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Daily Stock Data 01

The goal of this project is to gather stock,etf, and mutial fund prices and other basic statistics from publicly available resources.

During the bidding, please list your hours of operation in Eastern time so that we can coordinate more easily. Feel free to ask any questions and make recommendations.

The overall project will be broken down into smaller components because some may be run in parallel. This is to throttle the query rate as necessary as well as aid in later modifications and troubleshooting. If this project goes well, there will be many additional modifications and additions. The software will need to be clear and well documented both in code as well as command line usage describing the correct flags and format of commands.

It is intended to initially for US and Canadian exchange data. I will help in locating sources for this data, of which I have some already listed below. The exact sources of data are open to discussion.

This will not be used for high-frequency data gathering so performance and related requirements are not too much of an issue. The scripts will be run intermittently, most likely via cron in a Centos8 linux machine. I am most interested with historical daily data, and perhaps more detail for the current day.

The commandline script will take flags, such as the ticker symbol (or symbols via csv), exchange, data source to use, and date range to download.

It should output one file per symbol and contain as much detail as possible.

Required information to gather on requested date

1- Stock price

2- 52 week high and low

3- Open and Close pricing

4- Daily high/low

Possible data sources include but are not limited to those listed below.

[login to view URL]

[login to view URL]

[login to view URL]:Companies_listed_on_the_Toronto_Stock_Exchange

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[login to view URL]

[login to view URL]

[login to view URL]

Compétences : Python, Linux, Recherche Financière, Web Scraping, Data Scraping

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Concernant l'employeur :
( 2 commentaires ) East Northport, United States

Nº du projet : #24319019