version = "0.2.0" 59 | description = "Specifications for callback functions passed in to an API" 60 | category = "main" 61 | optional = false 62 | python-versions = "*" 63 | 64 | [[package]] 65 | name = "backports.zoneinfo" 66 | version = "0.2.1" 67 | description = "Backport of the standard library zoneinfo module" 68 | category = "main" 69 | optional = false 70 | python-versions = ">=3.6" 71 | 72 | [package.extras] 73 | tzdata = ["tzdata"] 74 | 75 | [[package]] 76 | name = "blinker" 77 | version = "1.5" 78 | description = "Fast, simple object-to-object and broadcast signaling" 79 | category = "main" 80 | optional = false 81 | python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" 82 | 83 | [[package]] 84 | name = "cachetools" 85 | version = "5.2.0" 86 | description = "Extensible memoizing collections and decorators" 87 | category = "main" 88 | optional = false 89 | python-versions = "~=3.7" 90 | 91 | [[package]] 92 | name = "certifi" 93 | version = "2022.6.15.1" 94 | description = "Python package for providing Mozilla's CA Bundle." 95 | category = "main" 96 | optional = false 97 | python-versions = ">=3.6" 98 | 99 | [[package]] 100 | name = "cfgv" 101 | version = "3.3.1" 102 | description = "Validate configuration and produce human readable error messages." 103 | category = "dev" 104 | optional = false 105 | python-versions = ">=3.6.1" 106 | 107 | [[package]] 108 | name = "charset-normalizer" 109 | version = "2.1.1" 110 | description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet." 111 | category = "main" 112 | optional = false 113 | python-versions = ">=3.6.0" 114 | 115 | [package.extras] 116 | unicode_backport = ["unicodedata2"] 117 | 118 | [[package]] 119 | name = "click" 120 | version = "8.1.3" 121 | description = "Composable command line interface toolkit" 122 | category = "main" 123 | optional = false 124 | python-versions = ">=3.7" 125 | 126 | [package.dependencies] 127 | colorama = {version = "*", markers = "platform_system == \"Windows\""} 128 | 129 | [[package]] 130 | name = "colorama" 131 | version = "0.4.5" 132 | description = "Cross-platform colored terminal text." 133 | category = "main" 134 | optional = false 135 | python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" 136 | 137 | [[package]] 138 | name = "commonmark" 139 | version = "0.9.1" 140 | description = "Python parser for the CommonMark Markdown spec" 141 | category = "main" 142 | optional = false 143 | python-versions = "*" 144 | 145 | [package.extras] 146 | test = ["flake8 (==3.7.8)", "hypothesis (==3.55.3)"] 147 | 148 | [[package]] 149 | name = "cycler" 150 | version = "0.11.0" 151 | description = "Composable style cycles" 152 | category = "main" 153 | optional = false 154 | python-versions = ">=3.6" 155 | 156 | [[package]] 157 | name = "decorator" 158 | version = "5.1.1" 159 | description = "Decorators for Humans" 160 | category = "main" 161 | optional = false 162 | python-versions = ">=3.5" 163 | 164 | [[package]] 165 | name = "distlib" 166 | version = "0.3.6" 167 | description = "Distribution utilities" 168 | category = "dev" 169 | optional = false 170 | python-versions = "*" 171 | 172 | [[package]] 173 | name = "entrypoints" 174 | version = "0.4" 175 | description = "Discover and load entry points from installed packages." 176 | category = "main" 177 | optional = false 178 | python-versions = ">=3.6" 179 | 180 | [[package]] 181 | name = "executing" 182 | version = "1.0.0" 183 | description = "Get the currently executing AST node of a frame, and other information" 184 | category = "main" 185 | optional = false 186 | python-versions = "*" 187 | 188 | [[package]] 189 | name = "filelock" 190 | version = "3.8.0" 191 | description = "A platform independent file lock." 192 | category = "dev" 193 | optional = false 194 | python-versions = ">=3.7" 195 | 196 | [package.extras] 197 | docs = ["furo (>=2022.6.21)", "sphinx (>=5.1.1)", "sphinx-autodoc-typehints (>=1.19.1)"] 198 | testing = ["covdefaults (>=2.2)", "coverage (>=6.4.2)", "pytest (>=7.1.2)", "pytest-cov (>=3)", "pytest-timeout (>=2.1)"] 199 | 200 | [[package]] 201 | name = "fonttools" 202 | version = "4.37.1" 203 | description = "Tools to manipulate font files" 204 | category = "main" 205 | optional = false 206 | python-versions = ">=3.7" 207 | 208 | [package.extras] 209 | all = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "fs (>=2.2.0,<3)", "lxml (>=4.0,<5)", "lz4 (>=1.7.4.2)", "matplotlib", "munkres", "scipy", "skia-pathops (>=0.5.0)", "sympy", "uharfbuzz (>=0.23.0)", "unicodedata2 (>=14.0.0)", "xattr", "zopfli (>=0.1.4)"] 210 | graphite = ["lz4 (>=1.7.4.2)"] 211 | interpolatable = ["munkres", "scipy"] 212 | lxml = ["lxml (>=4.0,<5)"] 213 | pathops = ["skia-pathops (>=0.5.0)"] 214 | plot = ["matplotlib"] 215 | repacker = ["uharfbuzz (>=0.23.0)"] 216 | symfont = ["sympy"] 217 | type1 = ["xattr"] 218 | ufo = ["fs (>=2.2.0,<3)"] 219 | unicode = ["unicodedata2 (>=14.0.0)"] 220 | woff = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "zopfli (>=0.1.4)"] 221 | 222 | [[package]] 223 | name = "gitdb" 224 | version = "4.0.9" 225 | description = "Git Object Database" 226 | category = "main" 227 | optional = false 228 | python-versions = ">=3.6" 229 | 230 | [package.dependencies] 231 | smmap = ">=3.0.1,<6" 232 | 233 | [[package]] 234 | name = "gitpython" 235 | version = "3.1.27" 236 | description = "GitPython is a python library used to interact with Git repositories" 237 | category = "main" 238 | optional = false 239 | python-versions = ">=3.7" 240 | 241 | [package.dependencies] 242 | gitdb = ">=4.0.1,<5" 243 | 244 | [[package]] 245 | name = "identify" 246 | version = "2.5.5" 247 | description = "File identification library for Python" 248 | category = "dev" 249 | optional = false 250 | python-versions = ">=3.7" 251 | 252 | [package.extras] 253 | license = ["ukkonen"] 254 | 255 | [[package]] 256 | name = "idna" 257 | version = "3.3" 258 | description = "Internationalized Domain Names in Applications (IDNA)" 259 | category = "main" 260 | optional = false 261 | python-versions = ">=3.5" 262 | 263 | [[package]] 264 | name = "importlib-metadata" 265 | version = "4.12.0" 266 | description = "Read metadata from Python packages" 267 | category = "main" 268 | optional = false 269 | python-versions = ">=3.7" 270 | 271 | [package.dependencies] 272 | zipp = ">=0.5" 273 | 274 | [package.extras] 275 | docs = ["jaraco.packaging (>=9)", "rst.linker (>=1.9)", "sphinx"] 276 | perf = ["ipython"] 277 | testing = ["flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"] 278 | 279 | [[package]] 280 | name = "importlib-resources" 281 | version = "5.9.0" 282 | description = "Read resources from Python packages" 283 | category = "main" 284 | optional = false 285 | python-versions = ">=3.7" 286 | 287 | [package.dependencies] 288 | zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""} 289 | 290 | [package.extras] 291 | docs = ["jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx"] 292 | testing = ["pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"] 293 | 294 | [[package]] 295 | name = "ipython" 296 | version = "8.5.0" 297 | description = "IPython: Productive Interactive Computing" 298 | category = "main" 299 | optional = false 300 | python-versions = ">=3.8" 301 | 302 | [package.dependencies] 303 | appnope = {version = "*", markers = "sys_platform == \"darwin\""} 304 | backcall = "*" 305 | colorama = {version = "*", markers = "sys_platform == \"win32\""} 306 | decorator = "*" 307 | jedi = ">=0.16" 308 | matplotlib-inline = "*" 309 | pexpect = {version = ">4.3", markers = "sys_platform != \"win32\""} 310 | pickleshare = "*" 311 | prompt-toolkit = ">3.0.1,<3.1.0" 312 | pygments = ">=2.4.0" 313 | stack-data = "*" 314 | traitlets = ">=5" 315 | 316 | [package.extras] 317 | all = ["Sphinx (>=1.3)", "black", "curio", "ipykernel", "ipyparallel", "ipywidgets", "matplotlib (!=3.2.0)", "nbconvert", "nbformat", "notebook", "numpy (>=1.19)", "pandas", "pytest (<7.1)", "pytest-asyncio", "qtconsole", "testpath", "trio"] 318 | black = ["black"] 319 | doc = ["Sphinx (>=1.3)"] 320 | kernel = ["ipykernel"] 321 | nbconvert = ["nbconvert"] 322 | nbformat = ["nbformat"] 323 | notebook = ["ipywidgets", "notebook"] 324 | parallel = ["ipyparallel"] 325 | qtconsole = ["qtconsole"] 326 | test = ["pytest (<7.1)", "pytest-asyncio", "testpath"] 327 | test_extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.19)", "pandas", "pytest (<7.1)", "pytest-asyncio", "testpath", "trio"] 328 | 329 | [[package]] 330 | name = "jedi" 331 | version = "0.18.1" 332 | description = "An autocompletion tool for Python that can be used for text editors." 333 | category = "main" 334 | optional = false 335 | python-versions = ">=3.6" 336 | 337 | [package.dependencies] 338 | parso = ">=0.8.0,<0.9.0" 339 | 340 | [package.extras] 341 | qa = ["flake8 (==3.8.3)", "mypy (==0.782)"] 342 | testing = ["Django (<3.1)", "colorama", "docopt", "pytest (<7.0.0)"] 343 | 344 | [[package]] 345 | name = "jinja2" 346 | version = "3.1.2" 347 | description = "A very fast and expressive template engine." 348 | category = "main" 349 | optional = false 350 | python-versions = ">=3.7" 351 | 352 | [package.dependencies] 353 | MarkupSafe = ">=2.0" 354 | 355 | [package.extras] 356 | i18n = ["Babel (>=2.7)"] 357 | 358 | [[package]] 359 | name = "joblib" 360 | version = "1.1.0" 361 | description = "Lightweight pipelining with Python functions" 362 | category = "main" 363 | optional = false 364 | python-versions = ">=3.6" 365 | 366 | [[package]] 367 | name = "jsonpickle" 368 | version = "2.2.0" 369 | description = "Python library for serializing any arbitrary object graph into JSON" 370 | category = "main" 371 | optional = false 372 | python-versions = ">=2.7" 373 | 374 | [package.extras] 375 | docs = ["jaraco.packaging (>=3.2)", "rst.linker (>=1.9)", "sphinx"] 376 | testing = ["ecdsa", "enum34", "feedparser", "jsonlib", "numpy", "pandas", "pymongo", "pytest (>=3.5,!=3.7.3)", "pytest-black-multipy", "pytest-checkdocs (>=1.2.3)", "pytest-cov", "pytest-flake8 (<1.1.0)", "pytest-flake8 (>=1.1.1)", "scikit-learn", "sqlalchemy"] 377 | "testing.libs" = ["simplejson", "ujson", "yajl"] 378 | 379 | [[package]] 380 | name = "jsonschema" 381 | version = "4.16.0" 382 | description = "An implementation of JSON Schema validation for Python" 383 | category = "main" 384 | optional = false 385 | python-versions = ">=3.7" 386 | 387 | [package.dependencies] 388 | attrs = ">=17.4.0" 389 | importlib-resources = {version = ">=1.4.0", markers = "python_version < \"3.9\""} 390 | pkgutil-resolve-name = {version = ">=1.3.10", markers = "python_version < \"3.9\""} 391 | pyrsistent = ">=0.14.0,<0.17.0 || >0.17.0,<0.17.1 || >0.17.1,<0.17.2 || >0.17.2" 392 | 393 | [package.extras] 394 | format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"] 395 | format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3986-validator (>0.1.0)", "uri-template", "webcolors (>=1.11)"] 396 | 397 | [[package]] 398 | name = "kiwisolver" 399 | version = "1.4.4" 400 | description = "A fast implementation of the Cassowary constraint solver" 401 | category = "main" 402 | optional = false 403 | python-versions = ">=3.7" 404 | 405 | [[package]] 406 | name = "lazy-loader" 407 | version = "0.1rc2" 408 | description = "lazy_loader" 409 | category = "main" 410 | optional = false 411 | python-versions = ">=3.8" 412 | 413 | [package.extras] 414 | dev = ["flit"] 415 | test = ["black", "flake8", "pre-commit", "pytest"] 416 | 417 | [[package]] 418 | name = "markupsafe" 419 | version = "2.1.1" 420 | description = "Safely add untrusted strings to HTML/XML markup." 421 | category = "main" 422 | optional = false 423 | python-versions = ">=3.7" 424 | 425 | [[package]] 426 | name = "matplotlib" 427 | version = "3.5.3" 428 | description = "Python plotting package" 429 | category = "main" 430 | optional = false 431 | python-versions = ">=3.7" 432 | 433 | [package.dependencies] 434 | cycler = ">=0.10" 435 | fonttools = ">=4.22.0" 436 | kiwisolver = ">=1.0.1" 437 | numpy = ">=1.17" 438 | packaging = ">=20.0" 439 | pillow = ">=6.2.0" 440 | pyparsing = ">=2.2.1" 441 | python-dateutil = ">=2.7" 442 | setuptools_scm = ">=4,<7" 443 | 444 | [[package]] 445 | name = "matplotlib-inline" 446 | version = "0.1.6" 447 | description = "Inline Matplotlib backend for Jupyter" 448 | category = "main" 449 | optional = false 450 | python-versions = ">=3.5" 451 | 452 | [package.dependencies] 453 | traitlets = "*" 454 | 455 | [[package]] 456 | name = "multipledispatch" 457 | version = "0.6.0" 458 | description = "Multiple dispatch" 459 | category = "main" 460 | optional = false 461 | python-versions = "*" 462 | 463 | [package.dependencies] 464 | six = "*" 465 | 466 | [[package]] 467 | name = "natsort" 468 | version = "8.2.0" 469 | description = "Simple yet flexible natural sorting in Python." 470 | category = "main" 471 | optional = false 472 | python-versions = ">=3.6" 473 | 474 | [package.extras] 475 | fast = ["fastnumbers (>=2.0.0)"] 476 | icu = ["PyICU (>=1.0.0)"] 477 | 478 | [[package]] 479 | name = "networkx" 480 | version = "2.8.6" 481 | description = "Python package for creating and manipulating graphs and networks" 482 | category = "main" 483 | optional = false 484 | python-versions = ">=3.8" 485 | 486 | [package.extras] 487 | default = ["matplotlib (>=3.4)", "numpy (>=1.19)", "pandas (>=1.3)", "scipy (>=1.8)"] 488 | developer = ["mypy (>=0.961)", "pre-commit (>=2.20)"] 489 | doc = ["nb2plots (>=0.6)", "numpydoc (>=1.4)", "pillow (>=9.1)", "pydata-sphinx-theme (>=0.9)", "sphinx (>=5)", "sphinx-gallery (>=0.10)", "texext (>=0.6.6)"] 490 | extra = ["lxml (>=4.6)", "pydot (>=1.4.2)", "pygraphviz (>=1.9)", "sympy (>=1.10)"] 491 | test = ["codecov (>=2.1)", "pytest (>=7.1)", "pytest-cov (>=3.0)"] 492 | 493 | [[package]] 494 | name = "nltk" 495 | version = "3.7" 496 | description = "Natural Language Toolkit" 497 | category = "main" 498 | optional = false 499 | python-versions = ">=3.7" 500 | 501 | [package.dependencies] 502 | click = "*" 503 | joblib = "*" 504 | regex = ">=2021.8.3" 505 | tqdm = "*" 506 | 507 | [package.extras] 508 | all = ["matplotlib", "numpy", "pyparsing", "python-crfsuite", "requests", "scikit-learn", "scipy", "twython"] 509 | corenlp = ["requests"] 510 | machine_learning = ["numpy", "python-crfsuite", "scikit-learn", "scipy"] 511 | plot = ["matplotlib"] 512 | tgrep = ["pyparsing"] 513 | twitter = ["twython"] 514 | 515 | [[package]] 516 | name = "nodeenv" 517 | version = "1.7.0" 518 | description = "Node.js virtual environment builder" 519 | category = "dev" 520 | optional = false 521 | python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*" 522 | 523 | [[package]] 524 | name = "numpy" 525 | version = "1.23.3" 526 | description = "NumPy is the fundamental package for array computing with Python." 527 | category = "main" 528 | optional = false 529 | python-versions = ">=3.8" 530 | 531 | [[package]] 532 | name = "packaging" 533 | version = "21.3" 534 | description = 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629 | description = "A small Python module for determining appropriate platform-specific dirs, e.g. a \"user data dir\"." 630 | category = "dev" 631 | optional = false 632 | python-versions = ">=3.7" 633 | 634 | [package.extras] 635 | docs = ["furo (>=2021.7.5b38)", "proselint (>=0.10.2)", "sphinx (>=4)", "sphinx-autodoc-typehints (>=1.12)"] 636 | test = ["appdirs (==1.4.4)", "pytest (>=6)", "pytest-cov (>=2.7)", "pytest-mock (>=3.6)"] 637 | 638 | [[package]] 639 | name = "plotly" 640 | version = "5.10.0" 641 | description = "An open-source, interactive data visualization library for Python" 642 | category = "main" 643 | optional = false 644 | python-versions = ">=3.6" 645 | 646 | [package.dependencies] 647 | tenacity = ">=6.2.0" 648 | 649 | [[package]] 650 | name = "pre-commit" 651 | version = "2.20.0" 652 | description = "A framework for managing and maintaining multi-language pre-commit hooks." 653 | category = "dev" 654 | optional = false 655 | python-versions = ">=3.7" 656 | 657 | [package.dependencies] 658 | cfgv = ">=2.0.0" 659 | identify = ">=1.0.0" 660 | nodeenv = ">=0.11.1" 661 | pyyaml = ">=5.1" 662 | toml = "*" 663 | virtualenv = ">=20.0.8" 664 | 665 | [[package]] 666 | name = "prompt-toolkit" 667 | version = "3.0.31" 668 | description = "Library for building powerful interactive command lines in Python" 669 | category = "main" 670 | optional = false 671 | python-versions = ">=3.6.2" 672 | 673 | [package.dependencies] 674 | wcwidth = "*" 675 | 676 | [[package]] 677 | name = "protobuf" 678 | version = "3.20.1" 679 | description = "Protocol Buffers" 680 | category = "main" 681 | optional = false 682 | python-versions = ">=3.7" 683 | 684 | [[package]] 685 | name = "ptyprocess" 686 | version = "0.7.0" 687 | description = "Run a subprocess in a pseudo terminal" 688 | category = "main" 689 | optional = false 690 | python-versions = "*" 691 | 692 | [[package]] 693 | name = "pure-eval" 694 | version = "0.2.2" 695 | description = "Safely evaluate AST nodes without side effects" 696 | category = "main" 697 | optional = false 698 | python-versions = "*" 699 | 700 | [package.extras] 701 | tests = ["pytest"] 702 | 703 | [[package]] 704 | name = "pyarrow" 705 | version = "9.0.0" 706 | description = "Python library for Apache Arrow" 707 | category = "main" 708 | optional = false 709 | python-versions = ">=3.7" 710 | 711 | [package.dependencies] 712 | numpy = ">=1.16.6" 713 | 714 | [[package]] 715 | name = "pydeck" 716 | version = "0.8.0b3" 717 | description = "Widget for deck.gl maps" 718 | category = "main" 719 | optional = false 720 | python-versions = ">=3.7" 721 | 722 | [package.dependencies] 723 | jinja2 = ">=2.10.1" 724 | numpy = ">=1.16.4" 725 | 726 | [package.extras] 727 | carto = ["pydeck-carto"] 728 | jupyter = ["ipykernel (>=5.1.2)", "ipython (>=5.8.0)", "ipywidgets (>=7,<8)", "traitlets (>=4.3.2)"] 729 | 730 | [[package]] 731 | name = "pygments" 732 | version = "2.13.0" 733 | description = "Pygments is a syntax highlighting package written in Python." 734 | category = "main" 735 | optional = false 736 | python-versions = ">=3.6" 737 | 738 | [package.extras] 739 | plugins = ["importlib-metadata"] 740 | 741 | [[package]] 742 | name = "pyjanitor" 743 | version = "0.23.1" 744 | description = "Tools for cleaning pandas DataFrames" 745 | category = "main" 746 | optional = false 747 | python-versions = ">=3.6" 748 | 749 | [package.dependencies] 750 | multipledispatch = "*" 751 | natsort = "*" 752 | pandas-flavor = "*" 753 | scipy = "*" 754 | 755 | [package.extras] 756 | all = ["biopython", "black (>=19.3b0)", "darglint", "flake8", "hypothesis (>=4.4.0)", "interrogate", "ipython (>7.31.1)", "isort (>=4.3.18)", "mkdocs", "mkdocs-material", "mkdocstrings (<0.18)", "pandas-vet", "pip-tools", "pre-commit", "py (>=1.10.0)", "pyspark", "pytest (>=3.4.2)", "pytest-cov", "pytest-xdist", "tqdm", "unyt"] 757 | biology = ["biopython"] 758 | chemistry = ["tqdm"] 759 | dev = ["black (>=19.3b0)", "darglint", "flake8", "isort (>=4.3.18)", 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version = "0.18.1" 787 | description = "Persistent/Functional/Immutable data structures" 788 | category = "main" 789 | optional = false 790 | python-versions = ">=3.7" 791 | 792 | [[package]] 793 | name = "python-dateutil" 794 | version = "2.8.2" 795 | description = "Extensions to the standard Python datetime module" 796 | category = "main" 797 | optional = false 798 | python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7" 799 | 800 | [package.dependencies] 801 | six = ">=1.5" 802 | 803 | [[package]] 804 | name = "python-levenshtein" 805 | version = "0.12.2" 806 | description = "Python extension for computing string edit distances and similarities." 807 | category = "main" 808 | optional = false 809 | python-versions = "*" 810 | 811 | [[package]] 812 | name = "pytz" 813 | version = "2022.2.1" 814 | description = "World timezone definitions, modern and historical" 815 | category = "main" 816 | optional = false 817 | python-versions = "*" 818 | 819 | [[package]] 820 | name = "pytz-deprecation-shim" 821 | version = "0.1.0.post0" 822 | description = "Shims to make deprecation of pytz easier" 823 | category = "main" 824 | optional = false 825 | python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7" 826 | 827 | [package.dependencies] 828 | "backports.zoneinfo" = {version = "*", markers = "python_version >= \"3.6\" and python_version < \"3.9\""} 829 | tzdata = {version = "*", markers = "python_version >= \"3.6\""} 830 | 831 | [[package]] 832 | name = "pyvis" 833 | version = "0.2.1" 834 | description = "A Python network graph visualization library" 835 | category = "main" 836 | optional = false 837 | python-versions = ">3.6" 838 | 839 | [package.dependencies] 840 | ipython = ">=5.3.0" 841 | jinja2 = ">=2.9.6" 842 | jsonpickle = ">=1.4.1" 843 | networkx = ">=1.11" 844 | 845 | [[package]] 846 | name = "pyyaml" 847 | version = "6.0" 848 | description = "YAML parser and emitter for Python" 849 | category = "dev" 850 | optional = false 851 | python-versions = ">=3.6" 852 | 853 | [[package]] 854 | name = "regex" 855 | version = "2022.8.17" 856 | description = "Alternative regular expression module, to replace re." 857 | category = "main" 858 | optional = false 859 | python-versions = ">=3.6" 860 | 861 | [[package]] 862 | name = "requests" 863 | version = "2.28.1" 864 | description = "Python HTTP for Humans." 865 | category = "main" 866 | optional = false 867 | python-versions = ">=3.7, <4" 868 | 869 | [package.dependencies] 870 | certifi = ">=2017.4.17" 871 | charset-normalizer = ">=2,<3" 872 | idna = ">=2.5,<4" 873 | urllib3 = ">=1.21.1,<1.27" 874 | 875 | [package.extras] 876 | socks = ["PySocks (>=1.5.6,!=1.5.7)"] 877 | use_chardet_on_py3 = ["chardet (>=3.0.2,<6)"] 878 | 879 | [[package]] 880 | name = "rich" 881 | version = "12.5.1" 882 | description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal" 883 | category = "main" 884 | optional = false 885 | python-versions = ">=3.6.3,<4.0.0" 886 | 887 | [package.dependencies] 888 | commonmark = ">=0.9.0,<0.10.0" 889 | pygments = ">=2.6.0,<3.0.0" 890 | typing-extensions = {version = ">=4.0.0,<5.0", markers = "python_version < \"3.9\""} 891 | 892 | [package.extras] 893 | jupyter = ["ipywidgets (>=7.5.1,<8.0.0)"] 894 | 895 | [[package]] 896 | name = "scipy" 897 | version = "1.9.1" 898 | description = "SciPy: Scientific Library for Python" 899 | category = "main" 900 | optional = false 901 | python-versions = ">=3.8,<3.12" 902 | 903 | [package.dependencies] 904 | numpy = ">=1.18.5,<1.25.0" 905 | 906 | [[package]] 907 | name = "semver" 908 | version = "2.13.0" 909 | description = "Python helper for Semantic Versioning (http://semver.org/)" 910 | category = "main" 911 | optional = false 912 | python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" 913 | 914 | [[package]] 915 | name = "setuptools-scm" 916 | version = "6.4.2" 917 | description = "the blessed package to manage your versions by scm tags" 918 | category = "main" 919 | optional = false 920 | python-versions = ">=3.6" 921 | 922 | [package.dependencies] 923 | packaging = ">=20.0" 924 | tomli = ">=1.0.0" 925 | 926 | [package.extras] 927 | test = ["pytest (>=6.2)", "virtualenv (>20)"] 928 | toml = ["setuptools (>=42)"] 929 | 930 | [[package]] 931 | name = "six" 932 | version = "1.16.0" 933 | description = "Python 2 and 3 compatibility utilities" 934 | category = "main" 935 | optional = false 936 | python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*" 937 | 938 | [[package]] 939 | name = "smmap" 940 | version = "5.0.0" 941 | description = "A pure Python implementation of a sliding window memory map manager" 942 | category = "main" 943 | optional = false 944 | python-versions = ">=3.6" 945 | 946 | [[package]] 947 | name = "stack-data" 948 | version = "0.5.0" 949 | description = "Extract data from python stack frames and tracebacks for informative displays" 950 | category = "main" 951 | optional = false 952 | python-versions = "*" 953 | 954 | [package.dependencies] 955 | asttokens = "*" 956 | executing = "*" 957 | pure-eval = "*" 958 | 959 | [package.extras] 960 | tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"] 961 | 962 | [[package]] 963 | name = "streamlit" 964 | version = "1.12.2" 965 | description = "The fastest way to build data apps in Python" 966 | category = "main" 967 | optional = false 968 | python-versions = ">=3.7, !=3.9.7" 969 | 970 | [package.dependencies] 971 | altair = ">=3.2.0" 972 | blinker = ">=1.0.0" 973 | cachetools = ">=4.0" 974 | click = ">=7.0" 975 | gitpython = "!=3.1.19" 976 | importlib-metadata = ">=1.4" 977 | numpy = "*" 978 | packaging = ">=14.1" 979 | pandas = ">=0.21.0" 980 | pillow = ">=6.2.0" 981 | protobuf = ">=3.12,<4" 982 | pyarrow = ">=4.0" 983 | pydeck = ">=0.1.dev5" 984 | pympler = ">=0.9" 985 | python-dateutil = "*" 986 | requests = ">=2.4" 987 | rich = ">=10.11.0" 988 | semver = "*" 989 | toml = "*" 990 | tornado = ">=5.0" 991 | typing-extensions = ">=3.10.0.0" 992 | tzlocal = ">=1.1" 993 | validators = ">=0.2" 994 | watchdog = {version = "*", markers = "platform_system != \"Darwin\""} 995 | 996 | [[package]] 997 | name = "tenacity" 998 | version = "8.0.1" 999 | description = "Retry code until it succeeds" 1000 | category = "main" 1001 | optional = false 1002 | python-versions = ">=3.6" 1003 | 1004 | [package.extras] 1005 | doc = ["reno", "sphinx", "tornado (>=4.5)"] 1006 | 1007 | [[package]] 1008 | name = "thefuzz" 1009 | version = "0.19.0" 1010 | description = "Fuzzy string matching in python" 1011 | category = "main" 1012 | optional = false 1013 | python-versions = "*" 1014 | 1015 | [package.extras] 1016 | speedup = ["python-levenshtein (>=0.12)"] 1017 | 1018 | [[package]] 1019 | name = "toml" 1020 | version = "0.10.2" 1021 | description = "Python Library for Tom's Obvious, Minimal Language" 1022 | category = "main" 1023 | optional = false 1024 | python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*" 1025 | 1026 | [[package]] 1027 | name = "tomli" 1028 | version = "2.0.1" 1029 | description = "A lil' TOML parser" 1030 | category = "main" 1031 | optional = false 1032 | python-versions = ">=3.7" 1033 | 1034 | [[package]] 1035 | name = "toolz" 1036 | version = "0.12.0" 1037 | description = "List processing tools and functional utilities" 1038 | category = "main" 1039 | optional = false 1040 | python-versions = ">=3.5" 1041 | 1042 | [[package]] 1043 | name = "tornado" 1044 | version = "6.2" 1045 | description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed." 1046 | category = "main" 1047 | optional = false 1048 | python-versions = ">= 3.7" 1049 | 1050 | [[package]] 1051 | name = "tqdm" 1052 | version = "4.64.1" 1053 | description = "Fast, Extensible Progress Meter" 1054 | category = "main" 1055 | optional = false 1056 | python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,>=2.7" 1057 | 1058 | [package.dependencies] 1059 | colorama = {version = "*", markers = "platform_system == \"Windows\""} 1060 | 1061 | [package.extras] 1062 | dev = ["py-make (>=0.1.0)", "twine", "wheel"] 1063 | notebook = ["ipywidgets (>=6)"] 1064 | slack = ["slack-sdk"] 1065 | telegram = ["requests"] 1066 | 1067 | [[package]] 1068 | name = "traitlets" 1069 | version = "5.3.0" 1070 | description = "" 1071 | category = "main" 1072 | optional = false 1073 | python-versions = ">=3.7" 1074 | 1075 | [package.extras] 1076 | test = ["pre-commit", "pytest"] 1077 | 1078 | [[package]] 1079 | name = "typing-extensions" 1080 | version = "4.3.0" 1081 | description = "Backported and Experimental Type Hints for Python 3.7+" 1082 | category = "main" 1083 | optional = false 1084 | python-versions = ">=3.7" 1085 | 1086 | [[package]] 1087 | name = "tzdata" 1088 | version = "2022.2" 1089 | description = "Provider of IANA time zone data" 1090 | category = "main" 1091 | optional = false 1092 | python-versions = ">=2" 1093 | 1094 | [[package]] 1095 | name = "tzlocal" 1096 | version 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